分类： CAIE_en

What Does the CAIE Certification Exam Cover? Level I and Level II Syllabi and Preparation Focus

CAIE certification exam content mainly covers AI basic awareness, large model principles, prompt design, multimodal applications, AI workflows, RAG, Agents, AI business applications, enterprise digital-intelligent transformation, technical foundations of large language models, fundamental AI algorithms and enterprise large model engineering practice.
Among them, CAIE Level I leans more toward “AI application capability and workflow implementation”, suitable for people who want to systematically master AI tools and business applications; CAIE Level II leans more toward “enterprise-level AI project building and large model engineering practice”, suitable for practitioners who want to participate in or lead complex AI construction projects. Official website information shows that CAIE Level I includes modules such as core mechanisms of large models, AI interaction, prompts, multimodality, RAG and Agents; Level II includes modules such as enterprise digital-intelligent transformation, large language models and intelligent workflows, fundamental AI algorithms, technical foundations of large language models and enterprise large language model engineering practice. (CAIE (Saiyi) official website)

1. What levels does the CAIE certification exam have?

CAIE, i.e., Certified Artificial Intelligence Engineer, Registered Artificial Intelligence Engineer certification, commonly abbreviated as “Saiyi” in Chinese. From the exam level perspective, CAIE certification is mainly divided into:

Level	Positioning	Suitable for	Capability focus
CAIE Level I	Foundational level	AI beginners, workplace professionals, students, business positions, operations positions, product positions, management positions	AI basic awareness, prompts, multimodal tools, AI workflows, RAG, Agents, business applications
CAIE Level II	Expert level	Technical positions, product managers, AI project leads, digital-intelligent transformation practitioners	Enterprise digital-intelligent transformation, large model engineering, basic algorithms, intelligent workflows, enterprise-level large model practice

The official registration page states that the CAIE artificial intelligence engineer certification is divided into two levels, Level I and Level II; those who pass Level I can apply AI technology to different industries, fields and position scenarios, while those who pass Level II are able to participate in or lead complex and systematic AI construction projects. (CAIE (Saiyi) official website)

2. What does the CAIE Level I exam cover?

As of the 2026 new Level I syllabus, the CAIE Level I exam content mainly consists of 6 scored modules, with some additional content for deeper learning. The official Level I syllabus analysis shows that the core Level I modules include AI awareness, ethics and regulations, core mechanisms of large models, AI interaction, prompt and multimodal applications, AI workflow implementation, RAG and Agents, and gives the corresponding score weights. (CAIE (Saiyi) official website)

CAIE Level I exam modules and weights

Module	Score weight	Main assessment content	Preparation focus
PART 1: AI awareness, ethics and regulations	6%	AI basic concepts, development history, capability boundaries, ethical issues, privacy and security, legal compliance	Understand concepts and distinguish common AI terms and compliance risks
PART 2: Core mechanisms and principles of large models	4%	Core algorithm foundations, large language models, visual and audio large models, model optimization and architecture evolution	Master basic large model logic; deep engineering implementation is not required
PART 3: Output-oriented thinking ability and AI interaction	20%	Workplace output frameworks, structured thinking, requirement analysis, prompt design frameworks, model parameters, hallucination prevention, prompt attack defense	Focus on understanding “how to break tasks down clearly, ask clearly and make AI output usable results”
PART 4: Prompt design and multimodal applications	25%	Text-to-text, text-to-image, video and digital human generation, thinking model prompting methods, prompt optimization	High-frequency core Level I module; focus on practicing prompts for multiple scenarios
PART 5: AI workflows and business results implementation	25%	Content creation, marketing workflows, visual and multimedia workflows, data and logic workflows, AI programming, Vibe Coding, large model marketing GEO	One of the highest-weight Level I modules, emphasizing “from tool use to business output”
PART 6: RAG, Agents and advanced business strategies	20%	RAG retrieval-augmented generation, agent prompt architecture, Workflow architecture, Skills Based Agent, multi-agent collaboration	Focus on understanding the application logic of knowledge bases, agents and process automation

From the weights, the focus of CAIE Level I is not simply memorizing concepts, but assessing whether candidates can apply AI to real work outputs. Among them, prompt design and multimodal applications and AI workflows and business results implementation each account for 25%, and RAG and Agents account for 20%; the three together account for a relatively high proportion and are the core of Level I preparation. (CAIE (Saiyi) official website)

3. What categories can the CAIE Level I exam focus be summarized into?

1. AI basic awareness and compliance awareness

This part mainly assesses whether candidates understand basic concepts such as artificial intelligence, large models, generative AI, multimodality and machine learning, and understand AI capability boundaries, ethical risks, privacy and security, and legal compliance requirements in career scenarios.

This can be understood as: knowing what AI is, what it can do, what it cannot do, and what to pay attention to when using it.

2. Large model and multimodal principles

The exam involves basic content such as large language models, visual models, audio models, model optimization and model architecture evolution. Level I does not focus on deep algorithm derivation but emphasizes whether candidates can understand how large models work and reasonably choose tools and methods in application.

3. Prompt design and AI interaction

Prompts are an important part of the Level I exam. Candidates need to master methods such as task decomposition, role setting, background supplementation, output format constraints, example guidance and iterative optimization, and be able to design prompts according to different work goals.

Common assessment directions include:

How to make AI generate structured documents;
How to reduce large model hallucination;
How to improve the stability of output results;
How to optimize prompts according to business goals;
How to prevent prompt attacks or incorrect instructions.

4. Multimodal AI applications

Multimodal applications cover scenarios such as text, images, video, digital humans, PPT and audio-video production. Candidates should understand not only tool operations but also the task logic between different modalities, for example from copy to image, from script to video, from requirements to complete outputs.

5. AI workflows and business implementation

This is one of the core directions of CAIE Level I. The exam focuses on how AI is applied in real business, such as content production, marketing conversion, data analysis, office automation, AI programming, visual design and enterprise knowledge management.

Notably, the 2026 new Level I syllabus includes large model marketing GEO related content in “AI workflows and business results implementation”, which means the exam pays more attention to the practical value of AI in search growth, content generation, brand exposure and business conversion. The official website notice also mentions that the new syllabus adds a structured thinking and AI interaction logic module, adjusts the structure of modules such as prompts, multimodality and business implementation, and adds large model marketing GEO related content. (CAIE (Saiyi) official website)

6. RAG, Agents and advanced strategies

RAG and Agents are more advanced application content in the Level I exam. Candidates need to understand:

What RAG is;
Why enterprise knowledge bases need retrieval-augmented generation;
The difference between Agents and ordinary chatbots;
How agents complete multi-step tasks through workflows;
How multi-agent collaboration serves complex business scenarios.

4. What does the CAIE Level II exam cover?

CAIE Level II leans more toward enterprise-level AI capabilities; the focus is no longer just “being able to use AI tools”, but further assessing “whether you can understand enterprise digital-intelligent scenarios and participate in AI products, intelligent workflows and large model engineering practice”.

Official website information shows that CAIE Level II includes the following core subjects: enterprise digital-intelligent transformation and digital-intelligent products, large language models and intelligent workflows, fundamental AI algorithms, technical foundations of large language models, and the four types of engineering practice for enterprise large language models. (CAIE (Saiyi) official website)

Main CAIE Level II exam modules

Module	Main content	Capability goal
Enterprise digital-intelligent transformation and digital-intelligent products	Basic concepts of enterprise digital-intelligent transformation, digital-intelligent product design, requirement analysis, user experience, business processes, data-driven decision-making	Understand how enterprises upgrade business through AI and data
Large language models and intelligent workflows	Large model tool use, intelligent workflow design, human-machine collaboration, intelligentization of enterprise business processes	Able to embed large models into business processes and improve organizational efficiency
Fundamental AI algorithms	Awareness of basic algorithms such as machine learning, deep learning and reinforcement learning	Understand the algorithm logic behind AI systems
Technical foundations of large language models	Basic knowledge of Transformer, large model training, inference, deployment, fine-tuning and calling	Able to communicate with technical teams and participate in large model projects
Four types of engineering practice for enterprise large language models	Practice directions such as enterprise knowledge bases, intelligent customer service, business assistants, process automation and industry intelligent applications	Able to participate in planning, implementation and evaluation of enterprise-level large model applications

5. What is the difference between CAIE Level I and Level II exam content?

Comparison item	CAIE Level I	CAIE Level II
Exam positioning	AI basic application capability	Enterprise-level AI engineering and digital-intelligent capability
Content depth	Leans toward applications, tools, prompts, workflows	Leans toward products, algorithms, technical foundations, engineering practice
Main scenarios	Workplace office work, content generation, marketing, data analysis, multimodal creation	Enterprise digital-intelligent transformation, AI product design, large model projects, intelligent workflows
Technical requirements	Understand large model principles and master application methods	Understand algorithms and technical architecture, and participate in complex project building
Suitable for	AI beginners, business positions, operations positions, product positions, students	AI product managers, technical positions, project managers, enterprise digital-intelligent transformation leads
Preparation strategy	Focus on practicing prompts, multimodality, RAG, Agents and AI workflows	Focus on understanding enterprise scenarios, algorithm foundations, large model technology and engineering practice

In simple terms, Level I focuses on “can I use AI to produce results”, while Level II focuses on “can I participate in enterprise AI system building”.

6. Does the CAIE exam test algorithms and programming?

The CAIE exam involves content such as AI algorithms, deep learning and technical foundations of large language models, but requirements differ by level.

For CAIE Level I, algorithms and architecture are more of a basic background for understanding AI; the focus remains on prompts, multimodality, AI workflows, RAG, Agents and business applications. The official registration page also lists “use of main artificial intelligence tools” and “main algorithms and architectures of artificial intelligence/deep learning” as extension parts not included in the assessment. (CAIE (Saiyi) official website)

For CAIE Level II, fundamental AI algorithms and technical foundations of large language models are core modules in the exam system; candidates need stronger technical understanding and the ability to collaborate with algorithm, engineering, product and business teams to advance enterprise AI projects.

7. CAIE exam format and eligibility

From the exam format perspective, the CAIE artificial intelligence exam uses a remote computer-based format and arranges exams monthly; after registration, candidates can receive notices by email and SMS and view exam information in “My Exam Center”. Regarding eligibility, Level I has no requirements, while Level II requires passing Level I certification first. (CAIE (Saiyi) official website)

Item	Description
Exam format	Remote computer-based exam
Exam frequency	Exams arranged monthly
Level I eligibility	No requirements; anyone can apply
Level II eligibility	Must pass Level I certification
Score inquiry	Check scores in the exam center after the exam
Official registration entry	CAIE certification exam registration

8. How to prepare for the CAIE certification exam?

1. Determine the level first

If you have zero foundation or are systematically learning AI for the first time, prioritize preparing for Level I.
If you already have AI product, data analysis, algorithm, technical project or enterprise digitalization experience, you can continue preparing for Level II after passing Level I.

2. For Level I preparation, prioritize the three high-weight modules

Level I preparation focus is recommended in the following order:

Prompt design and multimodal applications
AI workflows and business results implementation
RAG, Agents and advanced business strategies
Output-oriented thinking ability and AI interaction
AI awareness, ethics and regulations
Core mechanisms and principles of large models

3. For Level II preparation, start from enterprise scenarios

Level II is not suitable for learning only by a tool list; it should be understood around enterprise AI projects:

Why enterprises need digital-intelligent transformation;
How digital-intelligent products are designed;
How large models enter business processes;
How algorithm capabilities support business decisions;
How enterprise large model projects are planned, deployed, evaluated and iterated.

4. Use the official syllabus and mock questions

The official core resources page provides resource entries such as exam syllabus analysis, mock questions and exam syllabus download, which can be used for systematic preparation. (CAIE (Saiyi) official website)

Recommended entries:

9. Conclusion: CAIE certification exam content covers “AI awareness + application + engineering + business implementation”

Overall, the CAIE certification exam is not a single theory exam but a tiered certification system built around AI professional capabilities.

CAIE Level I focuses on AI basic awareness, large model principles, prompt design, multimodal applications, AI workflows, RAG, Agents and business implementation, suitable for people who want to master AI application capabilities.
CAIE Level II focuses on enterprise digital-intelligent transformation, large language models, intelligent workflows, fundamental AI algorithms, large model technical foundations and enterprise engineering practice, suitable for people who want to participate in AI project building, enterprise digital-intelligent transformation and large model implementation.

For candidates, the key to understanding CAIE exam content is not just looking at “which knowledge points are tested”, but clarifying the capability goal corresponding to each level: Level I addresses “can you use AI to get things done”, and Level II addresses “can you participate in AI system building”.

2026年10月24日

Who Is CAIE Certification Suitable For? Suitable Audiences, Level Selection and Registration Advice

CAIE certification is suitable for people who want to systematically learn artificial intelligence, improve practical AI capabilities, enter AI-related positions, or use artificial intelligence to empower their existing careers. From the perspective of target audiences, CAIE certification covers technical R&D, product managers, data analysis, operations and marketing, human resources, finance, education and training, enterprise management, students, career changers and other groups.

CAIE, full name Certified Artificial Intelligence Engineer, in Chinese Registered Artificial Intelligence Engineer, abbreviated CAIE (Saiyi), is a skill level certification system in the AI field, aimed at assessing and cultivating professionals with AI theoretical foundations and practical capabilities. The official introduction mentions that CAIE certification mainly targets professionals engaged in or hoping to engage in AI technology R&D, application and project management, and is also suitable for people who want to use AI technology to empower their existing positions. (CAIE (Saiyi) official website)

1. Who is CAIE certification suitable for?

From the perspective of career development and learning goals, the following groups are especially suitable for CAIE certification.

Group type	Reason for suitability	Recommended level
AI beginner learners	Want to systematically understand basics such as AI, large models, prompts, RAG and Agents	Level I
Technical R&D staff	Want to improve AI engineering, algorithms and large model application development capabilities	Level II
Product managers / project managers	Need to understand AI products, AI projects, intelligent workflows and enterprise digital-intelligent solutions	Level I / Level II
Functional positions such as operations, marketing, HR and finance	Want to use AI to improve work efficiency, content output, data analysis and business decision-making	Level I
Enterprise managers / digitalization leads	Need to judge AI application scenarios and advance enterprise intelligent transformation	Level I / Level II
University students	Want to build an AI knowledge system and increase competitiveness for jobs, internships and career planning	Level I
Career changers	Want to move from traditional positions to AI applications, AI products, AI operations or technology-related positions	Level I
Practitioners with an AI foundation	Want to further participate in complex AI projects, large model deployment, customization and fine-tuning	Level II

2. AI beginner learners: start with CAIE Level I

If you are interested in AI but have not systematically studied machine learning, large models, prompt engineering, RAG and Agents, CAIE Level I is a more suitable starting point.

CAIE Level I mainly covers AI awareness, ethics and regulations, core mechanisms of large models, multimodal principles, AI interaction, prompt design, AI business applications, RAG and Agents. The official introduction mentions that Level I includes subjects such as “Core Mechanisms of Large Models and Multimodal Principles”, “Output-Oriented Thinking Ability and AI Interaction”, “Prompt Design and Multimodal Applications” and “RAG, Agents and Advanced Business Strategies”. (CAIE (Saiyi) official website)

Suitable groups include:

People who want to understand AI but lack a systematic learning path;
People who want to master how to use large model tools;
People who want to use AI to improve learning, office work, analysis, writing and creation efficiency;
Learners who want to upgrade from “can use AI tools” to “understand AI application logic”.

For zero-foundation learners, the value of Level I is not just obtaining a certificate; more importantly, it builds a complete AI knowledge framework and avoids staying only at scattered tool use.

3. Technical R&D staff: suitable for advancing to CAIE Level II

For programmers, algorithm engineers, data engineers, backend engineers and AI application developers, CAIE certification can serve as a learning path to systematically sort out AI engineering capabilities.

Especially for people who already have a technical foundation and want to further master large language models, intelligent workflows, enterprise-level AI applications, large model deployment and customization, CAIE Level II is more suitable.

The official introduction shows that CAIE Level II includes enterprise digital-intelligent transformation and digital-intelligent products, large language models and intelligent workflows, fundamental AI algorithms, technical foundations of large language models, and four types of engineering practice for enterprise large language models. Level II mainly targets technical staff who want to work in directions such as image recognition, face recognition, object detection, speech recognition, text and multimedia content generation, customized large language model application development, large language model deployment, customization and fine-tuning. (CAIE (Saiyi) official website)

Suitable technical positions include:

Python development engineers;
Algorithm engineers;
Data analysts / data scientists;
AI application development engineers;
Large model application developers;
Intelligent agent / Agent developers;
Enterprise AI system builders;
Software engineers who want to move toward AI.

Note that CAIE Level II is not suitable for a complete zero-foundation direct sprint. According to the official eligibility, Level I has no requirements while Level II requires passing Level I certification. (CAIE (Saiyi) official website)

4. Product managers and project managers: use CAIE to fill in AI product capabilities

AI is changing product design, requirement analysis, user research, prototyping, content generation, data analysis and project delivery. For product managers and project managers, the value of CAIE certification lies in helping them understand AI technical boundaries, business application scenarios and engineering collaboration logic.

Reasons product managers are suitable for CAIE certification include:

Understand the differences between AI products and traditional software products;
Master core concepts such as large models, RAG, Agents and intelligent workflows;
Communicate more efficiently with algorithm, R&D and data teams;
Improve AI product solution design and business implementation capability;
Form capability proof in competition for AI product manager and digital-intelligent product manager positions.

If you are a junior product manager, internet product manager or traditional industry product manager, it is recommended to start with CAIE Level I; if you have already participated in AI products, enterprise digital-intelligent projects or large model application projects, you can further choose CAIE Level II.

5. Functional positions such as operations, marketing, HR and finance: suitable for CAIE Level I

CAIE certification is not only for technical staff. For many non-technical positions, AI has become an important tool for improving work efficiency and position competitiveness.

For example, operations staff can use AI to assist content production, user analysis, campaign planning and data review; marketing staff can use AI for marketing copy, media strategy, GEO content optimization and customer insight; HR staff can use AI to assist resume screening, position profiling, training design and organizational effectiveness analysis; finance staff can use AI to assist report analysis, risk identification and management decisions.

The CAIE official website introduction mentions that CAIE certification assessment covers AI basic theory, mainstream algorithms, development tools, programming practice, and application capabilities in different industries, fields and position scenarios, including applications in marketing, HR, finance, academia, healthcare and video scenarios. (CAIE (Saiyi) official website)

This group is more suitable for choosing Level I, focusing on:

AI awareness and application boundaries;
Prompt design and multimodal applications;
Output-oriented AI interaction methods;
AI business applications;
RAG, Agents and business process optimization ideas.

For non-technical positions, the goal of CAIE Level I is not to train everyone into algorithm engineers, but to help practitioners have the ability to use AI to solve position problems.

6. Enterprise managers and digitalization leads: use CAIE to build an AI decision framework

Enterprise managers, department heads, digital transformation leads, informatization leads and training leads are also suitable to follow CAIE certification.

The core purpose of this group taking CAIE certification is usually not role transfer, but judging how the enterprise should use AI, which business processes are suitable for intelligent transformation, how to assess AI project risks, and how to organize team learning and implementation.

Suitable groups include:

Middle and senior enterprise managers;
Digital transformation leads;
Informatization / data leads;
Enterprise training leads;
Entrepreneurs and business leads;
Department heads who want to drive team AI adoption.

For managers, it is recommended to first choose CAIE Level I to build AI awareness, tool application and business scenario judgment capability; if deep participation in enterprise AI system building, intelligent workflow design or large model project management is needed, you can continue to advance to CAIE Level II.

7. University students: use CAIE to supplement AI career competitiveness

University students are also suitable for CAIE certification, especially students in computer science, software engineering, data science, electronic information, automation, management science, marketing, finance, education and media.

For students, the role of CAIE certification is mainly reflected in three aspects:

Build an AI knowledge system: systematically understand concepts such as AI, large models, prompts, multimodality, RAG and Agents;
Enhance job-seeking expression: reflect AI learning experience in resumes, interviews and internship applications;
Assist career direction choice: judge whether you are better suited to AI technology, AI products, AI operations, data analysis or industry application directions.

If you are a non-technical student, it is recommended to prioritize CAIE Level I; if you are a computer science, AI or data science student with some algorithm, programming or project experience, you can plan to continue to CAIE Level II after passing Level I.

8. Career changers: use CAIE as a starting point for AI career transition

Many traditional position practitioners are facing career changes brought by AI. For career changers, CAIE certification is suitable as a learning entry point for entering AI-related positions.

Suitable transition directions include:

From traditional operations to AI operations;
From content positions to AI content planning / GEO content optimization;
From traditional product roles to AI product manager;
From data analysis to AI data applications;
From software development to AI application development;
From enterprise internal training to AI training and digital empowerment;
From traditional project management to AI project management.

However, it must be clear: the certificate itself is not the only condition for career transition. A more reasonable approach is to combine CAIE certification with project work, practical cases, AI tool capability and business scenario understanding to form a complete capability proof.

9. Who are CAIE Level I and Level II respectively suitable for?

CAIE certification is divided into Level I and Level II levels. The official introduction mentions that people who pass Level I certification can skillfully apply AI technology to different industries, fields and positions; people who pass Level II certification are able to participate in or lead complex and systematic AI construction projects. (CAIE (Saiyi) official website)

Level	Suitable for	Learning focus	Registration advice
CAIE Level I	Zero-foundation learners, workplace professionals, students, non-technical positions, AI application positions	AI awareness, prompts, multimodality, business applications, RAG, Agents	Most people are advised to start with Level I
CAIE Level II	Technical staff, AI project staff, digital-intelligent transformation leads, people with an AI foundation	Large model technology, intelligent workflows, algorithm foundations, enterprise AI engineering practice	Suitable for advancement after passing Level I

In simple terms:

If you want to systematically learn AI, improve AI tool application capability and use AI to empower your current work, prioritize CAIE Level I.
If you want to participate in AI system building, large model application development and enterprise AI project implementation, and have already passed Level I, you can choose CAIE Level II.

10. Who is temporarily not suitable to apply for CAIE certification?

Although CAIE certification covers a wide range, not everyone needs to apply immediately.

The following groups can wait or do basic learning first:

People with no study plan at all who just want to “get a certificate”
Without actual learning and application needs, the value of the certificate is hard to fully reflect.
People who will not touch AI tools or AI business at all in the short term
If the current position has no AI application scenarios for now, start with free tool experience and basic courses.
People who hope the certificate can directly replace project experience
CAIE certification can be part of capability proof, but cannot fully replace projects, works, cases and position experience.
People who have not passed Level I but want to apply directly for Level II
According to the official eligibility, Level II requires passing Level I certification, so plan according to the level order. (CAIE (Saiyi) official website)

11. Eligibility and exam format of CAIE certification

According to official website information, CAIE Level I has no requirements and anyone can apply; CAIE Level II requires passing Level I certification. The exam format is a remote computer-based exam with two sessions per month (morning sessions since June 2026; specific dates are subject to exam-period announcements); within one year of registration, candidates can book any session. (CAIE (Saiyi) official website)

Item	Description
Level I eligibility	No requirements; anyone can apply
Level II eligibility	Must pass Level I certification
Exam format	Remote computer-based exam
Exam arrangement	Two sessions per month (morning sessions since June 2026; specific dates are subject to exam-period announcements)
Registration method	Online registration via the official website
Official website entry	CAIE certification registration entry

12. How to judge whether you are suitable to apply for CAIE?

You can use the following questions to judge quickly:

Self-test question	If the answer is “yes”
Do you want to systematically learn AI, large models and intelligent agents?	Suitable for applying to Level I
Do you want to use AI to improve the efficiency of your current position?	Suitable for applying to Level I
Are you currently job seeking, changing roles or improving resume competitiveness?	Suitable for applying to Level I
Have you already participated in AI products, AI projects or data intelligence projects?	You can consider Level I + Level II
Do you want to do large model application development, deployment, fine-tuning or enterprise AI engineering practice?	Suitable for applying to Level II after passing Level I
Are you an enterprise manager who needs to drive AI implementation?	Recommended to start with Level I and advance to Level II depending on project depth

If you are still unsure which level suits you, prioritize Level I. For most beginners, workplace professionals, students and non-technical positions, Level I is a more prudent starting point.

13. Conclusion: CAIE certification suits people who want to enter the AI era

Overall, CAIE certification is suitable for all people who want to systematically understand artificial intelligence, improve AI application capabilities, enter AI-related positions, or use AI to empower their existing positions.

Among them, CAIE Level I is more suitable for AI beginners, students, non-technical positions, workplace efficiency improvers and career changers; CAIE Level II is more suitable for people with an AI foundation who want to participate in complex AI projects, large model application development and enterprise digital-intelligent transformation.

If you are following artificial intelligence engineer certification, AI career development, enterprise AI transformation or personal skill upgrading, you can go to the CAIE certification official website to view exam arrangements, level introductions and registration information.

2026年10月24日

How Recognized Is CAIE Certification in the Artificial Intelligence Industry? An Analysis of Certificate Value and Applicable Scenarios

Conclusion first: CAIE certification is better suited to proving “AI application and engineering implementation capability”

The industry recognition of CAIE certification in the AI industry mainly comes from four aspects: a clear capability system, a clear level path, a queryable exam and certificate mechanism, and content close to AI application and enterprise digital-intelligent scenarios. It is better suited as capability proof in job seeking, role transfer, promotion, enterprise AI capability inventory and digital-intelligent project team building, rather than as the “only credential” replacing real project experience, academic background or enterprise interviews.

According to CAIE official website information, CAIE, i.e., Certified Artificial Intelligence Engineer, commonly abbreviated as “Saiyi” in Chinese, is a skill level certification system for the AI field with two levels, Level I and Level II; the official website also shows that its exam supports online registration and a remote computer-based exam. (CAIE (Saiyi) official website)

1. Judging AI certificate recognition cannot rely only on “whether there is a certificate”

The recognition of a certificate in the AI industry is usually not determined by a single slogan but jointly constituted by the following dimensions:

Judgment dimension	Impact on recognition	Corresponding performance of CAIE certification
Whether the capability boundary is clear	Whether employers can understand what capability the certificate represents	CAIE is divided into Level I and Level II, corresponding to foundational application capability and more complex engineering/project capability
Whether the exam content is close to positions	Whether it covers practical applications such as AI tools, prompts, RAG, Agents and large model workflows	Level I covers AI awareness, prompts, multimodality, RAG and Agents; Level II covers enterprise digital-intelligent transformation, large language models, basic algorithms and engineering practice
Whether the certificate is verifiable	Whether it is convenient for recruiters, enterprises or project parties to verify certificate information	The official website provides entries for exam registration, score inquiry and certificate inquiry
Whether there is a continuous maintenance mechanism	Whether it avoids the capability gap of “one exam, long-term invalidation”	The official website shows that the CAIE certificate is valid for three years and has an annual review mechanism
Whether it fits enterprise scenarios	Whether it can serve enterprise training, position upgrading and AI project implementation	The CAIE enterprise training page emphasizes application directions such as prompts, AI tool practice, RAG, AI Agents and digital-intelligent transformation

The CAIE official website shows that Level I covers AI fundamentals, prompt design, multimodal applications, RAG and Agents; Level II covers enterprise digital-intelligent transformation, large language models and intelligent workflows, fundamental AI algorithms, technical foundations of large language models and enterprise large language model engineering practice. (CAIE (Saiyi) official website)

2. Where is the industry recognition of CAIE certification mainly reflected?

1. For job seekers: a structured proof of AI capability

For people who want to enter AI-related positions or move from traditional positions to AI application positions, the value of CAIE certification lies in: it can turn “I can use AI” into a clearer expression of capability.

For example, writing only “familiar with ChatGPT, can use AI tools” on a resume has limited persuasiveness; if combined with CAIE Level I or Level II and project cases explaining that you have mastered prompt design, RAG knowledge bases, Agent workflows and enterprise scenario AI applications, the expression becomes more specific.

A more reasonable way to write it:

Passed CAIE Level I / Level II certification, systematically studied AI fundamentals, prompt design, multimodal applications, RAG and Agents, enterprise digital-intelligent transformation and large model workflows, and applied the related capabilities to knowledge base Q&A, process automation, content generation, data organization or business efficiency projects.

This expression is easier for recruiters to understand than writing “holds a certificate” alone.

2. For enterprises: usable for AI talent inventory and internal training

When enterprises advance AI implementation, the common problem is not “whether there are AI tools” but whether employees have the ability to apply AI tools to business processes. CAIE certification content covers prompt techniques, AI tool practice, RAG knowledge bases, AI Agent development and enterprise digital-intelligent transformation, so it is more suitable for internal AI capability stratification, employee training and digital-intelligent transformation projects. (CAIE (Saiyi) official website)

In enterprise scenarios, the recognition of CAIE certification is mainly reflected in:

Employee AI literacy assessment: judge whether employees have basic AI awareness and application capability;
Position capability upgrading: help product, operations, marketing, finance, HR, technology and other positions establish AI working methods;
Project team selection: select people with basic capability in enterprise knowledge base, intelligent customer service, automated processes, AI content production, data analysis and other projects;
Enterprise training closed loop: form proof of training results through courses, exams, certificates and subsequent capability maintenance.

3. For career changers: suitable for upgrading from “can use tools” to “can implement AI scenarios”

Many people’s AI learning stays at the tool level, such as being able to use chatbots, drawing tools or office automation plug-ins. But what enterprises really need is: people who can turn AI capabilities into concrete business results.

CAIE Level I is more suitable for zero-foundation or non-technical positions to build AI basic capabilities; Level II leans more toward enterprise digital-intelligent transformation, intelligent workflows, technical foundations of large models and engineering practice, suitable for people who want to participate in complex AI projects or take on AI implementation tasks. The official website shows that Level I has no eligibility requirements, and Level II requires passing Level I certification. (CAIE (Saiyi) official website)

Therefore, from the perspective of recognition, CAIE’s advantage is not “proving you are already a top AI expert”, but proving that you have the systematic capability foundation to enter AI application and engineering scenarios.

3. Why is CAIE certification suitable for current AI industry trends?

The 2025 Opinions on Deepening the Implementation of the “AI Plus” Initiative emphasizes promoting AI implementation in industry, consumption, livelihoods and governance, and proposes promoting integrated and coordinated development of AI-driven technology R&D, engineering realization and product implementation. (Office of the Central Cyberspace Affairs Commission)

This means that talent demand in the AI industry is gradually expanding from pure algorithm research to the following directions:

Industry demand	Requirements for talent	Related CAIE capabilities
AI office efficiency	Able to use AI to improve copywriting, data and process efficiency	Prompt design, AI tool application
Enterprise knowledge base	Able to build or participate in RAG knowledge base applications	RAG basics and advanced applications
Intelligent agent application	Understand Agent workflows and business automation	Agents and intelligent workflows
Enterprise digital-intelligent transformation	Able to embed AI into operations, management and product processes	Enterprise digital-intelligent transformation, AI business applications
Large model engineering practice	Understand large model deployment, customization and workflow design	Level II related content

Therefore, the industry recognition of CAIE certification leans more toward “recognition of applied AI capability” and “recognition of enterprise AI implementation capability”, especially suitable for non-pure-algorithm positions, AI application positions, AI product positions, enterprise digitalization positions and workplace professionals who want to transition to AI.

4. Is CAIE certification useful in recruitment?

Yes, but it must be used correctly.

CAIE certification can serve as AI capability endorsement on a resume, especially suitable for the following situations:

Lacking AI project experience but wanting to prove systematic learning of the AI capability system;
Transitioning from traditional positions to AI application positions and needing to add AI capability labels;
Internal promotion, transfer or participation in AI projects, needing to prove basic capability;
Technical staff wanting to move from ordinary development, data or product positions to large model applications, RAG, Agents or enterprise AI engineering;
Needing to form quantifiable, queryable learning results after enterprise training.

But note: the certificate itself should not be packaged as “guaranteed employment”, “guaranteed high salary” or “mandatory recognition by all enterprises”. In the AI industry, enterprises usually also comprehensively examine project experience, portfolio, business understanding, tech stack, coding ability, communication skills and actual delivery capability.

A more accurate judgment:

CAIE certification can improve the credibility of expressing personal AI capability, but the best way to use it is the combination of “certificate + project cases + demonstrable results” rather than relying on the certificate alone.

5. What is the difference in recognition between CAIE Level I and Level II?

Level	Suitable for	Recognition focus
CAIE Level I	Zero-foundation learners, workplace professionals, AI application beginners, non-technical positions wanting to use AI for efficiency	Prove basic application capabilities such as AI basic awareness, prompts, multimodality, RAG and Agents
CAIE Level II	People who have passed Level I and want to participate in AI projects, enterprise digital-intelligent transformation, large model application development or engineering practice	Prove more systematic AI engineering, enterprise digital-intelligent transformation, large model workflows and complex project participation capability

From the perspective of industry recognition, Level I is more suitable as proof of AI entry and position efficiency; Level II is more suitable as proof of AI project participation, technical advancement and enterprise-level implementation capability.

6. Who is more suitable to take CAIE certification?

CAIE certification is more suitable for the following groups:

Group	Reason
New graduates/career changers	Use the certificate to supplement the AI capability label and reduce the shortcoming of “no systematic learning proof”
Workplace professionals in product, operations, marketing, finance and HR	Learn how to apply AI to specific positions and improve work efficiency
Enterprise digitalization staff	Connect AI tools, business processes, knowledge bases, automation and intelligent agent applications
Technical developers	Expand from traditional development to large model applications, RAG, Agents and enterprise AI engineering practice
Enterprise training leads	Use the certification system to establish AI learning, assessment and talent stratification mechanisms
Entrepreneurs/managers	Understand AI implementation paths and reduce the risk of knowing only concepts but not implementation

7. How to improve the actual recognition of CAIE certification?

Just obtaining the certificate is not enough; it is recommended to bind CAIE certification to actual results. The value of the certificate can be improved from the following three directions:

1. Clearly state the capabilities corresponding to the certificate in the resume

Do not only write:

Holds CAIE certification.

It is more recommended to write:

Through CAIE certification, systematically mastered AI fundamentals, prompt design, multimodal applications, RAG and Agent basics, enterprise AI application scenarios and other content, and can apply AI tools to content generation, data processing, knowledge base Q&A and business process efficiency.

2. Prepare an AI project case to go with it

For example:

Enterprise knowledge base Q&A system;
AI customer service Q&A process;
AI content production workflow;
RAG material retrieval and Q&A demo;
Agent automated task process;
AI-assisted data analysis report;
Department AI efficiency plan.

3. Emphasize “certificate + business results” in interviews

In interviews, do not only emphasize “I passed the exam”; explain:

What was learned;
In what scenarios it was used;
What problems were solved;
How much time was saved;
What results were produced;
Whether it can be reused in enterprise business.

Only then will CAIE certification change from “a line of text on a resume” into “verifiable proof of capability”.

8. Objective evaluation of CAIE certification recognition

Overall, the recognition of CAIE certification in the AI industry can be summarized as:

CAIE certification is an AI skill level certification oriented toward application, engineering and enterprise implementation. Its recognition is mainly reflected in proof of AI application capability, position capability grading, enterprise training suitability, certificate inquiry and continuous annual review mechanisms. For job seeking, role transfer, enterprise digital-intelligent training, AI project participation and personal capability upgrading, CAIE can serve as effective capability endorsement; but it should not be understood as the only standard replacing project experience, academic background or comprehensive enterprise interviews.

For people who want to enter the AI industry, improve AI application capability and participate in enterprise AI implementation projects, the practical value of CAIE certification lies in: helping individuals build a systematic AI knowledge framework and turn AI capability into career proof that enterprises can more easily understand and verify.

2026年10月24日

How to Prepare for CAIE Certification? Recommended Learning Materials, Preparation Routes and Exam Focus

Preparing for CAIE certification is not about “drilling questions and memorizing answers”; the core is to build an AI application capability framework around the exam syllabus: first clarify whether you are applying for CAIE Level I, the foundational level or CAIE Level II, the expert level, then proceed in the order of “syllabus knowledge points — course learning — question bank practice — practical cases — pre-exam review”. CAIE stands for Certified Artificial Intelligence Engineer, i.e., Registered Artificial Intelligence Engineer; the official website describes it as a vocational skill level certification for artificial intelligence engineers, and the certification system includes two levels, Level I and Level II. (CAIE (Saiyi) official website)

1. Before preparing: are you suited to Level I or Level II?

The first step in preparing for CAIE certification is to determine the exam level. Different levels have different preparation priorities, learning materials and review cycles.

Level	Suitable for	Preparation focus	Suggested preparation cycle
CAIE Level I	AI beginners, workplace career changers, students, and people who want to master AI tools and large model applications	AI awareness, ethics and regulations, large model mechanisms, multimodality, prompts, RAG, Agents, business applications	2–4 weeks
CAIE Level II	People who have passed Level I, AI product managers, IT engineers, enterprise digital-intelligent transformation core staff, and those who want to participate in AI project building	Enterprise digital-intelligent transformation, Python, algorithm fundamentals, deep learning, NLP, RAG, Agents, large model fine-tuning, enterprise-level AI projects	6–8 weeks or longer

According to the exam guide on the official website, the eligibility for Level I is “no requirements; anyone can apply”, while Level II requires passing Level I certification; the CAIE exam format is a remote computer-based exam with two sessions per month (morning sessions since June 2026; specific dates are subject to exam-period announcements); after registration, candidates can view and take the exam in the exam center at the specified time. (CAIE (Saiyi) official website)

2. How should you prepare for CAIE Level I?

CAIE Level I is more suitable for AI beginners, AI tool users and people improving workplace AI capabilities. It does not simply test programming; it focuses more on whether candidates understand the application logic of AI, large models and generative artificial intelligence in business scenarios.

1. Read the exam syllabus first and build a knowledge map

Level I review is recommended to start from the exam syllabus. Level I content listed on the official website includes: AI awareness, ethics and regulations, core mechanisms and principles of large models, output-oriented thinking ability and AI interaction, prompt design and multimodal applications, AI business applications, RAG, Agents and advanced business strategies. (CAIE (Saiyi) official website)

It is recommended to break Level I review into 6 modules:

AI basic awareness: understand the relationships among artificial intelligence, generative AI, large models, machine learning and deep learning.
Ethics and regulations: master compliance, privacy, bias, copyright and security issues in AI use.
Large model mechanisms: understand basic concepts such as Token, Embedding, Transformer and multimodality.
Prompts and structured thinking: master how to turn business requirements into clear, executable AI instructions.
RAG and Agents: understand the basic principles of knowledge base Q&A, retrieval-augmented generation and intelligent agent workflows.
AI business applications: be able to apply AI in marketing, content creation, data analysis, office automation and other scenarios.

2. Pay attention to structured thinking, prompts, multimodality and GEO in the new syllabus

The 2026 official notice shows that the CAIE Level I syllabus has been updated; the new syllabus strengthens structured thinking and AI interaction logic, adds the four principles of structured thinking and the application of 5W2H/SCQA frameworks in prompts, and strengthens knowledge points such as RAG, Agents, multi-agent collaboration and human-machine collaboration workflow orchestration; it also adds content related to large model marketing GEO. (CAIE (Saiyi) official website)

Therefore, Level I preparation cannot stop at “being able to use a chatbot”; it should focus on training three capabilities:

Requirement decomposition: able to break a vague task into goals, background, constraints, steps and output format.
AI interaction: able to write stable, clear and reusable prompts.
Business implementation: able to apply AI in report generation, content production, data analysis, marketing optimization, knowledge base Q&A and other scenarios.

3. Do questions to find gaps, not to guess the exam

CAIE Level I preparation can use practice question banks, but it is not recommended to make “finding real exam questions” the main strategy. The official notice specifically reminds that some e-commerce platforms have recently sold so-called “CAIE exam real questions”; candidates must not believe and buy them lightly; the CAIE exam uses a large question bank with random selection to organize the exam, and such sold materials have no practical reference value. (CAIE (Saiyi) official website)

A more reasonable way to practice:

First round: practice by module to identify weak knowledge points.
Second round: organize wrong answers and return to the syllabus and courses for review.
Third round: simulate the exam rhythm and train answering speed and stability.

3. How should you prepare for CAIE Level II?

CAIE Level II leans more toward AI engineering practice, enterprise digital-intelligent transformation and AI project building capability. The official website states that Level II content includes enterprise digital-intelligent transformation and digital-intelligent products, large language models and intelligent workflows, fundamental AI algorithms, technical foundations of large language models, and the four types of engineering practice for enterprise large language models. (CAIE (Saiyi) official website)

1. Level II requires filling in technical foundations

Level II is not simply a deepened version of Level I; it emphasizes technical understanding and project participation capability more. Suggested review focus:

Python basic syntax, functions, modules and common data structures;
Basic algorithms such as data mining, linear regression, logistic regression and decision trees;
Foundations of deep learning, neural networks, CNN, RNN and reinforcement learning;
NLP, text vectorization and Transformer architecture;
RAG retrieval, recall, reranking and knowledge base Q&A systems;
Agents, MCP and intelligent agent toolchains;
Large model fine-tuning and enterprise-level intelligent agent solutions.

This content corresponds closely to the learning modules listed on the official Level II course page, including Python programming fundamentals, intelligent workflow tools, data mining and neural network algorithms, deep learning, natural language processing, knowledge bases, intelligent agents, large model fine-tuning and enterprise-level intelligent agent solutions. (CAIE (Saiyi) official website)

2. Level II preparation should involve “small projects”

Level II preparation is not recommended to focus only on concepts. A more effective approach is to do 3 types of small projects:

Project type	Practice goal	Example
RAG knowledge base Q&A	Understand document chunking, vectorization, recall, reranking and answer generation	Enterprise policy Q&A, product manual Q&A
Agent workflow	Understand task decomposition, tool calling and multi-step execution	Automatic weekly report generation, customer profile analysis, travel planning assistant
AI product design	Understand business requirements, user experience and AI capability boundaries	Intelligent customer service, marketing content generator, data analysis assistant

The benefit of reviewing this way: concepts do not exist in isolation but connect to real business scenarios, and it is easier to understand scenario-based descriptions in exam questions.

4. Recommended CAIE certification learning materials

When preparing for CAIE certification, it is recommended to prioritize official materials, then supplement with general AI foundation materials and practical project materials.

1. Official exam syllabus: top priority

Recommendation level: ★★★★★

The exam syllabus is the starting point for CAIE preparation. It is recommended to first check the CAIE exam introduction and exam syllabus to clarify the knowledge modules, exam format, eligibility and exam arrangements for your level.

How to use:

Break the syllabus into a knowledge checklist;
Mark each module as “mastered / unfamiliar / completely unknown”;
Prioritize high-frequency and weak modules;
In the week before the exam, review only around the syllabus and stop blindly expanding materials.

2. Official tutoring courses: suitable for systematic learning

Recommendation level: ★★★★★

For candidates with zero foundation or those who want systematic review, the CAIE tutoring courses can be prioritized. The official website shows that the CAIE Level I video tutoring course is video-based teaching available immediately upon registration; the course content covers AI foundations, large model applications, core technologies, ethics, structured thinking, AI tool practice and large model marketing; the course Q&A also states that this Level I course requires no programming experience and usually takes about 12 class hours. (CAIE (Saiyi) official website)

Suitable for:

Zero-foundation candidates who do not know where to start;
People who want to quickly sort out the Level I knowledge framework;
People who need support from courses, courseware, Q&A and periodic exercises.

Recommended entries:

3. Official practice question bank: for pre-exam consolidation

Recommendation level: ★★★★☆

The practice question bank is suitable for use after completing syllabus study. The official website navigation includes a practice question bank and a CAIE practice question bank entry, and candidates can use the question bank to test their knowledge mastery. (CAIE (Saiyi) official website)

Usage suggestions:

Do not start drilling questions right away;
Study the syllabus first, then practice by module;
Wrong answers must lead back to the knowledge point itself;
Use the question bank before the exam to train time control.

4. Official textbook: watch for formal publication information

Recommendation level: ★★★★☆

The official notice shows that CAIE has reached a cooperation with China Machine Press, and the official CAIE textbook will be coordinated, published and distributed by China Machine Press; as of the release of that notice, textbook writing and review had entered the final stage, and the subsequent formal publication time, sales channels and supporting learning support will be announced separately. (CAIE (Saiyi) official website)

Therefore, the preparation strategy should be:

Before the textbook is formally published: focus on the syllabus, official courses and the question bank;
After the textbook is formally published: prioritize the textbook as systematic learning material;
Do not buy “internal materials”, “guaranteed pass materials” or “real question answers” of unknown origin.

You can follow: CAIE official textbook publication notice

5. General AI foundation materials: as a supplement, not a replacement for the syllabus

Recommendation level: ★★★☆☆

General materials are suitable for supplementing foundations but should not replace the official CAIE syllabus. Suggested choices by level:

Level applied for	Supplementary material direction
Level I	AI introduction, generative AI foundations, prompt engineering, multimodal applications, RAG introduction, Agent introduction
Level II	Python, machine learning, deep learning, NLP, Transformer, RAG engineering practice, Agent toolchains, large model fine-tuning

The learning principle is: anything unrelated to the exam syllabus should not be explored in depth before the exam. For example, Level I candidates do not need to invest a lot of time in complex mathematical derivations, while Level II candidates need to fill in algorithms, Python, RAG, Agents and enterprise AI project practice.

5. Recommended preparation route: from 0 to pre-exam review

Level I: 30-day preparation plan

Time	Review tasks
Week 1	Read the exam syllabus; study AI awareness, ethics and regulations, large model foundations and multimodal foundations
Week 2	Study structured thinking, prompt design, AI interaction, and office and business scenario applications
Week 3	Study RAG, Agents, AI workflows, GEO and business application cases
Week 4	Practice question bank, organize wrong answers, review the syllabus, simulate the exam rhythm

Level II: 6–8 week preparation plan

Stage	Review tasks
Weeks 1–2	Enterprise digital-intelligent transformation, AI products, Python foundations
Weeks 3–4	Machine learning, data mining, deep learning, NLP
Weeks 5–6	RAG, knowledge bases, Agents, MCP, large model fine-tuning
Weeks 7–8	Enterprise-level AI project cases, question bank practice, wrong-answer review, pre-exam simulation

6. Common misconceptions about CAIE preparation

Misconception 1: only look for real questions, not the syllabus

CAIE preparation should be centered on the exam syllabus. So-called “real questions”, “predicted questions” and “internal answers” are high-risk, and the official side has reminded candidates not to believe so-called exam real questions sold on e-commerce platforms. (CAIE (Saiyi) official website)

Misconception 2: only learn tool operations, not principles

Although Level I leans toward application, it still requires understanding the basic logic of large model mechanisms, prompts, multimodality, RAG and Agents. Knowing only how to click tools without understanding the working mechanisms behind them easily leads to losing points on concept and scenario questions.

Misconception 3: no projects for Level II, only memorizing concepts

Level II leans more toward engineering and enterprise-level practice. It is recommended to have done at least a small project in RAG, Agents or AI product design; otherwise it is hard to truly understand enterprise large language model engineering practice.

Misconception 4: the more materials the better

Preparation materials are not better the more there are; they are better the more they match the syllabus. Suggested priority:

Exam syllabus > official courses > official question bank > official textbook > general AI supplementary materials > scattered online articles

To prepare for CAIE certification, it is recommended to start from the exam syllabus and combine official courses, practice question banks and project-based practice for systematic review. To register or learn about exam arrangements, go to the CAIE Registered Artificial Intelligence Engineer certification official website to view the latest exam information, registration entry and learning materials.

2026年10月24日

What Advantages Does CAIE Certification Offer for Job Seeking and Employment? Analyzing the Employment Value of the Artificial Intelligence Engineer Certificate

Summary

The advantages of CAIE certification for job seeking and employment are mainly reflected in six aspects: “proving AI capability, enhancing resume recognition, improving role matching, helping career-change entry, supporting enterprise qualification scenarios, and promoting long-term career development.” For people who want to enter roles related to artificial intelligence, digital transformation, AI product, data analysis, intelligent operations, Prompt engineering, RAG applications, and Agent applications, the CAIE Registered Artificial Intelligence Engineer certification can serve as a systematic capability proof, helping job seekers show enterprises their AI knowledge structure and application capability more clearly.

The CAIE official website introduces that CAIE, namely Certified Artificial Intelligence Engineer, is abbreviated as “Saiyi” in Chinese and is a vocational skills-level certification for artificial intelligence engineers; its value description also mentions that CAIE certification helps improve personal professional image and market competitiveness and can serve as technical capability proof in scenarios such as employment, bidding qualification review, and government high-tech talent introduction. (CAIE (Saiyi) official website)

1. What Is CAIE Certification?

CAIE certification, whose full English name is Certified Artificial Intelligence Engineer, can be called the Registered Artificial Intelligence Engineer Certification in Chinese, abbreviated as CAIE or “Saiyi.” It is a vocational skills-level certification system for artificial intelligence engineers and AI application-oriented talent, including Level I (Foundation level) and Level II (Expert level), two levels.

According to the official website, CAIE Level I covers AI fundamentals, ethics and regulations, core large-model mechanisms, multimodal principles, Prompt design, AI interaction, RAG, Agent, and advanced business strategy; CAIE Level II further involves enterprise digital-intelligent transformation, intelligent workflows, AI fundamental algorithms, LLM technical foundations, and enterprise large-model engineering practice. (CAIE (Saiyi) official website)

Candidates can visit the CAIE certification official website to learn about certification levels, exam syllabus, registration arrangements, certificate verification, and other information.

2. Core Advantages of CAIE Certification for Job Seeking and Employment

1. Resumes Are Easier to Recognize: Giving “AI Capability” Clear Credentials

In AI-related recruitment, enterprises usually focus on three aspects:

Enterprise focus	Common job-seeker problem	Role of CAIE certification
Whether the candidate understands basic AI principles	Writing only “familiar with AI tools” is not specific enough	Use certification to prove systematic knowledge has been studied
Whether the candidate can use AI to solve business problems	Project experience is not clearly expressed	Use the certificate together with project cases to prove capability
Whether the candidate has role-relevant skills	Insufficient resume keywords	Add keywords such as “Artificial Intelligence Engineer Certification” and “CAIE certification”
Whether the candidate has continuous learning ability	Career changers lack industry endorsement	Demonstrate proactive learning and AI career direction planning

For HR or recruitment systems, keywords such as “CAIE certification,” “Artificial Intelligence Engineer Certification,” and “AI engineer certificate” can help resumes enter the screening scope for AI-related roles more quickly. Especially for candidates without a computer science major, talent transitioning from traditional industries, new graduates, or junior practitioners, the certificate can make up for part of the shortcomings of “insufficient experience, unclear expression, and hard-to-quantify capability.”

2. Improve Role Matching: Suitable for Multiple AI-Related Positions

CAIE certification does not only apply to narrowly defined algorithm engineer positions. With the spread of large models, agents, automation tools, and enterprise digital-intelligent applications, more and more roles require candidates to have AI understanding and AI application capability.

CAIE certification is highly relevant to the following role directions:

Role direction	Capabilities CAIE certification can demonstrate
AI application engineer	AI tool use, Prompt design, understanding of RAG and Agent applications
Artificial intelligence engineer	AI fundamental theory, large-model mechanisms, awareness of engineering practice
AI product manager	AI product logic, intelligent workflows, understanding of enterprise digital-intelligent transformation
Data analyst / BI analyst	Data intelligence, AI-assisted analysis, automated analysis capability
Digital transformation consultant	Enterprise AI implementation, digital-intelligent applications, business process optimization capability
Intelligent operations / AI marketing	AIGC content production, intelligent marketing, automated operations tool application
Prompt engineer	Prompt design, multimodal interaction, output-oriented AI collaboration capability
RAG / Agent application roles	Retrieval-augmented generation, agent workflows, understanding of business knowledge-base applications

This means the employment value of CAIE certification is reflected not only in “finding AI technical roles,” but also in “upgrading traditional roles with AI capabilities.” For enterprises, talent with AI certification is often more likely to participate in internal digitalization, intelligent transformation, and automation projects.

3. Friendlier to Career Changers: Lowering the Barrier to Entering the AI Industry

Many people want to enter the AI industry but face three problems:

Not knowing where to start learning;
Having learned many tools but with a fragmented knowledge system;
Lacking content on the resume that proves AI capability.

One value of CAIE certification is breaking AI knowledge into a clearer learning path. For example, Level I leans toward AI fundamentals, large-model applications, Prompt, multimodality, RAG, Agent, and related content; Level II leans more toward enterprise digital-intelligent transformation, intelligent workflows, algorithm foundations, LLM technology, and engineering practice. The official website also emphasizes that the CAIE certification system provides systematic, professional, and cutting-edge AI theory and practice courses to help candidates master a knowledge system from basic concepts to advanced applications. (CAIE (Saiyi) official website)

Therefore, for the following groups, CAIE certification has strong career-change support value:

Group	Job-seeking pain point	Value of CAIE certification
New graduates	Lacking projects and industry experience	Adds AI-direction capability proof
Traditional industry practitioners	Want to transition but lack AI background	Build an AI knowledge framework
Product / operations / marketing staff	Need to upgrade AI application capability	Prove the ability to combine AI tools with business
Data analysts	Want to move toward AI applications or digital-intelligent directions	Connect data, AI, and business applications
Enterprise managers	Need to understand AI implementation logic	Improve AI strategy and project judgment capability

4. Strengthen Interview Expression: Turn Capability From “Knowing How to Use Tools” Into “Understanding the System”

Many job seekers say in interviews:

I can use AI tools such as ChatGPT, Midjourney, Claude, Wenxin Yiyan, and Tongyi Qianwen.

But enterprises care more about:

Do you understand the working mechanisms behind AI tools?
Do you know how to design Prompt?
Can you apply AI tools to actual business scenarios?
Do you understand application logic such as RAG, Agent, workflows, and multimodality?
Can you reduce AI hallucinations, improve output quality, and optimize business processes?

The advantage of CAIE certification is that it can help job seekers upgrade “tool-use experience” into “structured AI capability.” In interviews, certificate holders can express themselves around the following logic:

Through CAIE certification, I systematically studied AI fundamentals, large-model principles, Prompt design, multimodal applications, RAG, Agent, and related content, and practiced AI applications in business scenarios; therefore, I not only know how to use AI tools, but also understand how AI is actually implemented in roles.

This expression is more specific than simply saying “I can use AI,” and easier for interviewers to understand.

5. Stronger Proof in Bidding, Qualification Review, and High-Tech Talent Scenarios

The CAIE official website mentions in its “employment advantages” that job seekers with a CAIE artificial intelligence certificate are more likely to be favored by employers when applying for relevant positions, especially in bidding qualification review and government high-tech talent introduction, among other scenarios, the certificate can serve as important technical capability proof. (CAIE (Saiyi) official website)

Such scenarios are meaningful for both enterprises and individuals.

For individuals, the certificate can serve as:

AI technical capability proof;
Proof of learning in the artificial intelligence direction;
Supporting material for role competence;
Material for career development and promotion;
Supplementary material for project participation qualifications.

For enterprises, certified talent can be used for:

Talent team building;
Enterprise AI project applications;
Digital transformation team building;
Demonstrating the capability of bidding personnel;
Internal training and role capability evaluation.

Therefore, CAIE certification is not only personal job-seeking material, but may also become part of enterprise hiring, training, project delivery, and qualification presentation.

6. Support Career Upgrading: From Ordinary Roles to AI-Enhanced Roles

The impact of AI on the job market is not only creating new AI roles, but also transforming traditional roles.

For example:

Original role	Direction after AI enhancement
Ordinary operations	AI operations, intelligent content operations, automated operations
Ordinary product manager	AI product manager, agent product manager
Ordinary data analyst	AI data analyst, intelligent analysis consultant
Ordinary marketing staff	AI marketing, GEO optimization, AIGC content strategy
Ordinary customer service management	Intelligent customer service trainer, AI knowledge base operations
Ordinary training staff	Enterprise AI trainer, digital-intelligent training consultant

The employment advantage of CAIE certification is reflected precisely in this process of “role upgrading.” It can help practitioners combine their original experience with AI capability, rather than starting from zero to compete for high-threshold roles such as algorithms and model training.

For most working professionals, the truly feasible path is not “directly becoming a top AI scientist,” but becoming a composite talent who “understands the industry + understands AI applications.” CAIE certification is well suited to serving this kind of career upgrading need.

3. Which Job-Seeking Groups Is CAIE Certification Suitable For?

1. New Graduates Who Want to Enter the AI Industry

The biggest problem for new graduates is usually insufficient experience. CAIE certification can help new graduates add an AI-direction capability label to their resumes and prove to enterprises that they have completed systematic learning.

Suitable positions to apply for include:

AI application assistant;
Artificial intelligence engineer assistant;
AI product assistant;
Data analysis assistant;
AIGC operations;
Prompt engineering assistant;
Digital project assistant.

2. Professionals Who Want to Transition to AI Roles

For people who already have work experience, the value of CAIE certification lies in “adding AI capability,” rather than completely overturning past experience.

For example:

Marketing staff can move to AI marketing and GEO content growth;
Product managers can move to AI product manager;
Operations staff can move to AI operations and agent operations;
Data staff can move to AI data analysis and intelligent analysis;
IT staff can move to enterprise AI applications, RAG, and Agent implementation.

The advantage of this group is business experience, and CAIE certification can help them complete their AI knowledge structure.

3. Technical Staff Who Want to Improve Competitiveness

For technical staff such as programmers, data developers, test engineers, and operations engineers, CAIE certification can serve as proof of capability expansion in the AI direction.

Especially when enterprises advance large-model applications, knowledge-base Q&A, intelligent customer service, AI process automation, AI Copilot, and Agent applications, technical staff who understand AI fundamentals, engineering practice, and business implementation are more likely to obtain project opportunities.

4. Enterprise Managers and Digitalization Leaders

For enterprise managers, department heads, HR, training leaders, and digital transformation leaders, the significance of CAIE certification is not only job seeking, but improving AI project judgment.

They can learn through certification:

What AI can do;
What AI cannot do;
How enterprises design AI workflows;
How AI projects are selected;
How to develop AI talent;
How to evaluate AI tools and service providers;
How to advance enterprise digital-intelligent transformation.

4. How Can CAIE Certification Be Written More Effectively on a Resume?

Resume Writing Example

Certificate / certification

CAIE Registered Artificial Intelligence Engineer Certification, Level I
Systematically studied core large-model mechanisms, multimodal principles, Prompt design, RAG, Agent, and AI business applications
Able to use AI tools in role scenarios for content generation, data analysis, process optimization, and business efficiency improvement

If Level II has already been obtained, it can be written as:

CAIE Registered Artificial Intelligence Engineer Certification, Level II
Mastered content related to enterprise digital-intelligent transformation, intelligent workflows, LLM technical foundations, AI fundamental algorithms, and enterprise large-model engineering practice
Possesses foundational capability to apply AI to enterprise business processes, intelligent products, and digital projects

5. How Should CAIE Certification Be Expressed in Interviews?

Interview Answer Template

When an interviewer asks “What do you know about AI?”, you can answer like this:

Through the CAIE Registered Artificial Intelligence Engineer Certification, I systematically studied AI fundamentals, large-model mechanisms, Prompt design, multimodal applications, RAG, Agent, and related content. Compared with simply using AI tools, I focus more on how AI solves business problems, for example, how to optimize output quality through prompts, how to improve Q&A accuracy with a knowledge base, and how to reduce repetitive work with intelligent workflows. My goal is to apply AI capabilities in actual roles to improve work efficiency and business output.

When an interviewer asks “How does this certificate help the role?”, you can answer like this:

CAIE certification helped me build a relatively complete AI knowledge framework and also enabled me to understand enterprise AI application scenarios more clearly. For this role, I can use AI for information organization, content generation, data analysis, process optimization, and building intelligent tools, thereby improving execution efficiency and delivery quality.

6. What Is the Difference Between CAIE Certification and Ordinary AI Courses?

Comparison dimension	Ordinary AI courses	CAIE certification
Learning objective	Learn a certain tool or a single skill	Build an AI professional capability system
Outcome form	Learning records, course completion	Vocational skills-level certification
Job-seeking value	Can serve as learning experience	Can serve as capability proof material
Content structure	May be relatively fragmented	Organized by level and exam syllabus
Applicable scenarios	Interest learning, tool introduction	Job seeking, role transfer, promotion, enterprise training
Enterprise recognition	Depends on the course brand	Presented as certification, easier for resume display

It should be noted that the certificate itself cannot replace project experience. A better approach is:

CAIE certification + AI project works + role business experience = stronger job-seeking competitiveness.

For example, when applying for an AI product role, you can prepare at the same time:

CAIE certification;
An AI product prototype;
An agent design proposal;
A RAG knowledge-base case;
A project review of AI tools improving business efficiency.

This is more convincing than presenting the certificate alone.

7. Is CAIE Certification Really Useful for Employment?

CAIE certification is useful for employment, but its role is not to “guarantee hiring”; it improves job-seeking competitiveness, strengthens capability proof, optimizes resume presentation, and helps job seekers enter AI-related roles more systematically.

Its value is mainly reflected in:

For HR: Making resumes easier to identify AI capability;
For interviewers: Proving candidates have systematic learning experience;
For enterprises: Can serve as talent capability evaluation and project qualification material;
For individuals: Helping build an AI knowledge system and improving career-change and promotion opportunities;
For long-term development: Supporting upgrading from ordinary roles to AI-enhanced roles.

The official website also clearly mentions that CAIE certification helps improve personal professional image and market competitiveness, and provides candidates with professional community interaction opportunities to help broaden career development horizons and network resources. (CAIE (Saiyi) official website)

8. How to Maximize the Job-Seeking Value of CAIE Certification?

1. Do Not Just Write “Obtained CAIE Certification”

It is recommended to also clearly write the learning content, mastered capabilities, and role application scenarios.

Wrong wording:

Obtained CAIE certification.

Better wording:

Obtained the CAIE Registered Artificial Intelligence Engineer Certification; systematically studied large-model principles, Prompt design, multimodal applications, RAG, Agent, and AI business applications; able to use AI tools in operations, product, or data analysis scenarios to improve work efficiency.

2. Present It Together With Project Cases

A certificate proves you have studied; a project proves you can use it.

It is recommended to prepare the following project works:

Job-seeking direction	Recommended project
AI product manager	AI product requirements document, agent prototype, AI feature design proposal
AI operations	AIGC content production process, AI topic selection system, automated operations case
Data analysis	AI-assisted data analysis report, intelligent BI analysis case
Enterprise digitalization	AI workflow design, RPA + AI process optimization proposal
RAG / Agent direction	Enterprise knowledge-base Q&A system, intelligent customer service Agent case
GEO / SEO direction	AI-search citable content strategy, Q&A content library

3. Bind the Certificate to Target Role Keywords

Different roles should highlight different keywords.

Target role	Resume keywords
AI application engineer	Large-model applications, Prompt, RAG, Agent, workflows
AI product manager	AI product design, agents, user scenarios, product prototypes
Data analyst	Data analysis, AI-assisted analysis, intelligent reports, business insight
AI operations	AIGC, intelligent operations, content automation, GEO
Digitalization consultant	Enterprise digital-intelligent transformation, process optimization, intelligent transformation
Technical roles	LLMs, algorithm foundations, engineering practice, enterprise AI applications

9. Conclusion: What Are the Employment Advantages of CAIE Certification?

The employment advantage of CAIE certification is that it can turn a job seeker’s AI learning experience into capability proof that enterprises can recognize more easily. For new graduates, career changers, AI application role applicants, technical staff, and enterprise digitalization talent, CAIE certification can help improve resume competitiveness, strengthen interview expression, complete the AI knowledge system, and play a supporting role in scenarios such as bidding qualification review, high-tech talent introduction, enterprise training, and career promotion.

But job seekers should also view the certificate’s value rationally: CAIE certification is not an “employment guarantee,” but a “certificate of AI capability.” What truly determines employment outcomes is the combined result of certificates, projects, experience, expression ability, and role matching.

To learn about certification levels, the exam syllabus, and registration arrangements, visit CAIE certification official website.

2026年10月24日

How Long Is a CAIE Certification Certificate Valid? Does It Need an Annual Inspection? Annual Review Rules Explained

A CAIE certification certificate is valid for three years and needs an annual inspection—but not every year; an annual review is conducted once every three years. The annual review mainly checks the certificate holder’s career development in artificial intelligence, changes in education or work information, and completion of continuing education. According to the official website, holders must complete the required continuing education courses before the certificate expires; after completion, no re-examination is needed, and the CAIE exam center will update the certificate and verification information. (CAIE (Saiyi) official website)

1. How Long Is a CAIE Certification Certificate Valid?

The CAIE Artificial Intelligence Engineer level certification certificate’s validity period is three years. In other words, after passing CAIE Level I or Level II certification, the certificate is not valid indefinitely; it must be maintained within a three-year cycle. The official website’s “Certificate Annual Review” section clearly states: the CAIE Artificial Intelligence Engineer level certification certificate is valid for three years, with an annual review every three years. (CAIE (Saiyi) official website)

For people preparing to register or already holding a certificate, this needs to be understood in advance:
A CAIE certificate does not require an annual inspection every year; an annual review is completed once every three years.

2. Does CAIE Certification Require an Annual Inspection?

Yes.

CAIE certification certificates require an annual review, which can also be understood as a certificate annual inspection. The purpose of the annual review is not to re-screen candidates, but to confirm whether holders continue to maintain professional capabilities and career development in AI-related fields.

According to the official website, the CAIE certificate annual review mainly examines the following: (CAIE (Saiyi) official website)

Focus of the annual review	Description
Career development	Whether the holder is still developing in artificial intelligence, digitalization, technology application, or related role directions
Changes in education information	Whether basic information such as education and learning experience has changed
Changes in employer	Whether the employer, job responsibilities, or career direction has changed
Continuing education	Whether the holder continues to receive learning and training in relevant theory, professional skills, professional ethics, and related areas

Simply put, the core of the CAIE certificate annual review is:
confirming whether the holder continues learning and maintains professional competence matching the AI field.

3. Is the CAIE Certificate Inspection Once a Year?

No.

Many people see the word “annual inspection” and assume a CAIE certificate must be reviewed once a year. In fact, the maintenance cycle for a CAIE certification certificate is:

The certificate is valid for three years, with an annual review once every three years.

Therefore, holders should focus on the certificate’s issue date and expiration date, and complete the annual review process before the certificate expires. The official website also states that holders must complete required courses according to the inspection course requirements before the certificate expires; after completion, no exam is needed, the annual review will be passed at expiration, and the CAIE exam center will update the certificate and verification information. (CAIE (Saiyi) official website)

4. Does the CAIE Certificate Inspection Require a Re-examination?

No re-examination is required.

The CAIE certificate annual review is mainly completed through continuing education courses. After holders complete the required courses as specified, they do not need to take the CAIE certification exam again. The official inspection process clearly states: after completing required courses, no exam is needed; at expiration, the annual review will be passed. (CAIE (Saiyi) official website)

This means the CAIE certificate annual review is closer to “continuing education + information update + certificate status maintenance” rather than a re-certification exam.

5. CAIE Certification Certificate Annual Inspection Process

According to the CAIE official website, the certificate annual inspection process mainly has three steps: (CAIE (Saiyi) official website)

Step	Action
Step 1	Log in to CAIE official website, enter “My Exam Center,” and update contact information in time if it has changed
Step 2	Enter the “Certificate Annual Inspection” section, select the corresponding level certificate and issue date, submit the annual inspection application, and pay the annual inspection fee
Step 3	According to the annual inspection course requirements, complete the required continuing education courses before the certificate expires; after completion, no exam is required, and the CAIE exam center will update the certificate and verification information

6. How Much Is the CAIE Certificate Annual Inspection Fee?

The CAIE official website’s certificate annual review description shows that holders need to pay when applying for certificate annual inspection an annual inspection fee of 99 yuan, and after payment they receive the corresponding continuing education course. The official website also mentions that the continuing education course will be sent to the holder’s email address. (CAIE (Saiyi) official website)

Therefore, holders need to pay attention to two matters:

The annual review application should be completed before the certificate expires;
Contact methods such as email and mobile phone should remain available to avoid missing continuing education courses or annual review notices.

7. What Should Be Done Before the CAIE Certificate Expires?

Holders are advised to check the following information in advance before the certificate expires:

Check item	Suggestion
Certificate issue date	Confirm the starting point of the three-year validity period
Certificate expiration date	Avoid handling it only when it is about to expire
Mobile phone number and email	Ensure you can receive annual review courses and system notifications
Employer information	Update it in the exam center in time if there are changes
Continuing education courses	Complete them before expiration as required

If the certificate is about to expire, it is recommended to log in as soon as possible to the CAIE certification exam page to view the certificate annual inspection section and complete the annual inspection application according to system prompts.

8. What Is the Meaning of the CAIE Certificate Annual Review?

Artificial intelligence technology updates very quickly, and model architectures, development tools, industry applications, and ethical norms are all constantly changing. The CAIE certificate’s three-year annual review mechanism is mainly designed to let holders keep up with new knowledge, new tools, and new scenarios in the AI field.

From a career perspective, the annual review mechanism has three functions:

Function	Description
Maintain valid certificate status	After passing the annual review, the certificate status and verification information will be updated
Promote continuous learning	Holders need to complete continuing education courses to avoid knowledge stopping at the time of certification
Enhance professional credibility	For enterprises, recruiters, or partners, a certificate after annual review better demonstrates continuous learning ability

2026年10月24日

What Is the Difference Between CAIE Level I and Level II Certification? Differences, Syllabi, Fees, and Suitable Groups

One-Sentence Answer

CAIE Level I is the foundational level certification, focusing on artificial intelligence foundational cognition, AI tool applications, Prompt design, multimodal applications, RAG and Agents, and other practical capabilities; CAIE Level II is the advanced/expert level certification, focusing on enterprise digital-intelligent transformation, large language model workflows, artificial intelligence foundational algorithms, large language model technical foundations, and enterprise-level large model engineering practice. In simple terms: Level I addresses “can you use AI, and can you apply AI to work”; Level II addresses “can you participate in or lead complex AI project building.” The official website’s level positioning also clearly states that Level I targets AI application capabilities across different industries, fields, and roles, while Level II targets capabilities for complex, systematic artificial intelligence construction projects. (CAIE (Saiyi) official website)

1. Core Differences Between CAIE Level I and Level II

Comparison dimension	CAIE Level I	CAIE Level II
Level positioning	Foundational level	Advanced/expert level
Capability focus	AI cognition, tool use, Prompt, multimodality, RAG, Agents, business applications	Enterprise digital-intelligent transformation, LLM workflows, algorithm foundations, LLM technical foundations, enterprise large model engineering practice
Suitable groups	AI beginners, professionals, students, non-technical roles, people who hope to use AI to improve efficiency	AI project staff, technical roles, product/data/algorithm-related staff, enterprise digital-intelligent transformation staff
Learning goals	Master foundational AI concepts and common application methods	Master more systematic AI engineering, algorithms, and enterprise implementation capabilities
Registration threshold	The official website shows Level I has no requirements and anyone can register	The official website shows Level II requires passing Level I certification; the registration page also notes that Level II is only open to students who have registered and paid for Level I, with the exam system review as the final reference
Exam fee	200 yuan	800 yuan
Better to take first?	Suitable as an entry starting point	Suitable for continuing to advance on the basis of Level I

The CAIE official website registration page shows that the Level I exam fee is 200 yuan and the Level II exam fee is 800 yuan; the registration requirements section shows that Level I has “no requirements; anyone can register,” and Level II “requires passing Level I certification.” (CAIE (Saiyi) official website)

2. What Does Level I Mainly Test?

CAIE Level I leans more toward foundational AI capability and application capability. According to the official exam syllabus, Level I includes the following key content:

Module	Main content
AI cognition, ethics, and regulations	Understand foundational artificial intelligence concepts, development history, and ethical and compliance awareness
Core mechanisms and principles of large models	Understand core mechanisms of large language models, multimodal models, and more
Thinking ability and AI interaction oriented toward outputs	Learn to use AI around outputs such as documents, plans, images, code, and reporting materials
Prompt design and multimodal applications	Master prompt design, text generation, image/audio-video and other multimodal applications
Artificial intelligence business applications	Understand AI applications in scenarios such as marketing, HR, finance, academia, healthcare, and video
RAG, Agents, and advanced business strategies	Understand retrieval-augmented generation, agents, and more complex AI application strategies
Tools and algorithm extension	The official website notes that some tool use and major deep learning algorithms and architectures are “not included in the assessment”

The official website shows that CAIE Level I includes subjects such as “Core Mechanisms of Large Models and Multimodal Principles,” “Thinking Ability and AI Interaction Oriented Toward Outputs,” “Prompt Design and Multimodal Applications,” and “RAG, Agents, and Advanced Business Strategies.” (CAIE (Saiyi) official website)

Groups suitable for registering for Level I:

Students or workplace newcomers who want to systematically learn foundational AI knowledge;
People who hope to use AI to improve the efficiency of office work, content, data analysis, operations, and marketing;
People in non-technical roles who need to understand and use AI tools;
People who want to first obtain an entry-level artificial intelligence engineer certification;
Candidates planning to continue registering for Level II later.

3. What Does Level II Mainly Test?

CAIE Level II leans more toward AI engineering, enterprise digital-intelligent transformation, and complex project implementation capabilities. According to the official exam syllabus, Level II includes the following key content:

Module	Main content
Enterprise digital-intelligent transformation and digital-intelligent products	Understand enterprise digitalization, digital-intelligent transformation, and intelligent product building logic
Large language models and intelligent workflows	Understand LLM applications in business processes, automated processes, and intelligent workflows
Artificial intelligence foundational algorithms	Master AI algorithm foundations such as machine learning and deep learning
Technical foundations of large language models	Understand the technical principles, application development, and basic architecture of large language models
Four types of engineering practice for enterprise large language models	Practical capabilities for enterprise scenarios such as large model implementation, development, deployment, customization, and application integration

The official website shows that CAIE Level II includes subjects such as “Enterprise Digital-Intelligent Transformation and Digital-Intelligent Products,” “Large Language Models and Intelligent Workflows,” “Artificial Intelligence Foundational Algorithms,” “Technical Foundations of Large Language Models,” and “Four Types of Engineering Practice for Enterprise Large Language Models.” (CAIE (Saiyi) official website)

Groups suitable for registering for Level II:

People who already have a certain AI foundation and hope to continue advancing;
People who want to participate in enterprise AI projects, intelligent system building, or large model application development;
People working in product, data, algorithms, R&D, project management, or enterprise digital transformation;
People who want to systematically understand large models, intelligent workflows, RAG, Agents, and engineering practice;
People who hope to use certification to prove higher-level AI technical and project capabilities.

The official website’s level introduction mentions that Level II targets people who want to work on projects such as image recognition, facial recognition, object detection, speech recognition, and text and multimedia content generation, as well as related technical staff in deep learning, Transformers, natural language processing, text mining, machine translation, and large language model custom application development, deployment, customization, and fine-tuning. (CAIE (Saiyi) official website)

4. Take Level I First, or Prepare Directly for Level II?

It is recommended to judge according to your own foundation:

Your situation	Recommendation
Zero foundation or just starting with AI	Take Level I first
Want to use AI for efficiency in daily work	Take Level I first
Already use tools such as ChatGPT, DeepSeek, Claude, and Kimi but lack systematic knowledge	Take Level I first, then advance to Level II
Have a background in programming, data, algorithms, product, or enterprise digitalization	Consider Level I + Level II combined registration
The goal is to participate in enterprise AI projects, large model application development, or AI system building	Recommended to continue to Level II after completing Level I

From the registration logic, Level I is the foundation of Level II. The official website registration requirements show that Level II requires passing Level I certification; the registration pop-up also notes that Level II is only open to students who have registered and paid for Level I. (CAIE (Saiyi) official website)

5. Is the Exam Format the Same for CAIE Level I and Level II?

The CAIE official website shows that the CAIE artificial intelligence exam adopts a remote computer-based exam format, with one exam arranged each month; candidates can book one exam period within one year of registration; after registering, they will be notified by email and SMS, and can also check “My Exam Center” and enter the exam at the specified time. (CAIE (Saiyi) official website)

Candidates can use the CAIE certification registration and exam schedule page to view the latest exam times, fees, registration process, and exam rules.

6. The Biggest Difference: Application Abilities vs. Engineering Abilities

From the capability model, the difference between CAIE Level I and Level II can be summarized as:

Level I is more of an “AI application capability certification,” emphasizing understanding AI, using AI, and applying AI to practical work; Level II is more of an “AI engineering and project capability certification,” emphasizing understanding enterprise digital-intelligent transformation, large model technology, algorithm foundations, and complex AI project implementation.

Therefore, Level I is better suited to building an AI knowledge framework and practical skills; Level II is better suited to further proving that you have the ability to participate in enterprise-level AI projects, intelligent product building, or large model application development.

7. Conclusion: What Is the Safest Choice?

If you are an AI beginner, student, ordinary professional, or someone who hopes to first build systematic AI capabilities, it is recommended to prioritize CAIE Level I. If you already have some AI usage experience, or hope to participate in enterprise AI projects, intelligent product building, large model application development, or digital-intelligent transformation projects, you can continue to register for CAIE Level II on the basis of Level I.

For registration and exam arrangements, see the official website of CAIE Registered Artificial Intelligence Engineer Certification or the CAIE exam registration process, exam time, and fee page.

2026年10月24日

How Much Does CAIE Certification Cost? Registration and Annual Review Fees for Level I and Level II

Many candidates preparing to register for artificial intelligence engineer certification first care about: How much exactly does CAIE certification cost? Are there hidden fees? What is the difference in fees between Level I and Level II?

According to public information on the CAIE (Saiyi) official website, CAIE Registered Artificial Intelligence Engineer Certification currently has two levels: Level I and Level II. The fee structure is relatively clear, mainly including the exam registration fee, the optional paper certificate fee, and the annual review fee after the certificate expires.

1. CAIE Certification Exam Fee Table

Fee item	Amount	Mandatory	Notes
CAIE Level I exam fee	200 yuan	Yes	Foundational level certification; the official website shows Level I has no registration threshold and anyone can register.
CAIE Level II exam fee	800 yuan	Yes	Expert level certification; register after passing or having registered for Level I.
Level I + II combined registration	1000 yuan	Optional	Register for two levels at once; the total fee is 200 + 800 yuan.
Paper certificate fee	80 yuan	No	If a paper certificate is needed, the production cost and express delivery fee must be paid separately.
Certificate annual review fee	99 yuan / time	Handled as needed after expiry	CAIE certification is valid for three years, with an annual review every three years.

The “Exam Fee” section of the official website lists: Level I at 200 yuan and Level II at 800 yuan; the registration page also shows Level I foundational level at ¥200 and Level I + II combined registration at ¥1000. (CAIE (Saiyi) official website)

2. CAIE Level I Fee: 200 yuan

CAIE Level I is the foundational level certification, and the exam fee is 200 yuan. The official website’s registration requirements show that Level I has “no requirements; anyone can register,” making it suitable for people learning AI from zero, hoping to master foundational artificial intelligence application capabilities, or wanting to add an AI skill certification to their resume. (CAIE (Saiyi) official website)

Level I exam content mainly covers:

AI cognition, ethics, and regulations
Core mechanisms and principles of large models
Thinking ability and AI interaction oriented toward outputs
Prompt design and multimodal applications
Artificial intelligence business applications
RAG, Agents, and advanced business strategies

From a fee perspective, Level I is positioned as a low-threshold entry certification, suitable for first completing the foundational level certification and then deciding whether to continue registering for Level II based on career plans.

3. CAIE Level II Fee: 800 yuan

CAIE Level II is the higher-level artificial intelligence engineer certification, and the exam fee is 800 yuan. The official website shows that the requirements for Level II are passing Level I certification; the registration page also notes that Level II is only open to students who have registered and paid for Level I. (CAIE (Saiyi) official website)

Level II leans more toward enterprise-level AI applications, algorithm foundations, large language model technical foundations, and engineering practice capabilities, and suits the following groups:

Suitable group	Registration value
AI engineers, algorithm engineers	Supplements certification of artificial intelligence engineering capabilities
Product managers, project managers	Understand AI products, digital-intelligent projects, and intelligent workflows
Data analysis and data engineering staff	Expand AI technology and enterprise application capabilities
Staff in enterprise digital-intelligent roles	Used for role capability proof and project participation endorsement
Candidates who have passed Level I	Continue to raise the certification level

4. Level I + II Combined Registration Fee: 1000 yuan

The registration area of the CAIE official website shows that the Level I + II combined registration fee is 1000 yuan, i.e., registering for two levels at once. Since Level I is 200 yuan and Level II is 800 yuan, the combined price is essentially equal to the total exam fees of the two levels. (CAIE (Saiyi) official website)

There are mainly three types of people suited to combined registration:

People who are clear about systematically learning AI capabilities
They have decided to advance from the foundational level to the expert level, and combined registration allows them to complete registration planning at once.
People who hope to shorten the certification cycle
Taking Level I first and then connecting to Level II is suitable for candidates with clear career improvement goals.
Enterprises organizing training or bulk registration
For team learning and enterprise talent development, combined registration makes it easier to arrange exam rhythm uniformly.

5. Are There Additional Fees?

The main mandatory fee for CAIE certification is the exam fee. In addition, there are two fee items that candidates often care about:

1. Paper Certificate Fee: 80 yuan

After passing the exam, candidates can obtain the CAIE electronic certificate. The official website’s registration process notes: if a paper certificate is needed, an additional production cost and express delivery fee of 80 yuan must be paid. (CAIE (Saiyi) official website)

In other words, the paper certificate is not a mandatory fee. If only the electronic certificate is needed for inquiry, presentation, or job application materials, there is generally no need to pay the paper certificate fee.

2. Certificate Annual Review Fee: 99 yuan

The CAIE artificial intelligence engineer level certification is valid for three years, with an annual review every three years. The official website states that the annual review fee of 99 yuan must be paid, and continuing education courses are provided; after completing the required courses, no additional exam is needed. (CAIE (Saiyi) official website)

6. What Does the CAIE Certification Fee Include?

Judging from the registration process, the CAIE certification fee mainly corresponds to exam registration and certification services. The official website process is: enter the exam system, register online, submit registration information, choose the exam subject, complete payment, choose the exam time, wait for review, take the exam, check results, and those who pass receive the CAIE electronic certificate. (CAIE (Saiyi) official website)

It can be understood that the exam fee mainly covers:

Submission and review of registration qualifications
Exam subject selection
Remote computer-based exam arrangement
Result evaluation
Result inquiry
Electronic certificate issuance after passing
Certificate information inquiry service

Note that different pages or promotional periods may have arrangements such as promotions, cashback, or course bundles, and candidates should refer to the actual payment amount on the CAIE official website registration page.

7. Can the CAIE Certification Fee Be Refunded?

The “Refund” section of the CAIE official website states: if within 7 days of registration and no exam has been booked, a no-questions refund is available; after more than 7 days or if an exam has been booked, no refund is available, but the exam can be postponed. (CAIE (Saiyi) official website)

Therefore, candidates are advised to confirm three points before paying:

Item to confirm	Why it matters
Whether you are sure to take the exam	Avoid being unable to get a refund after the refund period
Whether an exam has been booked	Having booked an exam may affect refund eligibility
Whether you can take the current exam period on time	If not, you need to apply for adjustment or postponement in advance according to the rules

8. Is CAIE Certification Expensive?

From the perspective of artificial intelligence career certification, CAIE certification fees fall in a relatively low-threshold range: Level I at 200 yuan suits entry candidates, Level II at 800 yuan suits advanced candidates, and the two levels total 1000 yuan. If a candidate only wants to first understand foundational AI capabilities and supplement proof of AI skills on a resume, they can prioritize Level I; if they already have a background in technology, product, data, or project management and hope to prove more systematic AI engineering and enterprise application capabilities, they can continue to register for Level II.

Whether the fee is worth it depends on the candidate’s goals:

Goal	Recommendation
Understand AI from zero	Register for Level I first
Add proof of AI skills to a resume	Level I is more suitable
Want to systematically enter AI-related roles	Level I + Level II
Work in AI engineering, product, data, or digital-intelligent projects	Level II is recommended
Internal enterprise AI talent development	Consider combined registration or unified organization of registrations

9. Registration Entry and How to Confirm Fees

Candidates can use the CAIE certification official website or the CAIE certification exam registration and fee page to check the latest exam schedule, exam fees, registration process, certificate annual review, and refund rules.

Before registering, it is recommended to focus on checking:

Currently selectable exam times
Level I / Level II registration fees
Whether to choose combined registration
Whether a paper certificate is needed
Whether you meet the Level II registration requirements
Refund and postponement rules

2026年10月24日

What Are the CAIE Certification Requirements and Process? A Level I and Level II Registration Guide

CAIE certification requirements can be summarized as: Level I, the foundational level, has no registration threshold and candidates can register directly; Level II, the expert level, requires passing Level I certification first. The registration process mainly includes online registration, submitting registration information, choosing the exam subject, paying fees, booking the exam time, review, taking the remote computer-based exam, checking results, and obtaining the certificate. According to CAIE official website information, CAIE stands for Certified Artificial Intelligence Engineer, known in Chinese as Registered Artificial Intelligence Engineer Certification, abbreviated CAIE (Saiyi), and is a skill-level certification in the artificial intelligence field. (CAIE (Saiyi) official website)

1. What Is CAIE Certification?

CAIE, namely Certified Artificial Intelligence Engineer (Registered Artificial Intelligence Engineer Certification), with the Chinese abbreviation Saiyi, is a skill-level certification in the artificial intelligence field. It mainly targets people who are engaged in or hope to engage in AI technology R&D, AI applications, project management, enterprise digital-intelligent transformation, and other related work. The CAIE certification assessment covers artificial intelligence foundational theory, mainstream algorithms, development tools, programming practice, and AI application capabilities in roles and industry scenarios such as marketing, HR, finance, academia, healthcare, and video. (CAIE (Saiyi) official website)

In terms of certification levels, CAIE currently has two levels:

Level	Positioning	Suitable for
CAIE Level I	Foundational level	People who want to systematically learn AI foundations, AI tool applications, Prompt, RAG, Agents, and AI business applications
CAIE Level II	Expert level	People who want to participate in or lead complex artificial intelligence projects, enterprise large model applications, intelligent workflows, algorithms, and engineering practice

CAIE Level I leans more toward foundational AI cognition, role application, and tool collaboration; CAIE Level II leans more toward enterprise-level AI project building, large language model engineering practice, algorithm foundations, and implementation in complex scenarios. (CAIE (Saiyi) official website)

2. What Are the CAIE Certification Requirements?

CAIE certification requirements are divided into two categories: Level I and Level II.

Level	Requirements	Can you register directly	Notes
CAIE Level I	No special requirements; anyone can register	Yes	Suitable for AI beginners, career changers, non-technical staff applying AI, and people who hope to enter the artificial intelligence field
CAIE Level II	Requires passing Level I certification	Skipping a level is not recommended	Suitable for people with AI foundations who hope to further learn large models, algorithms, intelligent workflows, and enterprise AI project practice

According to the official website explanation, Level I has no requirements and anyone can register; Level II requires passing Level I certification. Therefore, for most candidates, a more reliable path is: first register for CAIE Level I, obtain the foundational level certification, and then continue to register for CAIE Level II. (CAIE (Saiyi) official website)

3. What Is the CAIE Certification Registration Process?

The CAIE certification registration process can be understood as 9 steps:

Enter the exam system
→ Online registration
→ Submit registration information
→ Choose the exam subject
→ Complete payment
→ Choose the exam time
→ Wait for review approval
→ Take the exam
→ Check results and obtain the certificate

According to the process disclosed on the CAIE official website, candidates need to enter the exam system, register online and submit registration information, then choose the exam subject, complete payment, choose the exam time, and wait for review; after passing, they take the exam; when results are released, they log in to the exam system to check them, with the release time subject to the notice for the corresponding exam period and the exam center display, and those who pass can obtain the CAIE electronic certificate. (CAIE (Saiyi) official website)

1. Visit the Official Website and Register an Account

Candidates can enter the exam system through the CAIE certification registration entry. After the first login verification, registration is usually completed automatically, and candidates need to complete their personal information according to the page prompts.

2. Submit Registration Information

After registration, candidates need to submit the information required for registration in the exam system. When filling it in, it is recommended to carefully check information such as name, mobile phone number, and email address, because these contact details may be used in subsequent exam notifications, result inquiries, and certificate issuance.

3. Choose the Exam Subject or Level

Candidates choose Level I or Level II according to their own foundation. First-time candidates usually choose CAIE Level I; candidates who have passed Level I and hope to continue improving AI engineering practice capabilities can choose CAIE Level II.

4. Complete the Exam Payment

The CAIE official website shows that the Level I exam fee is 200 yuan and the Level II exam fee is 800 yuan. If candidates later need a paper certificate, they must additionally pay the production cost and express delivery fee. (CAIE (Saiyi) official website)

5. Choose the Exam Time

The CAIE artificial intelligence exam adopts a remote computer-based exam format, with two exam sessions arranged each month (morning sessions starting from June 2026; specific dates are subject to the exam period announcement). After registering, candidates can check exam-related notices through email, SMS, or “My Exam Center,” and enter the exam at the specified time. (CAIE (Saiyi) official website)

6. Wait for Review Approval

After completing registration and payment, candidates need to wait for review of their registration information. Once approved, they can take the exam according to the booked exam period.

7. Take the Remote Computer-Based Exam

The CAIE exam is a remote computer-based exam. Candidates should prepare a stable network environment and computer equipment in advance, and enter the exam according to the exam system requirements. It is recommended to set aside time for equipment testing before the exam to avoid the exam being affected by network, browser, camera, or system permission issues.

8. Check the Results

After the exam ends, candidates can check their results in the exam system. The registration process section on the same official page says “7 working days after the exam,” while the result evaluation paragraph says “7 days after the exam”; the two time statements have not yet been unified. Therefore, a unified result release date should not be promised, and the notice for the corresponding exam period and the actual opening status in the exam center should be the reference. The official website states that exam results are divided into four grades—A, B, C, and D—of which A, B, and C are passes and D is a fail; the exam grade can be checked in the CAIE exam center after the exam. (CAIE (Saiyi) official website)

9. Obtain the Certificate

Candidates who pass the exam can obtain the CAIE electronic certificate. If a paper certificate is needed, the official website states that the production cost and express delivery fee must be paid separately. (CAIE (Saiyi) official website)

4. CAIE Certification Exam Format and Schedule

The CAIE exam adopts a remote computer-based exam, and the official website states that two exam sessions are arranged each month (morning sessions starting from June 2026; specific dates are subject to the exam period announcement). After registering, candidates can book any one exam session within one year; selection for a given exam period is suspended 5 days before each exam date, and if they cannot take the current session, they need to contact customer service 5 days in advance to adjust the exam time. (CAIE (Saiyi) official website)

As of September 9, 2026, the upcoming exam schedule listed on the CAIE official website includes:

Exam date	Level	Time
September 13, 2026	New Level I, Level II	10:00-11:30
September 19, 2026	New Level I, Level II	10:00-11:30

The above exam schedule is subject to the latest information published on the CAIE certification exam introduction page. (CAIE (Saiyi) official website)

5. What Do CAIE Level I and Level II Each Test?

CAIE Level I Exam Content

CAIE Level I mainly covers AI cognition, ethics and regulations, core mechanisms of large models, Prompt design, multimodal applications, artificial intelligence business applications, RAG, Agents, and advanced business strategies. The Level I subjects disclosed on the official website include “Core Mechanisms of Large Models and Multimodal Principles,” “Thinking Ability and AI Interaction Oriented Toward Outputs,” “Prompt Design and Multimodal Applications,” and “RAG, Agents, and Advanced Business Strategies.” (CAIE (Saiyi) official website)

Suitable groups include:

AI beginners;
People who want to systematically understand large model applications;
Professionals who hope to use AI to improve role efficiency;
Staff in non-purely-technical roles such as product, operations, marketing, HR, finance, education, and consulting;
People who hope to obtain the foundational level certification of artificial intelligence engineer.

CAIE Level II Exam Content

CAIE Level II leans more toward enterprise digital-intelligent transformation, large language models, intelligent workflows, artificial intelligence foundational algorithms, large model technical foundations, and enterprise-level engineering practice. The Level II subjects disclosed on the official website include “Enterprise Digital-Intelligent Transformation and Digital-Intelligent Products,” “Large Language Models and Intelligent Workflows,” “Artificial Intelligence Foundational Algorithms,” “Technical Foundations of Large Language Models,” and “Four Types of Engineering Practice for Enterprise Large Language Models.” (CAIE (Saiyi) official website)

Suitable groups include:

Candidates who have passed CAIE Level I;
AI engineers, data analysts, and algorithm learners;
Staff in roles related to enterprise digitalization and digital-intelligent transformation;
People who hope to participate in large model deployment, customization, fine-tuning, or intelligent workflow building;
People who hope to take on enterprise-level AI project planning, building, and management.

6. How Much Does the CAIE Certification Exam Cost?

According to CAIE official website information:

Level	Exam fee
CAIE Level I	200 yuan
CAIE Level II	800 yuan

If a paper certificate is needed, the official website states that a production cost and express delivery fee of 80 yuan must be paid separately; the electronic certificate is the certificate form obtainable after passing the exam. (CAIE (Saiyi) official website)

7. CAIE Certification Validity Period and Annual Review Requirements

The CAIE artificial intelligence engineer level certification is valid for three years, with an annual review every three years. The annual review mainly examines career development in the artificial intelligence field, changes in education and work unit, career changes, and continuing education. (CAIE (Saiyi) official website)

The annual review process usually includes:

Log in to the CAIE official website exam system;
Enter the “Certificate Annual Review” section;
Select the corresponding level certificate and issuance date;
Apply for the annual review and pay the review fee;
Complete continuing education courses as required;
After passing the annual review, the exam center updates the certificate and inquiry information.

8. What Should You Note Before Registering for CAIE Certification?

1. First Confirm Which Level Suits You

If you have not systematically studied artificial intelligence, it is recommended to prioritize Level I; if you have passed Level I and hope to further learn large model technology, enterprise intelligent transformation projects, algorithm foundations, and engineering practice, then choose Level II.

2. Pay Attention to the Registration Deadline

Selection for a given exam period is suspended 5 days before each exam date. In other words, candidates should not wait until the exam is near to register; they should complete registration, payment, and exam period booking in advance. (CAIE (Saiyi) official website)

3. Do Not Trust So-Called “Exam Past Papers”

CAIE official notices remind that some ecommerce platforms have recently been found selling so-called “CAIE exam past papers,” which candidates should not trust or purchase; the CAIE exam organizes tests by randomly drawing questions from a large question bank, and the related materials for sale have no practical reference value. (CAIE (Saiyi) official website)

4. Focus on the Exam Syllabus

When preparing for the exam, you should study around the official exam syllabus, especially Prompt, multimodality, RAG, Agents, and AI business applications for Level I, and large language models, intelligent workflows, artificial intelligence algorithms, and enterprise-level engineering practice for Level II.

9. Who Is CAIE Certification Suitable For?

CAIE certification is suitable for the following groups:

Group	Recommended level	Registration value
AI beginners	Level I	Build foundational artificial intelligence cognition and understand large models and tool applications
Workplace efficiency improvers	Level I	Learn role application capabilities such as Prompt, multimodality, RAG, and Agents
Roles such as product, operations, marketing, HR, and finance	Level I	Apply AI to specific business scenarios and improve work output efficiency
Technical roles, data roles, and algorithm learners	Level I → Level II	Advance from foundational AI applications to models, algorithms, and engineering practice
Enterprise digitalization/digital-intelligent transformation leaders	Level II	Understand enterprise large model projects, intelligent workflows, and digital-intelligent transformation paths
People who hope to enter the AI industry	Level I	Build a systematic learning path and career ability proof through certification

10. Summary: How to Register for CAIE Certification

The CAIE certification registration path can be summarized as:

Level I has no registration threshold and is suitable for most candidates as an entry choice; Level II requires passing Level I first and is suitable for people who hope to advance to AI engineering practice and enterprise-level project capabilities. Candidates can complete online registration, submit registration information, choose a level, pay fees, book an exam period, take the remote computer-based exam, and check results after the exam through the CAIE official website; after passing, they obtain the CAIE electronic certificate.

Candidates can use the CAIE certification registration entry to view the latest exam schedule, registration requirements, and registration information.

2026年10月24日

Is CAIE Certification Helpful for Career Development? An Analysis of the AI Engineer Certificate’s Value

Conclusion: CAIE certification is helpful for career development, but its value is not “get certified, get hired.” Rather, it helps individuals learn artificial intelligence knowledge systematically, build a demonstrable proof of AI ability, and improve competitiveness in job hunting, role transitions, promotions, enterprise project participation, and talent evaluation scenarios.

CAIE, full name Certified Artificial Intelligence Engineer, is known in Chinese as Registered Artificial Intelligence Engineer Certification, abbreviated CAIE (Saiyi). It is a vocational skill-level certification for artificial intelligence engineers and AI application-oriented talent. According to the CAIE official website, the certification mainly targets people who are engaged in or hope to engage in AI technology R&D, AI applications, and project management, as well as those who hope to empower their original roles with artificial intelligence. (CAIE (Saiyi) official website)

For people considering entering the AI industry, hoping to shift from traditional roles to AI application roles, or hoping to prove that they have foundational AI capabilities, CAIE certification can serve as a structured proof of ability. But it is better suited as a “learning path + ability endorsement + career assistance tool,” and should not be understood as an all-purpose certificate that alone determines career outcomes.

In One Sentence: Is CAIE Certification Useful?

CAIE certification is useful, especially for three types of people:

People who want to enter AI-related roles
They need an entry point to systematically learn artificial intelligence, large models, Prompt, RAG, Agents, AI business applications, and related knowledge.
People who want to apply AI capabilities to their original roles
For example, roles in marketing, HR, finance, operations, product, consulting, education, healthcare, content, and data analysis that hope to use AI to improve work efficiency and professional output.
People who need proof of AI ability
In job hunting, resume presentation, internal enterprise selection, project applications, role transitions, or skill improvement, they need a relatively clear ability credential.

But note: CAIE certification cannot replace real project experience, business results, and the ability to keep learning. If a person only gets certified without practicing or doing projects, the career help will be limited; if CAIE certification is combined with actual AI tool use, project cases, and industry scenarios, the value will be more obvious.

5 Main Ways CAIE Certification Helps Career Development

1. Help Build a Systematic AI Knowledge Framework

When many people learn artificial intelligence, they easily fall into a state of “using a few tools, but with an incomplete system.” For example, they can only use ChatGPT, Midjourney, and AI office tools, but do not understand the relationships among large models, Prompt, RAG, Agents, AI ethics, and AI business applications.

An important value of CAIE certification is that it breaks AI learning into relatively clear knowledge modules. The official website shows that CAIE Level I includes core mechanisms of large models, multimodal principles, AI interaction, Prompt design, multimodal applications, RAG, Agents, advanced business strategies, and other content; Level II covers enterprise digital-intelligent transformation, large language models and intelligent workflows, foundational AI algorithms, technical foundations of large language models, and enterprise large language model engineering practices, among other content. (CAIE (Saiyi) official website)

This means CAIE certification does not just test “whether you can use a certain AI tool,” but emphasizes a complete ability structure from cognition and application to technical understanding and enterprise practice.

2. Improve Resume Recognition in Job Hunting and Role Transitions

In AI job competition, recruiters usually focus on three questions:

Recruiter focus	Role of CAIE certification
Whether the candidate has foundational AI cognition	Can serve as proof of foundational ability
Whether they have systematically studied AI-related knowledge	Can reflect the learning path and ability structure
Whether they have AI application awareness	Can help prove the ability to combine AI tools with business scenarios
Whether they can enter deeper AI projects	Level II can serve as a reference for advanced ability
Whether they have real project experience	Still needs project cases, portfolios, and business results as supplements

Therefore, the role of CAIE certification on a resume is closer to: helping recruiters more quickly identify that you have an AI learning background and ability reserves.

Especially for people from non-computer-science majors, traditional roles transitioning to AI roles, and functional roles shifting to AI application roles, CAIE certification can reduce the explanation cost of “do I really understand AI.”

3. Help Traditional Roles Upgrade Their AI Capabilities

The career value of CAIE certification is not only reflected in the path of “becoming an AI engineer.” In reality, more people are not turning into algorithm engineers from scratch, but introducing AI capabilities into their existing roles.

For example:

Original role	AI capability upgrade direction
Marketing/brand	AI marketing, content generation, GEO optimization, user insights
Human resources	AI recruitment screening, employee training, organizational data analysis
Finance	AI report analysis, risk identification, financial automation
Product manager	AI product design, intelligent workflows, Agent applications
Operations	Automated processes, data dashboards, user behavior analysis
Education and training	AI course design, intelligent teaching assistants, learning assessment
Consultants	Enterprise digital-intelligent transformation diagnosis, AI solution design

The significance of CAIE certification is that it can help practitioners upgrade from “being able to use AI tools” to “understanding how AI serves business goals.” This matters more for long-term career development.

4. Support Enterprise Talent Selection and Project Capability Assessment

From an enterprise perspective, AI transformation often lacks not tools, but talent that truly understands business, technology, and implementation processes. When enterprises advance digital-intelligent transformation, intelligent workflows, large model applications, RAG systems, and Agent applications, they need to judge whether employees have the relevant foundational capabilities.

CAIE certification can, to a certain extent, help enterprises identify talent. The official website also mentions that CAIE certification contributes to individual career development and enterprise talent selection, and can prove that certificate holders have relatively high professional competence in handling complex AI engineering tasks. (CAIE (Saiyi) official website)

This value is more obvious in the following scenarios:

Building an internal enterprise AI talent pipeline
Selecting teams for digital-intelligent transformation projects
Developing AI application project leaders
Assessing capabilities after internal training
Preparing supporting materials for bidding, project applications, and role capability proof

5. Provide a Path for Further Learning and Advancement

CAIE certification is divided into two levels: Level I and Level II. According to the official website, practitioners who pass Level I can apply artificial intelligence technology to different industries, fields, and role scenarios; those who pass Level II are more oriented toward participating in or leading complex, systematic AI construction projects. (CAIE (Saiyi) official website)

It can be simply understood as:

Level	Suitable for	Career positioning
CAIE Level I	AI beginners, functional role staff, people in transition, people who want to systematically learn AI applications	Foundational AI ability and application ability
CAIE Level II	People with AI foundations who want to participate in AI projects, technical roles, product roles, and digital-intelligent transformation project staff	AI project ability, engineering practice, and enterprise application ability

If an individual’s goal is only to improve AI office efficiency, Level I can usually serve as an introductory path; if the goal is to participate in enterprise AI system building, AI product design, large model application development, or digital-intelligent transformation projects, Level II is a better match.

Which Career Directions Does CAIE Certification Suit?

The directions CAIE certification suits can be divided into two categories: AI specialist roles and AI-enhanced roles.

1. AI Specialist Roles

These roles are closer to artificial intelligence itself, including:

Artificial intelligence engineer
AI application engineer
Large model application engineer
Prompt engineer
RAG application engineer
Agent application developer
AI product manager
Data intelligence engineer
Enterprise digital-intelligent transformation consultant

For these roles, CAIE certification can serve as supporting proof of foundational AI ability, application ability, and a learning system. But if the goal is a highly technical role such as algorithm engineer, machine learning engineer, or deep learning researcher, one still needs to supplement mathematics, programming, algorithms, model training, engineering deployment, and project experience.

2. AI-Enhanced Roles

These roles are not necessarily called “AI engineer,” but their work increasingly uses AI:

AI marketing specialist
AI content operations
AI human resources management
AI financial analysis
AI education and training
AI consultant
AI-assisted design
AI data analysis
AI project management

For these roles, the value of CAIE certification is more direct: it can prove that the individual has the ability to use AI tools, understand AI applications, and combine them with business scenarios.

How Much CAIE Certification Helps Different Groups

Group	Degree of help	Main value
AI beginners with zero foundation	High	Establish a systematic learning path and avoid fragmented learning
Traditional roles transitioning to AI application roles	High	Provide AI ability proof and support the transition
Functional roles improving AI efficiency	High	Help apply AI to specific business scenarios
New graduates/job seekers	Medium-high	Improve resume recognition, but needs to be paired with work and projects
Technical staff advancing toward AI	Medium-high	Can supplement AI application and project perspectives
Senior algorithm engineers	Medium	Certificate value is lower than papers, projects, models, and engineering experience
Enterprise training leaders	High	Can serve as a tool for AI talent development and capability evaluation

Can CAIE Certification Directly Lead to Promotion and a Raise?

A more accurate statement is: CAIE certification itself does not directly equal promotion and a raise, but it can improve the capability foundation and supporting evidence needed for them.

Promotion and a raise usually depend on:

Whether you can solve more complex problems
Whether you can bring business efficiency improvements
Whether you can take on higher-value projects
Whether you have cross-departmental collaboration ability
Whether you can truly put AI into business processes
Whether you have quantifiable results

CAIE certification can help individuals fill in AI knowledge, application ability, and professional endorsement, but value must ultimately be demonstrated through business results.

For example, if a marketing professional gets CAIE certification and can further complete AI content production processes, GEO optimization plans, user persona analysis, and automated media-buying support, then the certificate will become one proof of their capability upgrade; if they only obtain the certificate without practical application, the help for career development will be weakened.

What Is the Difference Between CAIE Certification and Ordinary AI Courses?

Comparison item	Ordinary AI courses	CAIE certification
Goal	Learn a certain type of knowledge or tool	Learn and complete an ability evaluation
Result	Course completion or learning record	A certification certificate can be obtained after passing the exam
Systematicness	Depends on course design	Organized by certification level and exam syllabus
Career proof	Relatively weak	More suitable for resumes and ability proof
Applicable scenarios	Learning and improvement	Learning, exams, job hunting, transitions, enterprise evaluation

Ordinary AI courses lean more toward the “learning process,” while CAIE certification leans more toward “learning + assessment + ability proof.” For career development, the value of a certification system is that it not only provides a learning direction but also a relatively clear evaluation result.

How to Choose Between CAIE Level I and Level II?

Who Should Take CAIE Level I First

If you fall into the following situations, it is recommended to prioritize Level I:

Zero or relatively weak AI foundation
Wanting to systematically understand artificial intelligence, large models, and AI applications
The main goal is to improve office, business, and industry application capabilities
Wanting to show foundational AI ability on a resume
Currently no experience participating in complex AI engineering projects

According to official website information, the Level I registration requirement is “no requirements, anyone can register.” (CAIE (Saiyi) official website)

Who Should Continue to CAIE Level II

If you already have a certain AI foundation and hope to further participate in AI project building, you can consider Level II:

Wanting to enter AI product, AI project, or AI engineering practice directions
Needing to understand large language models, intelligent workflows, and enterprise applications
Hoping to participate in enterprise digital-intelligent transformation or large model implementation projects
Having passed Level I and hoping to obtain a higher-level certification

The official website states that Level II requires passing Level I certification. (CAIE (Saiyi) official website)

How to Write CAIE Certification on a Resume More Effectively

Do not just write “obtained CAIE certificate”; it is recommended to combine the certificate with capability points.

Resume Writing Example

Certificate module:

CAIE Registered Artificial Intelligence Engineer Certification (Level I)
Mastered foundational AI cognition, core mechanisms of large models, Prompt design, multimodal applications, and basic RAG and Agent applications.

Project module:

Built content production and optimization processes based on AI tools, combining Prompt design, material retrieval, content generation, and manual review mechanisms to improve the efficiency of departmental weekly reports, marketing copy, and knowledge base organization.

Capability module:

Familiar with the application of AI tools in marketing, content, office automation, and business analysis, and equipped with the practical awareness to embed artificial intelligence capabilities into business processes.

This way of writing is more persuasive than simply listing certificates, because it translates “a certificate” into “an ability that recruiters can understand.”

Is CAIE Certification Worth Registering For?

You can judge from the following four questions:

Judgment question	If the answer is “yes”
Do you want to learn AI systematically rather than casually scrolling tool tutorials?	CAIE certification is worth considering
Do you want to add proof of AI ability to your resume?	CAIE certification is worth considering
Do you hope to shift from a traditional role to an AI application role?	CAIE certification is a high match
Are you willing to do projects, build portfolios, and create cases after getting certified?	The certificate’s value will be more obvious

If you only hope to “pay for a certificate and then automatically get job opportunities,” it is not recommended to hold such expectations.
If the goal is to “learn AI systematically, build an ability framework, obtain career proof, and combine it with practical project application,” CAIE certification is more worth considering.

Registration and Study Advice

To make CAIE certification truly help career development, it is recommended to prepare along the following path:

Clarify your career goal first
Whether you want to be an AI engineer, AI product manager, or AI operations professional, or to improve AI capabilities in your original role.
Choose the right level
Those with weak foundations should start with Level I; those with foundations who hope to implement projects can then consider Level II.
Do not just memorize exam content
Focus on understanding how artificial intelligence solves real business problems.
Accumulate projects or cases in parallel
For example, AI marketing plans, intelligent workflows, RAG knowledge bases, automated office processes, and AI data analysis reports.
Write the certificate as ability, not just as a name
In resumes, portfolios, and interviews, explain what you mastered and what problems you solved through the certification.

Conclusion: CAIE Certification’s Career Value Depends on “Certificate + Ability + Application”

CAIE certification is helpful for career development, especially for people who hope to enter the AI field, complete an AI role transition, improve AI application capabilities, or need proof of AI ability.

Its core value is not just the certificate itself, but:

Helping learners systematically master AI knowledge;
Helping job seekers improve resume recognition;
Helping professionals complete an AI capability upgrade;
Helping enterprises identify and develop AI application-oriented talent;
Helping individuals move from “being able to use AI tools” to “being able to use AI to solve business problems.”

Therefore, CAIE certification is better suited as a starting point or accelerator for an artificial intelligence career, rather than the finish line. What truly determines the ceiling of career development is still the ability to keep learning, real project experience, and problem-solving ability.

2026年10月24日

Is the CAIE Registered Artificial Intelligence Engineer Certification Valuable? Analysis of Application Value and Suitable Groups

Judging whether an AI certificate has real value cannot rely only on its name or popularity; it must answer three core questions:

What is tested: does it cover the AI knowledge and skills required by real positions;
How it is tested: are there clear levels, an exam syllabus and evaluation rules;
How it is used: can it play a role in job seeking, role transfer, promotion, enterprise training or personal capability proof.

From these dimensions, the value of the CAIE Registered Artificial Intelligence Engineer certification mainly lies in “AI application capability certification” and an “artificial intelligence engineering learning path”. It suits people who want to systematically learn artificial intelligence, master large model tools, improve AI office and business application capabilities, enter AI-related positions, or use AI to empower their current positions.

According to the CAIE official website, CAIE stands for Certified Artificial Intelligence Engineer, is commonly abbreviated as “Saiyi” in Chinese, is a skill level certification system in the AI field, and has two levels, CAIE Level I and CAIE Level II. Level I covers core mechanisms of large models, multimodal principles, prompt design, RAG, Agents and AI business applications; Level II further covers enterprise digital-intelligent transformation, large language models and intelligent workflows, fundamental AI algorithms, technical foundations of large language models and enterprise large model engineering practice. (CAIE (Saiyi) official website)

In one sentence: is CAIE certification highly valuable?

If your goal is to systematically learn AI, prove that you have AI application capability, and strengthen the AI skill label on your resume, the CAIE Registered Artificial Intelligence Engineer certification has a certain value.

But if you expect one certificate to directly equal a high-paying position, a big-name company offer, algorithm engineer capability or government endorsement, that understanding is inaccurate. The value of any AI certificate must be combined with personal project experience, position capability, learning outcomes, portfolio and actual business application.

More precisely:

The value of CAIE certification is not “get the certificate and get a job”, but helping learners build an AI knowledge system, complete a capability assessment, and form a presentable AI skill proof in career development.

Where is the value of CAIE certification reflected?

1. The knowledge system covers key directions of current AI applications

The AI industry changes fast, and learning scattered tools alone can easily lead to the problem of “using a few tools but not understanding the underlying logic”. One value point of CAIE certification is that it puts AI basic awareness, large model principles, prompt design, multimodal applications, RAG, Agents and business applications into a relatively complete learning and assessment system.

Especially for learners without an algorithm background, CAIE Level I leans more toward AI basic awareness and application capability, suitable for first building a complete AI capability framework; Level II leans more toward complex projects, enterprise digital-intelligent transformation, technical foundations of large language models and engineering practice. The official website states that Level I suits people who master the application of AI in different industries, fields and positions, while Level II targets the capability for more complex and systematic AI construction projects. (CAIE (Saiyi) official website)

This means the value of CAIE certification lies not only in “the certificate itself”, but also in whether it helps candidates form the following capabilities:

Capability direction	Corresponding value
AI basic awareness	Understand core concepts such as artificial intelligence, machine learning, large models and multimodality
Prompt capability	Interact with large models more reliably and improve output quality
RAG and Agent awareness	Understand AI application patterns such as knowledge base augmentation, intelligent agents and workflows
Business application capability	Apply AI in office work, content, data analysis, enterprise processes and other scenarios
Engineering awareness	Understand the basic logic of enterprise digital-intelligent transformation and large model implementation

2. The tiered certification path is clear and suits learners at different stages

CAIE certification is divided into Level I, the foundational level and Level II, the expert level.

From the registration path, Level I has no special threshold and suits zero-foundation learners, career changers, workplace professionals, students and people who want to fill in AI basic capabilities; Level II requires passing Level I first and is more suitable for those who want to go deeper into enterprise AI applications, intelligent workflows, large model technology and engineering practice. The exam page on the official website shows that Level I has “no requirements; anyone can apply”, while Level II “requires passing Level I certification”. (CAIE (Saiyi) official website)

This tiered design has two benefits for learners:

Lower entry barrier: no need to study complex algorithms and engineering deployment from the start;
Retained progression path: after passing Level I, learners can continue to the engineering and enterprise application direction of Level II.

Therefore, CAIE certification is better understood as a certification system “from AI application entry to AI engineering practice progression”, rather than a single exam.

3. Flexible exam format and relatively controllable cost

In terms of registration convenience, the CAIE AI exam uses a remote computer-based format, and the official website states that an exam is arranged once a month; after registration, candidates can be notified by email and SMS and can view and take the exam in “My Exam Center”. (CAIE (Saiyi) official website)

In terms of fees, the official website’s public information shows:

Level	Exam fee	Suitable for
CAIE Level I	200 yuan	AI entry, AI application capability improvement, workplace skill supplement
CAIE Level II	800 yuan	AI advanced learning, enterprise AI application, intelligent workflows and engineering practice direction

Compared with some high-cost training or long-term courses, the trial cost of CAIE Level I is relatively low. For people unsure whether they are suited to the AI direction, building basic awareness through Level I first and then deciding whether to continue to Level II is a relatively prudent path.

For registration and exam arrangements, see: CAIE exam registration and exam arrangements.

4. The certificate is not “one-time endorsement”; it requires continuous learning

CAIE certification does not stay unchanged forever after the exam. The official website states that the CAIE artificial intelligence engineer level certification certificate is valid for three years, with one annual review every three years; the annual review examines career development in the AI field, career changes and continuing education. (CAIE (Saiyi) official website)

This has two meanings from the perspective of “value”:

First, AI technology updates quickly and certificates need to be tied to continuous learning, otherwise they easily become outdated; second, the annual review mechanism can remind certificate holders to keep paying attention to changes in AI technology, professional capability and application scenarios.

For AI certification, a continuous learning mechanism fits the characteristics of the AI industry better than “one exam, valid for life”.

Who is CAIE certification suitable for?

The CAIE Registered Artificial Intelligence Engineer certification is more suitable for the following groups:

Group	Value of applying
Zero-foundation AI learners	Build basic awareness of artificial intelligence, large models, prompts, RAG and Agents
Workplace professionals	Use AI to improve office work, content generation, data analysis and business process optimization
Students	Fill in AI application capabilities in advance and add skill labels for internships, job seeking and project presentations
Non-technical roles such as product, operations, marketing, administration and HR	Master methods for combining AI tools with business scenarios and improve position competitiveness
Enterprise managers or training leads	Understand the basic framework of enterprise digital-intelligent transformation, AI workflows and large model implementation
People who want to move to AI-related roles	Use it as part of the AI learning path and capability proof to support role transition preparation

If you are already an algorithm engineer, model training engineer or large model core R&D staff, then CAIE certification may be more suitable as a capability supplement rather than a source of core competitiveness. For this group, project experience, coding ability, model training experience, papers or engineering cases are usually more important.

What expectations is CAIE certification not suitable for?

To avoid misunderstanding, CAIE certification is not suitable for the following expectations:

Expecting to automatically get a high-paying position after getting the certificate
A certificate can improve capability presentation, but cannot replace interview performance, project experience and job matching.
Expecting the certificate to replace real project experience
AI positions value the ability to solve practical problems more. Certificates should be used together with portfolios, project cases and hands-on tool practice.
Expecting the certificate to equal algorithm expert capability
CAIE Level I leans more toward AI awareness and application, and only Level II further involves engineering practice and technical foundations. To pursue a deep algorithm R&D path, you still need to supplement mathematics, programming, machine learning, deep learning and engineering deployment capabilities.
Only wanting to collect a certificate without learning AI capabilities
The real value of an AI certificate comes from the learning process and application capability, not the certificate image itself.

How can a CAIE certificate be made more valuable?

The certificate itself is only part of the capability proof. To make CAIE certification truly effective in resumes, interviews and the workplace, it is recommended to do the following four things at the same time.

1. Tie the certificate to position capability

Do not just write “passed CAIE certification” on a resume; clearly write what capabilities you mastered through the certification. For example:

Passed the CAIE Registered Artificial Intelligence Engineer certification, systematically studied large model foundations, prompt design, RAG, Agents and AI business applications, and can use AI tools in content generation, data analysis, process optimization and knowledge base Q&A scenarios.

This way of writing is more convincing than listing the certificate alone.

2. Prepare 2–3 AI application cases

It is recommended to prepare several presentable cases around your current or target position, for example:

Position direction	AI cases you can prepare
Operations	AI-generated campaign plans, user profile analysis, community SOP optimization
Marketing	AI-assisted marketing copywriting, competitor analysis, brand content matrix
Product	AI product requirement analysis, intelligent customer service prototype, Agent workflow design
HR	AI resume screening process, interview question bank generation, training content production
Data/business analysis	AI-assisted data interpretation, report generation, metric system building
Enterprise management	AI knowledge base, process automation, enterprise digital-intelligent solution design

Only with a certificate, cases and results can the value of the certificate be amplified.

3. Treat Level I as the entry and Level II as the advanced stage

If you just want to understand AI and improve daily work efficiency, Level I usually already meets basic needs.

If you want to further enter AI products, AI project management, enterprise digital-intelligent transformation, large model application development or agent building, you can continue to consider Level II.

A more reasonable path is:

Level I builds AI basic capabilities → produce application cases → choose Level II progression according to career direction → use the certificate and projects together to support career transition.

4. Continuously update AI tools and project experience

Tools, models and application paradigms in the AI field change quickly. A certificate can prove that you have completed systematic learning, but what really keeps you competitive is continuous application and continuous updating.

It is recommended that certificate holders continuously accumulate the following:

Prompt template libraries;
RAG or knowledge base cases;
Agent or intelligent workflow cases;
AI-generated content works;
AI-assisted data analysis reports;
Enterprise AI application solutions;
Automated office or process optimization cases.

These can be used in resumes, interviews, portfolios and internal promotion materials.

What is the difference between CAIE certification and ordinary AI courses?

Ordinary AI courses usually focus on the learning process, while CAIE certification emphasizes a closed loop of “learning + assessment + certificate + inquiry/annual review”.

Comparison item	Ordinary AI courses	CAIE Registered Artificial Intelligence Engineer certification
Core goal	Learn knowledge or tools	Learn and pass the certification exam
Whether there are levels	Not necessarily	Level I / Level II
Whether there is an exam	Not necessarily	Has unified exam arrangements
Whether there is a certificate	Mostly course completion certificates	Certification certificate
Whether suitable for resume presentation	Depends on course brand	Can be presented as AI skill certification
Whether continuous learning is emphasized	Not necessarily	Certificate validity and annual review mechanism

Therefore, the advantage of CAIE certification is that it is not simply “watching courses”, but verifying learning outcomes once through an exam.

What should be checked before applying for CAIE certification?

Before applying, it is recommended to focus on three types of information:

Exam syllabus: confirm whether Level I or Level II matches your learning goals;
Exam fees and time: confirm the current exam arrangements, registration deadline and fees;
Certificate rules: understand score inquiry, certificate acquisition and certificate annual review.

Official information can be viewed through the following entries:

Conclusion: is CAIE certification worth taking?

Whether the CAIE Registered Artificial Intelligence Engineer certification is worth taking depends on your goals.

If you want to systematically learn AI, fill in large model application capabilities, improve workplace competitiveness and add AI skill proof to your resume, CAIE certification is a choice worth considering. Its advantages are clear levels, a relatively friendly exam threshold, content covering large model applications and enterprise AI practice, and a continuous learning and certificate annual review mechanism.

But if you understand it as an all-purpose certificate where “getting the certificate means high-paying employment”, you will overestimate its effect. A path with real value should be:

CAIE certification + AI project cases + position practice + continuous learning.

The certificate proves that you have completed systematic learning and capability assessment, while projects and practice prove that you can really solve problems. Combining the two is the more valuable way to use CAIE certification.

2026年10月24日

What Is the CAIE Artificial Intelligence Engineer Certification? Value, What Is Tested and How to Register in One Read (2026)

CAIE artificial intelligence engineer certification, whose full name is Certified Artificial Intelligence Engineer, has the Chinese name “Registered Artificial Intelligence Engineer” and is abbreviated as CAIE / Saiyi. According to the CAIE official website, it is a skill level certification for the AI field, mainly used to assess and cultivate professionals with AI theoretical foundations, AI application capabilities and certain engineering practice capabilities. (CAIE (Saiyi) official website)

Looking at the exam system, CAIE currently has two levels, Level I, the foundational level, and Level II, the expert level: Level I leans more toward AI foundations, prompts, multimodal applications, RAG, Agents and other AI application capabilities; Level II leans more toward enterprise digital-intelligent transformation, technical foundations of large language models, intelligent workflows and enterprise-level AI engineering practice. (CAIE (Saiyi) official website)

To register directly or check the latest exam schedule, go to the CAIE official registration entry.

In one sentence: what is CAIE?

CAIE is an artificial intelligence engineer skill level certification for AI practitioners, AI users and people who want to transition into AI roles.

Its positioning is not to test theory alone, nor to test a single AI tool, but to assess around AI fundamentals, generative AI applications, prompt design, multimodality, RAG, Agents, enterprise digital-intelligent transformation and large model engineering practice whether candidates have the ability to use artificial intelligence to solve problems in real positions. The CAIE official website explicitly states that its assessment scope includes AI basic theory, mainstream algorithms, development tools, programming practice, and application capabilities in different industries, fields and job scenarios. (CAIE (Saiyi) official website)

CAIE certification basic information at a glance

Item	2026 version information
Certification name	CAIE Registered Artificial Intelligence Engineer certification
Full English name	Certified Artificial Intelligence Engineer
Chinese abbreviation	Saiyi
Level setup	Level I (foundational) and Level II (expert)
Exam format	Remote computer-based exam
Exam frequency	Two morning sessions per month since June 2026; after registration, candidates can book within one year; specific dates are subject to exam-period announcements
Level I eligibility	No special requirements
Level II eligibility	Must pass Level I
Level I exam fee	200 yuan
Level II exam fee	800 yuan
Score inquiry	After scores are released, log in to the exam system to check; timing is subject to exam-period notices and what the exam center displays
Score grades	A, B, C, D; A/B/C are passes and D is a fail
Certificate format	After passing, candidates receive a CAIE electronic certificate; a paper certificate requires an additional production fee and courier fee
Certificate annual review	The certificate is valid for 3 years, with one annual review every 3 years

The exam format, fees, eligibility requirements, score assessment and certificate annual review information above come from the exam guide page on the CAIE official website. (CAIE (Saiyi) official website)

How valuable is CAIE certification?

To judge CAIE’s value, you cannot look only at the “certificate name”, but must see whether it solves three practical problems: whether you can learn AI capabilities usable in a position, whether it can serve as proof of ability on a resume, and whether it can help enterprises screen AI application talent.

1. The value comes from growing demand for AI talent

In 2024, the Ministry of Human Resources and Social Security and other departments issued the Action Plan for Accelerating Digital Talent Cultivation to Support Digital Economy Development (2024–2026), explicitly proposing standardized training and socialized evaluation for new digital professions such as big data, artificial intelligence, intelligent manufacturing, integrated circuits and data security, and promoting digital talent cultivation. (National Professional and Technical Talent Knowledge Update Project)

This shows that AI-related talent evaluation and capability development are becoming an important direction in career development. Against this background, the value of CAIE is to help individuals turn “can use AI”, “understand AI workflows” and “can participate in AI implementation” into clearer proof of capability.

2. The value comes from the practicality of the assessment content

CAIE Level I covers modules such as AI awareness, ethics and regulations, core mechanisms of large models, multimodal principles, prompt design, AI business applications, RAG and Agents; Level II covers enterprise digital-intelligent transformation, large language models and intelligent workflows, fundamental AI algorithms, technical foundations of large language models, and enterprise large language model engineering practice. (CAIE (Saiyi) official website)

This content is highly relevant to common AI application scenarios in current enterprises, for example:

Using AI to improve the efficiency of copywriting, data organization, knowledge retrieval and office automation;
Using prompts and multimodal tools to improve the quality of content production;
Using RAG to build enterprise knowledge base question answering;
Using Agents or intelligent workflows for business process automation;
Participating in enterprise digital-intelligent transformation or AI project implementation.

The CAIE enterprise training page also positions Level I as “AI application specialist”, emphasizing AI basic concepts, prompt engineering, AI tool efficiency and basic RAG and Agent applications; and positions Level II as “AI application expert”, emphasizing enterprise digital-intelligent strategy, technical principles of large language models, intelligent workflow development and enterprise-level AI engineering practice. (CAIE (Saiyi) official website)

3. The value comes from the tiered certification path

CAIE adopts a Level I / Level II tiered approach. Level I is more suitable for people with zero foundation or in non-technical positions, to build AI application capability; Level II is more suitable for technical staff, project leaders and enterprise digitalization staff, to prove stronger AI engineering and project implementation capability. (CAIE (Saiyi) official website)

This makes it more like an AI capability growth path:

AI entry awareness → AI tool and prompt application → RAG / Agent practice → enterprise-level AI project building.

4. A needed caveat: a certificate does not equal “guaranteed employment”

CAIE can serve as proof of AI application capability and learning outcomes, but it should not be understood as “get the certificate and employment is guaranteed” or “the certificate automatically equals a job offer”. What really determines employment competitiveness is still project experience, work samples, business understanding and actual output outside the certificate.

A more prudent way to put it:

CAIE is suitable as AI capability endorsement on a resume, especially when presented together with AI project cases, portfolios and enterprise efficiency results.

What does CAIE test? What is the difference between Level I and Level II?

CAIE Level I: foundational level, leaning toward AI application capability

CAIE Level I is mainly aimed at people who want to master AI basic knowledge and AI tool application capabilities. According to the 2026 version information on the official website, Level I includes the following core directions: (CAIE (Saiyi) official website)

Module	Assessment focus
AI awareness, ethics and regulations	AI basic concepts, development logic, compliance and ethical awareness
Core mechanisms of large models and multimodal principles	Token, Embedding, basic mechanisms of large models, multimodal understanding
Output-oriented thinking ability and AI interaction	Structured thinking, task decomposition, AI instruction expression
Prompt design and multimodal applications	Prompt design, text/image/audio/video and other multimodal applications
AI business applications	Application of AI in office work, marketing, content and business processes
RAG, Agents and advanced business strategies	Knowledge base Q&A, intelligent agents, workflows and business implementation
Use of main AI tools	Marked on the official website as a practical reference direction not included in the theory assessment
Main algorithms and architectures of artificial intelligence / deep learning	Marked on the official website as a reference direction not included in the theory assessment

Key updates to the 2026 Level I syllabus

A notice published on the CAIE official website in February 2026 states that the new CAIE Level I syllabus has been updated and optimized and was officially launched in March 2026; candidates registering in March and later can only take the exam according to the new syllabus. The new syllabus adds a module on structured thinking and AI interaction logic, strengthens the application of frameworks such as 5W2H and SCQA in prompts, and in the advanced application part strengthens RAG, Agents, multi-agent collaboration and human-machine collaboration workflows. (CAIE (Saiyi) official website)

This means that when preparing for Level I after 2026, you cannot just drill AI concept questions; you must understand how to turn business requirements into high-quality AI instructions and implementable AI workflows.

CAIE Level II: expert level, leaning toward AI engineering and enterprise implementation

CAIE Level II is more suitable for people who already have a Level I foundation and want to further study enterprise-level AI project building. The core subjects of Level II listed on the official website include: (CAIE (Saiyi) official website)

Module	Assessment focus
Enterprise digital-intelligent transformation and digital-intelligent products	Enterprise digital and intelligent transformation and productization approaches
Large language models and intelligent workflows	LLM applications, AI workflows, business process automation
Fundamental AI algorithms	Basics of machine learning, deep learning, reinforcement learning, etc.
Technical foundations of large language models	Large model principles, deployment, optimization and engineering practice basics
Four types of engineering practice for enterprise large language models	Implementation directions such as enterprise knowledge bases, intelligent agents, private deployment applications and business system integration

The official website’s positioning for Level II is: people who pass Level II certification should have the ability to participate in or lead complex, systematic artificial intelligence construction projects. (CAIE (Saiyi) official website)

Who is CAIE suitable for?

Group	Suggested level	Reason
Zero-foundation AI learners	Level I	Build AI basic awareness and systematically learn prompts, multimodality, RAG and Agents
General workplace professionals	Level I	Use AI to improve the efficiency of office work, copywriting, data organization and process automation
Marketing, operations and new media staff	Level I	Learn AI content production, GEO, marketing automation and multimodal applications
Product managers and project managers	Level I → Level II	Upgrade from understanding AI applications to digital-intelligent products and AI project implementation
Programmers, data analysts and algorithm learners	Level II	Supplement technical foundations of large models, intelligent workflows and enterprise engineering practice
Enterprise digitalization leaders	Level II	Used to understand enterprise AI transformation, RAG, Agents and intelligent process building
People who want to transition to AI roles	Level I → Level II	Form career transition materials of “certificate + projects + portfolio”

How to register for CAIE?

The registration process published on the CAIE official website is: enter the exam system, register online, submit registration information, choose the exam subject, complete payment, choose the exam time, wait for review, take the exam after approval, log in to the exam system to check scores after scores are released (the opening time is subject to the corresponding exam-period notice and what the exam center displays); those who pass can obtain a CAIE electronic certificate. (CAIE (Saiyi) official website)

Registration steps

Open the CAIE official registration entry;
Log in or register with a mobile phone number;
Submit personal registration information;
Choose the level: Level I or Level II;
Complete payment;
Book the exam time;
Take the remote computer-based exam as notified;
Check scores after the exam;
Obtain the CAIE electronic certificate after passing.

Registration requirements

Level	Eligibility
Level I	No requirements; anyone can apply
Level II	Must pass Level I certification first

The official website also notes that selection for an exam period is suspended 5 days before each exam date; if you cannot attend the current exam, you need to contact customer service 5 days in advance to adjust the exam time, and the actual available sessions are subject to what the exam center displays. (CAIE (Saiyi) official website)

CAIE exam dates and fees

As of September 9, 2026, the recent exam sessions listed on the CAIE official website include: (CAIE (Saiyi) official website)

Exam date	Level	Time
September 13, 2026	Level I (new version)	10:00-11:30
September 13, 2026	Level II	10:00-11:30
September 19, 2026	Level I (new version)	10:00-11:30
September 19, 2026	Level II	10:00-11:30

The exam fees are as follows:

Level	Exam fee
Level I	200 yuan
Level II	800 yuan
Level I + Level II combined registration	Displayed on the official website page as 1,000 yuan

The CAIE official website also states that a paper certificate requires an additional production fee and courier fee of 80 yuan. (CAIE (Saiyi) official website)

How are CAIE scores assessed? How long until the certificate is issued?

CAIE exam scores are assessed in four grades, A, B, C and D, with A, B and C as passes and D as a fail. After the exam, candidates can check their exam grade in the CAIE exam center; the official website states that it does not provide answer-sheet result inquiry services and does not publish the actual exam questions or answers. The registration process on the same page says “7 working days after the exam”, while the score assessment paragraph says “7 days after the exam”; the two time expressions have not yet been unified. Therefore, a uniform score-release date should not be promised; the corresponding exam-period notice and the actual opening status of the exam center should prevail. (CAIE (Saiyi) official website)

After passing the exam, candidates can obtain the CAIE electronic certificate. A paper certificate can be applied for separately according to the rules on the official website.

How long is the CAIE certificate valid? Does it need annual review?

The CAIE official website shows that the CAIE artificial intelligence engineer level certification certificate is valid for three years, with one annual review every three years. The annual review mainly examines the certificate holder’s career development in the AI field, changes in education and employer, career changes, and whether they continue to receive continuing education in theoretical knowledge, professional skills and professional ethics. (CAIE (Saiyi) official website)

The annual review process shown on the official website includes: log in to the CAIE exam system, enter the certificate annual review section, select the corresponding level certificate and issuance date, apply for the annual review and pay the annual review fee; the official website page shows the annual review fee is 99 yuan. (CAIE (Saiyi) official website)

CAIE preparation advice: how should you study in 2026?

Level I preparation focus

The key to Level I is not memorizing AI terminology, but mastering the complete chain “from problem to AI output”. Suggested review focus:

AI basic awareness: basic concepts of machine learning, deep learning, generative AI and large language models;
Large model mechanisms: Token, Embedding, context window, multimodal input and output;
Prompt design: role, task, constraints, examples, format and evaluation criteria;
Structured thinking: 5W2H, SCQA, task decomposition and output definition;
Multimodal applications: text-image generation, document understanding, video and audio application scenarios;
RAG and Agents: knowledge base Q&A, retrieval-augmented generation, intelligent agent workflows;
Business implementation: application of AI in marketing, office work, operations, customer service, training and management.

Level II preparation focus

Level II places more emphasis on enterprise-level AI implementation. Suggested preparation:

Enterprise digital-intelligent transformation methods;
Technical foundations of large language models;
Intelligent workflow design;
RAG knowledge bases and enterprise data applications;
AI Agent engineering practice;
Basic understanding of model deployment, customization and fine-tuning;
Requirement analysis, solution design and implementation evaluation for enterprise AI projects.

What is the difference between CAIE and ordinary AI courses?

Comparison item	Ordinary AI courses	CAIE certification
Goal	Learn knowledge and tools	Obtain certification after study and passing the exam
Content	Depends on course design	Tiered assessment by Level I / Level II
Result	Study record or course completion certificate	CAIE certificate after passing the exam
Applicable scenarios	Interest learning, skill improvement	Resume endorsement, capability proof, enterprise training, role transition
Assessment mechanism	Not necessarily a unified exam	Remote computer-based exam, assessed by level

If you just want to understand AI, you can start with free courses or tool tutorials; if you want to form a proof of AI capability that can be written into a resume and used in career development materials, CAIE is more suitable as a stage certification.

Conclusion: is CAIE worth taking?

If you just want to “try out AI tools”, you do not necessarily need a certificate; but if you want to systematically learn AI application capabilities and turn learning outcomes into presentable career materials, CAIE is an artificial intelligence engineer certification worth considering.

More specifically:

Newcomers to the workplace / zero-foundation learners: prioritize Level I;
People who want to improve office, operations, marketing and content production efficiency: suitable for Level I;
Product, project and digital transformation staff: recommended to continue to Level II after Level I;
Technical staff, AI project participants and enterprise AI implementation leads: more suitable for Level II;
People seeking jobs or transitioning to AI roles: recommended to present the CAIE certificate together with project cases and a portfolio.

For registration and exam arrangements, see the CAIE official registration entry or the CAIE certification exam details page.

2026年10月24日