Microsoft AI Certification Guide

Microsoft AI Credentials Have Changed

Microsoft’s AI certification and credential landscape changed significantly in 2026. If you have been researching Microsoft AI training, you may still encounter courses, articles, and study materials referring to exams such as AI-900, AI-102, and DP-100. Those exam paths have changed or retired, making it important to check current Microsoft requirements before choosing what to study.

Microsoft now offers several ways to demonstrate AI knowledge and practical skills. These include foundational certification as well as Microsoft Applied Skills credentials designed around specific workplace tasks and technologies.

That means the best Microsoft AI credential for you depends on what you are trying to accomplish. Someone building foundational AI knowledge may need a different path from a developer working with generative AI, a professional building AI agents, or a business user learning to apply Microsoft AI tools at work.

This guide will help you understand the current Microsoft AI credential landscape, identify which options may fit your goals, and avoid spending time preparing for outdated exams.

Microsoft Certifications vs. Microsoft Applied Skills

Before choosing a Microsoft AI credential, it helps to understand that Microsoft offers more than one type of credential. Two important options are Microsoft Certifications and Microsoft Applied Skills.

Both can demonstrate learning, but they are designed for different purposes.

Microsoft Certifications

Microsoft Certifications are broader credentials associated with particular technologies, roles, or areas of expertise. They typically require passing a certification exam that measures knowledge across a defined set of skills.

A certification may make sense when you want a credential representing a broader foundation of knowledge or when a particular Microsoft certification is relevant to the type of work or career you are pursuing.

Microsoft Applied Skills

Microsoft Applied Skills are narrower, task-focused credentials. Instead of covering a broad professional role, they are designed to demonstrate that you can complete a particular real-world task using Microsoft technologies.

These credentials generally use interactive, lab-based assessments in which you demonstrate practical skills rather than relying only on a traditional certification exam.

For someone who already knows what capability they want to develop—such as creating an AI solution, working with generative AI, or building an AI agent—an Applied Skills credential may provide a more focused learning path.

Neither approach is automatically better. The useful question is what you want the credential to demonstrate and how closely that matches your career, learning, or workplace goals.

Microsoft Certified: Azure AI Fundamentals (AI-901)

For people beginning their Microsoft AI learning journey, Microsoft Certified: Azure AI Fundamentals is one of the main credentials to consider.

The certification uses Exam AI-901 and is designed for people who are early in their development of AI solution skills. It combines foundational understanding of artificial intelligence with introductory technical skills for working with AI solutions in Microsoft Azure.

What Does AI-901 Cover?

The current AI-901 exam focuses on two broad areas: understanding AI concepts and capabilities, and implementing AI solutions using Microsoft Foundry.

Topics include responsible AI, generative AI, AI models, common AI workloads, text and speech, computer vision, information extraction, and AI agents. The exam also includes practical concepts such as prompting, deploying models, working with AI applications, and creating basic agent solutions.

This makes the current fundamentals credential more than a vocabulary-only introduction to artificial intelligence. Learners should expect to understand both AI concepts and how Microsoft technologies can be used to implement basic AI solutions.

Who Is AI-901 For?

AI-901 may be worth exploring if you are beginning a technical AI learning path and want structured exposure to Microsoft’s AI ecosystem.

It may be particularly relevant for students, early-career technology professionals, career changers developing technical AI skills, or professionals who expect to work with Microsoft Azure and Microsoft Foundry.

Some familiarity with Python and basic cloud concepts can be useful. You do not need to be an experienced AI engineer before beginning, but the current credential includes technical material that goes beyond a purely nontechnical introduction to AI.

What Happened to AI-900?

If you find older training materials recommending Exam AI-900, check their publication date before using them.

AI-900 was the previous exam for Microsoft Azure AI Fundamentals. Microsoft retired that exam on June 30, 2026. The current exam is AI-901.

That distinction matters because older AI-900 study guides may not reflect the skills measured by the current exam. Before paying for a course or spending significant time preparing, compare the material with Microsoft’s current AI-901 exam objectives.

Intermediate Microsoft AI Certifications

After developing foundational knowledge, some learners may want a credential focused on building and deploying AI solutions. Microsoft currently offers several intermediate certifications for different types of AI development work.

The right choice depends less on which credential sounds most advanced and more on the technologies and responsibilities you expect to use.

Azure AI Apps and Agents Developer Associate (AI-103)

Microsoft Certified: Azure AI Apps and Agents Developer Associate is designed for people who build, manage, and deploy AI applications and agents using Azure and Microsoft Foundry.

The certification covers areas such as generative AI, agentic solutions, computer vision, text analysis, and information extraction. Candidates should already have experience developing applications with Python and familiarity with Azure services and AI concepts.

This path may be relevant for developers and aspiring AI engineers who want to build AI-powered applications and agent solutions within Microsoft’s Azure ecosystem.

Azure AI Cloud Developer Associate (AI-200)

Microsoft Certified: Azure AI Cloud Developer Associate focuses more heavily on the cloud infrastructure and back-end development needed to support AI solutions on Azure.

The certification includes areas such as containerized applications, Azure data services, messaging and event systems, security, monitoring, troubleshooting, and scalable application architecture.

Candidates are expected to have technical experience that includes Python, Azure development tools, data services, and containerized applications.

This credential may be particularly relevant for developers who want to work on the cloud systems and production infrastructure surrounding AI applications rather than concentrating primarily on AI models and agents.

AI Agent Builder Associate (AB-620)

Microsoft Certified: AI Agent Builder Associate focuses on designing, extending, integrating, testing, and managing enterprise AI agents using Microsoft Copilot Studio and related Microsoft technologies.

The certification is intended for professional developers and advanced builders. Relevant knowledge includes Microsoft Power Platform, Dataverse, Microsoft 365 Copilot, Microsoft Foundry, APIs, prompt engineering, and generative AI concepts.

This path may make sense for professionals who expect to build AI agents that connect with organizational data, business applications, APIs, and enterprise workflows.

How Are These Certifications Different?

Although these credentials overlap in their use of artificial intelligence, they emphasize different types of work.

AI-103 concentrates on developing AI applications and agents with Azure and Microsoft Foundry. AI-200 places greater emphasis on the cloud architecture, back-end services, security, monitoring, and infrastructure supporting AI applications. AB-620 focuses on building and integrating enterprise agents through Microsoft Copilot Studio and the broader Microsoft business technology ecosystem.

Before choosing among them, look at the actual work you want to learn how to do. Matching the credential to your intended skills is usually more useful than selecting one simply because it appears more advanced.

Microsoft Applied Skills for AI

A full certification is not the only way to demonstrate Microsoft AI skills. Microsoft Applied Skills credentials provide a more focused option for people who want to develop and demonstrate a specific capability.

Instead of preparing for a broad certification exam, you can choose an Applied Skills path that closely matches something you want to do at work or add to your professional skill set.

Microsoft’s available Applied Skills credentials can change as technologies evolve, so it is important to review the current Microsoft Learn catalog before beginning a particular path.

Generative AI and Microsoft Foundry

Some Applied Skills credentials focus on building generative AI solutions with Microsoft Foundry and related Azure technologies.

These learning paths can be useful for people who want hands-on experience working with generative AI applications, models, prompts, and the tools used to build AI solutions.

For a learner who already understands basic AI concepts, this can provide a way to move from general knowledge toward a more specific technical capability.

AI Agents

AI agents have become an increasingly important part of Microsoft’s AI ecosystem.

Microsoft offers Applied Skills options related to creating agents with technologies such as Microsoft Foundry and Microsoft Copilot Studio. Depending on the credential, learners may work with topics such as agent behavior, instructions, knowledge sources, tools, business data, and workflow integration.

This type of credential may be useful if your goal is to learn how AI agents can perform tasks, interact with information, or participate in business processes.

Business and Workplace AI

Not every AI learner needs to become an AI developer.

Microsoft also provides learning and credential options related to using AI within business applications and workplace processes. These can be relevant for professionals who want to apply AI to productivity, automation, customer interactions, organizational information, or other business activities.

For many professionals, learning how to use and evaluate AI effectively within an existing occupation may be more immediately useful than pursuing a highly technical AI engineering credential.

When an Applied Skills Credential May Make Sense

An Applied Skills credential may be worth considering when you can identify a specific capability you want to develop and demonstrate.

For example, you might want to build an AI agent, create a generative AI application, automate part of a business process, or gain practical experience with a particular Microsoft platform.

Because these credentials are narrower than broad certifications, they can also provide a way to explore an area before committing to a longer certification path.

The important question is not how many credentials you can collect. It is whether the learning helps you build a skill you can actually use.

Which Microsoft AI Credential Should You Choose?

The best place to start depends on what you already know and what you want to be able to do. You do not necessarily need to progress through every Microsoft AI credential in order.

If You Are New to AI

Consider beginning with Microsoft Certified: Azure AI Fundamentals and the AI-901 exam.

This path can help you develop a foundation in AI concepts while introducing you to Microsoft’s AI technologies. From there, you can decide whether you want to continue toward technical development, AI agents, cloud infrastructure, or another area.

If You Want to Build AI Applications and Agents

Explore Microsoft Certified: Azure AI Apps and Agents Developer Associate and the AI-103 exam.

This path is more appropriate for someone who already has programming experience and wants to develop AI applications and agentic solutions using Azure and Microsoft Foundry.

If You Want to Build the Cloud Systems Behind AI

Explore Microsoft Certified: Azure AI Cloud Developer Associate and the AI-200 exam.

This path emphasizes the Azure services, back-end development, security, monitoring, data services, and infrastructure that help AI applications operate reliably in production.

If You Want to Build Enterprise AI Agents

Explore Microsoft Certified: AI Agent Builder Associate and the AB-620 exam.

This path is oriented toward building and integrating enterprise agents using Microsoft Copilot Studio and related Microsoft business technologies.

If You Want a Specific Practical Skill

Explore Microsoft Applied Skills.

A focused Applied Skills credential may be appropriate if you can already identify the task you want to learn, such as building an AI agent, developing a generative AI solution, or applying AI within a particular Microsoft environment.

This can also be a useful way to gain practical experience before deciding whether a broader certification is worth pursuing.

If You Are a Business or Nontechnical Professional

Do not assume that you need to pursue a developer-level certification simply because you want stronger AI skills.

You may benefit more from developing practical AI literacy, learning how to use AI responsibly in your existing work, and choosing focused training that relates directly to your occupation.

A credential can provide structure and evidence of learning, but the credential itself should support a larger goal. Start with the work you want to do, identify the skills that work requires, and then decide whether a Microsoft credential helps you close that gap.

How Much Do Microsoft AI Credentials Cost?

How Much Do Microsoft AI Credentials Cost?

Cost is worth considering before beginning a certification path, but the exam fee may be only part of the investment. You may also spend time on training, hands-on practice, labs, study materials, or other learning resources.

Before registering for an exam, check Microsoft’s current certification page for the credential you are considering. Pricing and availability can vary by country or region and may change over time.

Certification Exam Costs

Microsoft displays current exam pricing during the certification and scheduling process. Because prices can vary by location, use Microsoft’s current listing rather than relying on an older article, course, or study guide for the exact amount.

Also consider whether your employer offers professional-development funding, training benefits, exam vouchers, or reimbursement for certifications related to your work.

You do not necessarily need to purchase expensive third-party training. Microsoft Learn provides official learning resources for many Microsoft credentials, and hands-on practice may be more valuable than simply adding more study materials.

Microsoft Applied Skills

Microsoft Applied Skills credentials use practical assessments rather than the same traditional exam structure used for Microsoft Certifications.

Check the individual credential page before beginning for current requirements, assessment information, and availability. Microsoft can update these programs as its products and credential system evolve.

How Long Should You Expect to Prepare?

There is no single preparation time that applies to everyone.

Someone who already works with Azure, Python, Microsoft Foundry, Copilot Studio, or related technologies may need less preparation than someone encountering those tools for the first time.

Instead of choosing an arbitrary number of weeks, review the skills measured by the credential and compare them with what you can already do. Then build your study plan around the gaps.

Hands-on practice is particularly important for technical credentials. Being able to recognize a concept while studying is different from being able to use the technology to solve a problem.

Are Microsoft AI Credentials Worth It?

A Microsoft AI credential can be useful when it supports a specific career or learning objective.

It can provide a structured learning path, help you identify skills you need to develop, and give you a way to demonstrate that you completed a defined body of work. A Microsoft credential may also be relevant when the employers, clients, or projects you are interested in use Microsoft technologies.

However, a credential does not guarantee a job, promotion, salary increase, or successful career change.

Its value is stronger when you can combine the credential with practical ability. Projects, workplace experience, problem-solving skills, communication, and evidence that you can apply what you learned can matter alongside the credential itself.

Before committing significant time or money, ask a simple question: What will I be able to do after completing this that I cannot do today?

If you can answer that clearly, you are in a much better position to decide whether the credential is worth pursuing.

What Should You Do Next?

Start with the outcome you want rather than the credential you think you should earn.

If you are new to artificial intelligence, build a foundation first and explore whether AI-901 matches what you want to learn. If you already have technical experience, compare the intermediate certifications with the type of AI development work you want to pursue. If you need one specific practical capability, an Applied Skills credential may be a more focused option.

Before enrolling in a course or paying for an exam, review the current credential requirements on Microsoft Learn. Microsoft can update exams, skills measured, learning paths, and credential availability as its technologies evolve.

Then compare those requirements with the skills you already have. Identify the most important gaps and build a learning plan around them rather than trying to learn everything at once.

Most importantly, give yourself opportunities to use what you learn. Build a project, solve a workplace problem, experiment with the technology, or create something you can explain to another person.

A credential can document learning. The longer-term value comes from being able to apply that learning to useful work.