Certification comparison
AI-900 retired on June 30, 2026. Microsoft continues the Azure AI Fundamentals credential through its current exam path. AI-102 retired on June 30, 2026 and is no longer an active exam. Use Microsoft's current role-based AI credential guidance for a new plan.
Side-by-side decision guide
| Decision factor | AI-900 | AI-102 |
|---|---|---|
| Purpose | Introduced AI and machine-learning concepts, Azure AI workloads, and responsible AI fundamentals. | Covered design, development, deployment, security, and monitoring of Azure AI solutions. |
| Intended audience | Technical and non-technical candidates beginning an Azure AI learning path. | Azure AI engineers with software-development and cloud implementation responsibilities. |
| Experience level | Foundational AI | Intermediate role-based AI engineering |
| Recommended prerequisites | No formal prerequisite; basic cloud and client-server concepts are helpful. | No formal exam prerequisite; Python or C#, REST APIs, SDKs, and Azure AI experience were expected. |
| Technical depth | Foundational | High implementation depth |
| Management depth | Low | Low |
| Relative difficulty | Foundational | Intermediate to advanced implementation |
| Typical preparation time | Often several weeks for candidates new to AI concepts and Azure services. | Typically a multi-month, lab-driven preparation cycle. |
| Current exam standard | Skills measured as of May 2, 2025 | Confirm the current exam standard with the provider |
| Exam length | 45 minutes | 100 minutes |
| Question count | Provider did not publish a fixed item count | Provider did not publish a fixed item count |
| Passing methodology | 700/1000 | 700/1000 |
| Certification provider | Microsoft | Microsoft |
| Renewal requirements | Microsoft fundamentals certifications do not expire; the AI-900 exam retired on June 30, 2026. | The certification and AI-102 renewal path retired on June 30, 2026. |
| Vendor-specific or neutral | Microsoft Azure-specific | Microsoft Azure-specific |
| Typical job roles | AI-aware business professional, junior cloud professional, product or project stakeholder | Azure AI engineer, AI application developer, cloud AI developer |
| Career paths | AI literacy, Azure data and AI, responsible AI, later role-based engineering | AI engineering, application development, search and knowledge mining, generative AI implementation |
Use Microsoft's current Azure AI Fundamentals path for conceptual AI literacy without an engineering prerequisite.
AI-102 historically fit developers implementing Azure AI solutions; it is now retired, so use Microsoft's current role-based guidance.
The fundamentals path was commonly taken first, though it was never a formal prerequisite.
Foundational concepts support later implementation work, but hands-on development is the essential bridge.
The current Azure AI Fundamentals path.
A current Microsoft role-based AI engineering path, not the retired AI-102 exam.
Start with current fundamentals unless you already build software and Azure AI solutions.
Current Azure AI Fundamentals -> Python or C# and REST practice -> current Microsoft AI engineering credential.
Exam versions, eligibility, delivery, and renewal policies can change after this comparison is published.
Candidate questions
Neither is universally better. Start with current fundamentals unless you already build software and Azure AI solutions.
The fundamentals path was commonly taken first, though it was never a formal prerequisite.
Foundational concepts support later implementation work, but hands-on development is the essential bridge.
Use beginner, intermediate, and advanced paths to plan the next step after either credential.