AI-102 Is Retired: What Changed in AI-103
AI-103 is not an AI-102 question bank with a new code. It moves the centre of gravity toward Microsoft Foundry, generative applications, RAG, and agents.
The short answer
Microsoft retired AI-102 on June 30, 2026. AI-103 is the current associate certification for developers building Azure AI applications and agents. Your knowledge of Azure AI services still matters, but a study plan that ignores Foundry projects, RAG, agents, evaluation, and operational controls is incomplete.
Check the dates in the official retirement list and use the official AI-103 study guide as the source of truth.
What changed in practical terms
| Preparation area | What to do for AI-103 |
|---|---|
| Azure AI platform | Understand Foundry resources, projects, connections, deployments, identity, networking, quotas, and monitoring as one operating environment. |
| Generative AI | Move beyond prompt basics into model selection, RAG design, grounding, structured outputs, evaluation, safety, and observability. |
| Agents | Practice tools, instructions, memory, orchestration, multi-agent decisions, identity, tracing, and responsible operation. |
| Applied AI services | Keep vision, language, speech, and information extraction, but learn to choose and integrate them inside modern solutions. |
| Question practice | Prioritise scenario reasoning and current documentation. Treat material that only renames AI-102 as suspect. |
What still carries over
- Choosing the right Azure AI capability for a requirement.
- Authentication, managed identity, role-based access, private networking, and responsible AI.
- Computer vision, language, speech, document processing, and search fundamentals.
- Reading Python, REST, JSON, and configuration in scenario questions.
- Explaining trade-offs instead of memorising product names.
Do not throw away sound AI-102 knowledge. Reframe it inside the AI-103 architecture and verify every renamed service, portal workflow, SDK, role, and API against current Microsoft documentation.
Where to spend the extra study time
The largest AI-103 domain is Implement generative AI and agentic solutions at 30–35%. Plan and manage an Azure AI solution contributes another 25–30%. Together, those two areas can represent more than half of the measured skills.
- Build one Foundry project and be able to explain every connection and identity.
- Implement a small RAG flow and justify chunking, retrieval, grounding, and evaluation choices.
- Build an agent with at least one tool, then trace and evaluate its behaviour.
- Review vision, text analysis, and information extraction as solution-selection scenarios.
- Run timed practice and use wrong answers to build a targeted revision list.
Turn the transition into a baseline
Use ten original scenarios to see whether your current AI-102 knowledge transfers to the new blueprint.
Start the free AI-103 diagnosticNext step
Continue with the 30-day AI-103 study plan, or review the complete AI-103 practice exam overview.