Current AI-103 Exam Facts
Key Takeaways
- AI-103 is Microsoft's Develop AI Apps and Agents on Azure exam for the Azure AI Apps and Agents Developer Associate credential.
- Microsoft Learn lists the current skills measured as of April 16, 2026, with Plan and manage an Azure AI solution weighted 25-30%.
- The passing score is 700/1000, and Microsoft lists 120 minutes for the assessment on the certification page.
- Local metadata records the U.S. exam fee as US$165 while Microsoft notes that price depends on the country or region where the exam is proctored.
- Use Microsoft Learn, the local exam metadata, and the AI-103 cheat sheet together so duration, blueprint weights, and Foundry terminology stay aligned during future updates.
Current AI-103 Exam Facts
AI-103: Develop AI Apps and Agents on Azure validates whether an Azure AI engineer can plan, build, deploy, and operate AI apps and agents that use Microsoft Foundry. The official Microsoft Learn study guide calls the exam Developing AI Apps and Agents on Azure and says the candidate builds, manages, and deploys agents and AI solutions that take advantage of Microsoft Foundry. The credential page names the certification Microsoft Certified: Azure AI Apps and Agents Developer Associate and lists a 700 passing score.
Use the April 2026 blueprint as the study anchor. Microsoft Learn states that skills are measured as of April 16, 2026. That matters because older AI-102 habits do not fully map to AI-103: Foundry projects, agents, model deployments, retrieval, observability, and responsible AI controls are now first-class planning topics.
| Fact | Current working value | Source note | Study implication |
|---|---|---|---|
| Exam | AI-103 | Microsoft Learn and local metadata | Prepare for Foundry app and agent development, not a generic Azure AI survey |
| Passing score | 700/1000 | Microsoft Learn credential and study-guide support text | Treat 700 as a scaled score, not a raw percentage target |
| Duration | 120 minutes | Microsoft Learn credential page | Build enough stamina for scenario and interactive items |
| Questions | 40-60 typical | Local metadata | Practice mixed scenarios with time pressure |
| U.S. price | US$165 | Local metadata; Microsoft says price varies by country/region | Confirm price when scheduling through Pearson VUE |
| Blueprint date | April 16, 2026 | Microsoft Learn study guide | Prefer current Foundry terminology over retired service names |
Current Blueprint Weights
| Domain | Weight |
|---|---|
| Plan and manage an Azure AI solution | 25-30% |
| Implement generative AI and agentic solutions | 30-35% |
| Implement computer vision solutions | 10-15% |
| Implement text analysis solutions | 10-15% |
| Implement information extraction solutions | 10-15% |
The local metadata, AI-103 cheat sheet, and Microsoft Learn blueprint are now aligned on the April 16, 2026 weighting model: Plan and manage an Azure AI solution is 25-30%, and the credential page lists a 120-minute assessment window. Future updates should keep those files synchronized before new practice, flashcard, cheat sheet, or guide content is generated.
What This Means for Study Planning
- Spend the first review block on Foundry structure, identity, networking, deployments, content safety, monitoring, and evaluation.
- Do not separate agents from operations; the blueprint expects agent behavior to be governed, traced, evaluated, and constrained.
- Use local practice questions for coverage signals, but do not memorize wording or treat them as official exam items.
- Keep a source checklist: Microsoft Learn AI-103 study guide, the certification page, Foundry docs, Content Safety docs, and the local metadata files.
The safest final-week target is not just answering service-name questions. You should be able to explain why a team would choose a Foundry project, a hub-based project, a model deployment option, a private endpoint, a managed identity, or a continuous-evaluation signal in a realistic production scenario.
A team is updating AI-103 prep content after Microsoft publishes a newer skills outline. What is the best maintenance action?