AI-103 Exam Overview: Developing AI Apps and Agents on Azure

AI-103 measures practical Azure AI implementation knowledge. Candidates need to understand planning and managing Azure AI solutions, building generative AI and agentic solutions, using computer vision, and implementing information extraction. The exam language emphasizes Azure AI Foundry, Azure OpenAI, Azure AI Search, Azure AI Vision, and Azure AI Document Intelligence.

Microsoft lists four current skill areas for AI-103: plan and manage an Azure AI solution, implement generative AI and agentic solutions, implement computer vision solutions, and implement information extraction solutions. Keep those names consistent across your study notes so you do not mix AI-103 with older Azure AI engineering material.

The exam fits candidates who can work with Azure services, read and write code, understand APIs, and reason about AI application behavior. Useful background includes Python or C#, prompt engineering basics, responsible AI concepts, search and retrieval design, and the ability to troubleshoot model, data, and access issues.

Preparation should focus on service selection and implementation tradeoffs. Know when to use vector search, how grounding improves generative responses, why content filtering matters, how agent tools extend workflows, and how Document Intelligence and Vision solve different extraction problems. Avoid relying on invented question counts or unofficial structure claims.