Blog Post
AI-103 vs AI-200: Which Microsoft Azure AI Certification Should You Go For?
Microsoft launched two new Azure AI certifications in 2026 : AI-103 and AI-200. Here's a clear breakdown of what each one tests, who it's for, and how to decide which fits your role and career direction.
Microsoft's 2026 certification overhaul is one of the most significant reshuffles in years. Two new AI‑focused exams, AI‑103 and AI‑200, are at the center of the discussion. Both target developers. Both are new. From the outside, they look confusingly similar.
They're not. Choosing the wrong one means preparing for a credential that doesn't reflect what you actually do at work.
This post breaks down what each exam validates, who each is for, and how to decide cleanly.
Why These Exams Exist
AI‑103 has replaced AI‑102 (Azure AI Engineer Associate), which retired on June 30, 2026. AI‑200 replaces AZ‑204 (Azure Developer Associate), which also retired on the same date.
Microsoft's overhaul embeds AI competency directly into role‑based credentials rather than treating it as a separate track. The signal: Azure AI development is no longer a niche; it's now the baseline expectation for developers and engineers on the platform.
What AI‑103 Actually Tests
AI‑103 is the Microsoft Certified: Azure AI Apps and Agents Developer Associate. It focuses on generative AI, multimodal scenarios, agentic workflows, and responsible AI using Azure services and Microsoft Foundry.
The practical emphasis is on AI agents – autonomous systems that can plan, use tools, and take actions. Microsoft is investing heavily here through Copilot Studio, Microsoft Foundry, and the Semantic Kernel framework.
Core topics:
- Microsoft Foundry hub and project architecture
- Prompt engineering and RAG (retrieval‑augmented generation)
- Multi‑agent orchestration using Semantic Kernel and Copilot Studio
- Function calling and tool‑use capabilities
- Responsible AI safeguards and content filtering
- Production deployment of AI applications at scale
The shift from AI‑102: AI‑102 taught you how to use tools. AI‑103 teaches you how to build systems.
Who AI‑103 is for:
- Developers building generative AI apps and autonomous agents
- Engineers working with Azure OpenAI Service, Semantic Kernel, or Copilot Studio daily
- Professionals transitioning from AI‑102 who want forward‑looking credentials
What AI‑200 Actually Tests
AI‑200 is the Microsoft Certified: Azure AI Cloud Developer Associate. It validates the ability to build, integrate, and monitor AI solutions on Azure using containerized compute, vector‑enabled databases, event‑driven AI pipelines, serverless functions, and distributed observability.
Where AI‑103 focuses on the application/agent layer, AI‑200 focuses on the infrastructure those applications run on.
Core topics:
- Containerized solutions on Azure for AI workloads
- Event‑driven AI pipelines and serverless architectures
- Vector‑enabled databases and AI data management
- Secure, observable AI solution deployment
- Integration patterns between Azure AI services and enterprise applications
- Cost optimization for inference workloads
Who AI‑200 is for:
- Cloud developers and Azure engineers whose work spans the full infrastructure stack
- Full‑stack developers integrating AI into existing cloud applications
- Engineers responsible for deploying and monitoring AI solutions in production
- Professionals coming from AZ‑204 moving into AI‑powered cloud development
The Core Difference, Stated Plainly
- AI‑103 answers: Can you build intelligent applications and agents using Microsoft's AI development platform?
- AI‑200 answers: Can you architect and deploy the cloud infrastructure that AI solutions run on?
Neither is more advanced. They measure different dimensions of work.
A Practical Decision Framework
What does your current work involve most?
- Mostly Azure OpenAI Service, RAG pipelines, agent workflows, Microsoft Foundry → AI‑103
- Mostly containers, serverless functions, event‑driven architectures, observability → AI‑200
What roles are you targeting in 12‑18 months?
- AI engineer, agent developer, Copilot Studio developer → AI‑103
- Cloud developer, Azure engineer, full‑stack developer building AI‑integrated apps → AI‑200
Check real job postings. The certifications they mention are better signal than any guide.
What's your existing credential history?
Both exams together signal end‑to‑end Azure AI expertise. For most people, pick the one that matches your actual work first. The second can follow.
What Preparation Looks Like for Each
Because both exams are new, official practice assessments aren't yet available.
For AI‑103: Start with the Microsoft Learn path (AI‑103T00‑A). Beyond that, hands‑on work with Microsoft Foundry, Azure OpenAI Service, and Semantic Kernel is the most effective preparation.
For AI‑200: The AI‑200T00‑A course covers core infrastructure patterns. Supplement with hands‑on work involving AKS for AI workloads, Azure Functions with AI integrations, and Event Grid pipelines.
For both: Scenario‑based practice that forces you to apply concepts under realistic constraints builds the judgment the exams test. ExamOS has comprehensive coverage for 2026 Microsoft AI exam wave, you can start your practice today with mock exams for both AI-103 and AI-200.
The Bigger Picture
AI‑103 and AI‑200 reflect the same underlying shift: Microsoft is done treating AI as an add‑on to cloud development. These certifications validate real‑world, job‑ready skills for the AI‑powered workplace of 2026 and beyond.
The professionals who earn them early, while the job market is still calibrating, will have an advantage – not by rushing into an unprepared exam, but by making a deliberate choice, mapping their current skills to the right exam, and building toward it with consistency.
Preparing for AI‑103, AI‑200, or other new Microsoft certifications? Explore scenario‑based practice on ExamOS Azure Practice Exam Hub and build the daily habit that keeps your skills current as the certification landscape evolves.
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