- The Status Change Every Trainee Needs to Know
- Official Training: AI-103T00-A Replaces AI-102T00
- Exam Logistics That Shape Your Training Plan
- Domain-by-Domain Training Breakdown
- Who Should Actually Train for This Credential
- Building a Training Schedule Around the Domains
- Practice Tools and How to Use Them
- Frequently Asked Questions
- AI-102 and its Azure AI Engineer Associate credential retired June 30, 2026 at 11:59 PM Central.
- The live training path is Exam AI-103, taught through the four-day AI-103T00-A course.
- Implement generative AI and agentic solutions is the heaviest domain at 30-35% of the exam.
- The exam costs $165 USD, runs 120 minutes, and requires a scaled score of 700 to pass.
The Status Change Every Trainee Needs to Know
If you searched for "AI-102 training," you landed in the middle of a credential transition, and it matters for how you prepare. Exam AI-102, Designing and Implementing a Microsoft Azure AI Solution, along with Microsoft Certified: Azure AI Engineer Associate, retired on June 30, 2026 at 11:59 PM Central. The renewal assessment retired with it. That means the exam can no longer be scheduled, and the associate credential can no longer be earned or renewed by anyone who did not already hold it before the cutoff.
Anyone who certified before retirement keeps the credential listed in the Active Certifications section of their Microsoft Learn transcript until its printed expiration date, but there is no renewal path once it lapses. For everyone else, the relevant, learnable credential going forward is Exam AI-103, Developing AI Apps and Agents on Azure, which awards Microsoft Certified: Azure AI Apps and Agents Developer Associate. If you want the full backstory on how the numbering and naming changed, our AI-102 Certification overview and What Is AI-102? explainer both walk through it in detail.
Official Training: AI-103T00-A Replaces AI-102T00
At the instructor-led training level, Microsoft's four-day AI-103T00-A course has replaced the older AI-102T00 course. If a training provider, bootcamp, or corporate learning catalog still lists AI-102T00, that listing is stale and should be treated as a signal to double-check whether the rest of the curriculum has been updated. AI-103T00-A is built around the tools and services the current exam actually measures: Microsoft Foundry, Foundry Agent Service, Microsoft Agent Framework, Azure OpenAI in Foundry Models, Azure AI Search, Azure Content Understanding in Foundry Tools, Azure Document Intelligence in Foundry Tools, Azure Speech, and Azure Translator.
There are no formal prerequisites to sit the exam, but the audience profile Microsoft designs the training for assumes working app development experience in Python, plus general familiarity with AI concepts, generative AI patterns, and core Azure services. If you're unsure whether your background clears that bar, our AI-102 Requirements guide breaks down what "no prerequisites" actually means in practice.
Key Takeaway
Match any training material's vocabulary to the current toolset. If a course, video series, or book never mentions Foundry Agent Service or Microsoft Agent Framework, it's teaching the retired exam, not the live one.
Exam Logistics That Shape Your Training Plan
Training decisions - how much time to budget, when to schedule the exam, how many practice attempts to build in - depend on the mechanics of the exam itself. Here's what governs the current version:
| Factor | Detail |
|---|---|
| Delivery | Pearson VUE, at a test center or online proctored |
| Standard US price | $165 USD (varies by country/region) |
| Duration | 120 minutes, may include interactive item types |
| Passing score | 700 on a 100-1000 scale |
| Retake wait | 24 hours after a first fail, longer waits after that |
| Renewal | Free annual renewal via unproctored Microsoft Learn assessment |
Microsoft doesn't publish a fixed question count or a pass rate for this exam, so pacing your training around a specific number of "questions to master" isn't realistic. Instead, plan around the domain weightings and the 120-minute clock. For a deeper breakdown of the exact scoring mechanics, see AI-102 Passing Score 2026: Exactly What You Need to Pass, and for the full cost picture including retake fees and renewal, check AI-102 Certification Cost 2026: Complete Pricing Breakdown.
Domain-by-Domain Training Breakdown
Training time should be allocated in rough proportion to exam weight, not evenly across all five domains. Here's how the current outline breaks down, and what to focus training hours on inside each one.
Domain 1: Plan and manage an Azure AI solution (25-30%)
Covers provisioning and securing Azure AI resources, managing cost and monitoring, and understanding responsible AI controls at a solution level.
- Resource provisioning, keys, and endpoint management
- Monitoring, logging, and cost governance for AI workloads
Domain 2: Implement generative AI and agentic solutions (30-35%)
The largest domain by far, and the one that most distinguishes the current exam from its predecessor. Training here should be non-negotiable priority.
- RAG implementation patterns and grounding data
- Multi-agent orchestration and function calling with tool schemas
- Conversation memory, agent evaluation, and error analysis
- Tracing, token analytics, and autonomous workflows with approval controls
Domain 3: Implement computer vision solutions (10-15%)
Focuses on image analysis, object detection, and vision-enabled Foundry Tools workflows.
- Image analysis and tagging pipelines
- Vision integration inside broader AI app solutions
Domain 4: Implement text analysis solutions (10-15%)
Covers language understanding, sentiment, and key phrase extraction as building blocks for text-driven apps.
- Text classification and sentiment scoring
- Language detection and entity recognition
Domain 5: Implement information extraction solutions (10-15%)
Centers on Azure Document Intelligence in Foundry Tools and Azure Content Understanding in Foundry Tools for structured extraction from unstructured input.
- Document field extraction and prebuilt vs. custom models
- Content Understanding pipelines for mixed-format input
For a complete narrative walkthrough of all five areas with more subtopics, our AI-102 Exam Domains 2026: Complete Guide to All 5 Content Areas article is the natural companion to this one. And if you're trying to gauge overall difficulty before committing training hours, How Hard Is the AI-102 Exam? Complete Difficulty Guide 2026 covers where candidates typically struggle.
Who Should Actually Train for This Credential
The training audience Microsoft designs AI-103T00-A for is developers, not data scientists in the classic sense. Expect the exam and courseware to assume you can already write application code - Python is the assumed language - and that you're comfortable calling APIs, handling authentication, and reading service documentation. What you're being trained on top of that baseline is how to wire Azure AI services, Foundry-based agent tooling, and generative AI patterns into real applications.
Typical roles pursuing this training include application developers adding AI features to existing products, cloud engineers standing up agent-based automation, and solution architects who need hands-on fluency with Foundry Agent Service and Microsoft Agent Framework rather than a purely theoretical understanding. If you're evaluating whether this training investment pays off for your specific role, Is the AI-102 Certification Worth It? Complete ROI Analysis 2026 and AI-102 Jobs both dig into the hiring angle, and AI-102 Salary Guide 2026: Complete Earnings Analysis covers compensation considerations.
Key Takeaway
If your daily work doesn't touch application code, prioritize training on Domain 2's agent and generative AI concepts first - they carry the most exam weight and the steepest new-material learning curve for non-developers.
Building a Training Schedule Around the Domains
Generic study techniques like spaced repetition or timed review blocks only help if they're pointed at the right material in the right order. Below is one reasonable way to sequence a training plan against the actual domain weights rather than treating all five areas equally.
Foundations and Domain 1
- Provision Azure AI resources hands-on; practice key/endpoint management
- Review monitoring, cost controls, and responsible AI guardrails
Domain 2 deep work
- Build a small RAG pipeline against Azure AI Search
- Implement function calling, tool schemas, and a basic multi-agent flow in Foundry Agent Service
- Practice tracing, token analytics review, and approval-gated workflows
Domains 3 and 4
- Run image analysis exercises and compare prebuilt vs. custom vision models
- Work through text analysis tasks: sentiment, entities, key phrases
Domain 5 and integration review
- Practice Document Intelligence extraction on varied document types
- Test Content Understanding pipelines on mixed-format input
Timed practice and gap closing
- Run full-length timed practice sessions within the 120-minute limit
- Revisit weak domains identified during practice
For a more detailed week-by-week methodology with additional variations, see our dedicated AI-102 Study Guide 2026: How to Pass on Your First Attempt.
Practice Tools and How to Use Them
Reading documentation is necessary but not sufficient - this exam includes interactive components, and hands-on familiarity with Foundry tooling closes the gap that reading alone leaves open. Pair conceptual review with realistic scenario practice, then use timed practice tests to confirm your pacing across all five domains under exam-length pressure. You can run full-length, domain-weighted practice sessions on our practice test platform, which is built specifically around the current AI-103 outline rather than legacy AI-102 content.
Before your first real attempt, use practice exams to identify which domain is actually costing you the most points - for most candidates it's Domain 2, simply because agentic orchestration and RAG patterns are newer material than the vision and text analysis domains most developers already have some exposure to. If you want a compact reference to sanity-check facts the night before your exam, our AI-102 Cheat Sheet 2026: One-Page Review of Must-Know Facts is designed exactly for that, and a final practice run the day before is a reasonable last step in any training plan.
Frequently Asked Questions
The AI-102 exam and its Azure AI Engineer Associate credential retired June 30, 2026 at 11:59 PM Central and can no longer be earned. Current training should target AI-103 instead, which measures skills current as of April 16, 2026.
The four-day AI-103T00-A course replaced AI-102T00 at the instructor-led training level, covering Foundry, Foundry Agent Service, Microsoft Agent Framework, and the other tools now measured on the exam.
No formal prerequisites exist. Microsoft's assumed audience has Python app development experience plus general familiarity with AI, generative AI, and Azure services.
The exam runs 120 minutes and may include interactive item types. You need a scaled score of 700 out of a 100-1000 range to pass.
Implement generative AI and agentic solutions, at 30-35% of the exam, is the heaviest domain and covers RAG, multi-agent orchestration, function calling, and agent evaluation.