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Official source
Microsoft AB-100 study guide
This on-site viewer mirrors the official Microsoft Learn AB-100 syllabus for quick review. Open the Microsoft Learn source when you need the full study guide, current details, and related certification resources.
Skills measured
- Plan AI-powered business solutions: 25-30%
- Design AI-powered business solutions: 25-30%
- Deploy AI-powered business solutions: 40-45%
Exam profile
- Role: Solution Architect
- Level: Advanced
- Subject: Artificial intelligence
- Current official study guide checked: Microsoft Learn, last updated 2026-01-06
Core preparation focus
- Agentic-first business process strategy and measurable outcomes
- Copilot Studio, Microsoft Foundry, Dynamics 365, Power Platform, Microsoft 365 agents, MCP, and open protocols
- Testing, ALM, responsible AI, security, governance, risk, compliance, monitoring, and continuous improvement
Plan subpoints
- Assess agent use for automation, analytics, and decision-making
- Review grounding data for accuracy, relevance, timeliness, cleanliness, and availability
- Design AI adoption, agent strategy, multi-agent solutions, prebuilt agents, constraints, knowledge sources, prompt libraries, prompt engineering, AI Center of Excellence, Dynamics 365 AI, ROI, build/buy/extend, and model routing
Design subpoints
- Design Dynamics 365 Copilot terms, customizations, connectors, contact-center agents, task agents, autonomous agents, prompt and response agents, topics, fallback, grounding, canvas-app AI components, and agent flows
- Use Microsoft Power Platform Well-Architected Framework decisions for intelligent workloads
- Design extensibility with Foundry custom models, Microsoft 365 Copilot agents, Copilot Studio, MCP, Computer Use, reasoning, voice mode, Teams, SharePoint, prebuilt agents, and Microsoft 365 Copilot for Sales and Service
Deploy subpoints
- Monitor agents, analyze backlog and feedback, use AI-based issue analysis, track performance metrics, and interpret telemetry for tuning
- Define agent test processes, validation criteria, prompt best-practice checks, end-to-end Dynamics 365 test scenarios, and Copilot-assisted test-case strategy
- Design ALM for AI data, Copilot Studio agents, connectors, actions, Foundry agents, custom models, Dynamics 365 finance and supply-chain AI, and customer experience/service AI
- Design security, governance, model protection, prompt-manipulation mitigation, responsible AI adherence, data residency, grounding access controls, model-tuning controls, and audit trails