Architecting agentic AI business solutions is an advanced course for architects, senior consultants, and technical leaders responsible for planning, designing, and governing AI-powered enterprise solutions built on Microsoft platforms. This course serves as a foundational, real-world, and architectural preparation step that builds the design judgment, strategic reasoning, and end-to-end understanding learners need before pursuing the AB100 exam or implementing agentic AI solutions at scale.

This course is intended for experienced technology professionals who are responsible for planning, designing, and guiding AI-powered business solutions using Microsoft platforms. It is best suited for learners who want to deepen their architectural judgment, design decision-making, and enterprise readiness for agentic AI solutionsrather than those seeking step-by-step configuration guidance or exam preparation.

This course assumes familiarity with Microsoft business applications, cloud concepts, and solution architecture fundamentals.

Learners will explore how to architect AI-powered business solutions that use agents, copilots, and generative AI to automate tasks, improve decision-making, and enhance employee and customer experiences. Emphasis is placed on architecture, trade-offs, governance, cost/benefit analysis, and lifecycle management, rather than step-by-step configuration.

• Introduction to agentic AI and autonomous agent architectures
• Understanding agentbased and agentorchestrated business solutions
• Architecting AIpowered business solutions using agents, copilots, and generative AI
• Designing agenticfirst solution architectures aligned to business goals
• Applying architectural frameworks for AIdriven enterprise solutions
• Evaluating business use cases for agentic AI and generative AI
• Designing AI solutions that automate tasks and improve decisionmaking
• Integrating agentic AI solutions with Microsoft Dynamics 365, Power Platform, Microsoft Copilot, and AI services
• Designing multiagent orchestration models and interaction patterns
• Applying governance, security, and responsible AI principles to agentic solutions
• Managing cost, value, and tradeoff decisions for AIpowered architectures
• Designing lifecycle management strategies for agentic AI solutions
• Communicating architectural decisions and AI solution designs to business and technical stakeholders