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 AB€‘100 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 solutions€”rather 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 agent€‘based and agent€‘orchestrated business solutions
• Architecting AI€‘powered business solutions using agents, copilots, and generative AI
• Designing agentic€‘first solution architectures aligned to business goals
• Applying architectural frameworks for AI€‘driven enterprise solutions
• Evaluating business use cases for agentic AI and generative AI
• Designing AI solutions that automate tasks and improve decision€‘making
• Integrating agentic AI solutions with Microsoft Dynamics 365, Power Platform, Microsoft Copilot, and AI services
• Designing multi€‘agent orchestration models and interaction patterns
• Applying governance, security, and responsible AI principles to agentic solutions
• Managing cost, value, and trade€‘off decisions for AI€‘powered architectures
• Designing lifecycle management strategies for agentic AI solutions
• Communicating architectural decisions and AI solution designs to business and technical stakeholders