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.
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.
This course is intended for experienced technology professionals who are responsible for planning, designing, and guiding AI-powered business solutions using Microsoft platforms. This course assumes familiarity with Microsoft business applications, cloud concepts, and solution architecture fundamentals. 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.
Important Note: While this course aligns conceptually with many of the AB‑100 exam skill areas, it is not a test-preparation course and does not focus on test-taking strategies. Instead, it provides the architectural foundations, enterprise context, and design reasoning that make AB‑100 learning meaningful and applicable. For many learners, this course serves as a recommended preparatory step before beginning focused AB‑100 exam study. The ideal audience includes:
- Solution Architects and Enterprise Architects designing intelligent and agent-based business solutions
- Senior Functional and Technical Consultants working with Dynamics 365, Microsoft 365, Power Platform, or Azure AI services
- AI and Digital Transformation Leads defining AI strategy, governance, and adoption across the organization
- Application Architects and Technical Leads integrating agents, copilots, and generative AI into enterprise workloads
- Experienced practitioners preparing to advance toward formal AI solution validation, seeking architectural depth rather than exam-focused instruction
By the end of the course, participants should be able to:
- Align AI with Business Strategy: Analyze business processes and technical requirements to design an enterprise-wide AI strategy using the Azure Cloud Adoption Framework.
- Architect Multi-Agent Systems: Plan, prototype, and build agentic-first, multi-agent orchestrated solutions across Microsoft platforms including Copilot Studio, Microsoft Foundry, and Dynamics 365.
- Evaluate ROI and Financial Trade-Offs: Perform total cost of ownership (TCO) and return on investment (ROI) analyses to make informed "build, buy, or extend" decisions, incorporating intelligent model routing strategies to manage costs.
- Extend & Customize Enterprise AI: Design scalable architectures that extend Microsoft 365 Copilot and Dynamics 365 through custom connectors, knowledge sources, and customized Small Language Models (SLMs).
- Establish Governance and Security Frameworks: Implement secure cloud environments, data residency controls, and audit trails while defending against modern vulnerabilities like prompt manipulation in line with Microsoft’s Responsible AI principles.
- Manage AI Application Lifecycle (ALM): Structure Application Lifecycle Management processes to maintain consistency, versioning, and environment governance for AI data, models, and agents.
- Implement Advanced Monitoring and Tuning: Architect enterprise monitoring strategies to track agent performance, analyze user feedback logs, and interpret telemetry data for continuous model optimization.
- Govern Quality Assurance and Testing: Standardize validation criteria for custom AI models, validate effective prompt engineering libraries, and design end-to-end multi-application test cases using automated frameworks.
Module 01: Introduction to agentic AI business solutions
Learn to align AI solutions with business goals and scale AI adoption using Microsoft technologies.
Topics:
- Drive AI transformation with architect strategies
- Explore Microsoft AI technologies for business
- Identify Microsoft AI technologies for business solutions
- Identify out-of-box Microsoft AI agent resources for business solutions
- Identify out-of-box Microsoft AI agents for business
Module 02: Analyze requirements for AI-powered business solutions
Learn to analyze, design, and implement AI-powered business solutions using agents, generative AI, and Microsoft Copilot for productivity.
Topics:
- Analyze, design, and implement AI-powered business solutions
- Align agent capabilities with business requirements
- Leverage generative AI and Microsoft Copilot for productivity
Module 03: Design overall AI strategy for business solutions
Learn to design an enterprise AI strategy using Azure's Cloud Adoption Framework, aligning AI agent lifecycle with business goals for operational excellence.
Topics:
- Enterprise AI strategy using Azure's Cloud Adoption Framework
- Align AI agent lifecycle with business goals
- Drive operational excellence through AI adoption
Module 04: Evaluate costs and benefits of AI solutions
Learn to assess costs, benefits, and ROI of AI solutions while deciding whether to build, buy, or extend AI components for business processes.
Topics:
- Assess costs, benefits, and ROI of AI solutions
- Evaluate build vs. buy vs. extend decisions
- Integrate AI components into business processes
Module 05: Design AI agents for business solutions
Learn to design AI agents tailored to business needs using Dynamics 365 and Copilot.
Topics:
- Tailor AI agents to business needs
- Leverage Dynamics 365 for agent design
- Implement Copilot features in agent solutions
Module 06: Design extensibility of AI solutions
Learn to design scalable, secure, and customizable AI solutions using Microsoft platforms.
Topics:
- Scalable and customizable AI solution design
- Implement security across Microsoft platforms
- Extend AI solutions for enterprise needs
Module 07: Orchestrate configuration of prebuilt agents and apps
Learn to orchestrate, configure, and extend AI-driven experiences in Dynamics 365 and Microsoft 365 Copilot.
Topics:
- Orchestrate and configure prebuilt agents
- Extend AI-driven experiences in Dynamics 365
- Maximize Microsoft 365 Copilot application
Module 08: Monitor, analyze, and tune AI agents
Learn to ensure AI agents operate reliably, deliver high-quality outcomes, and continuously improve in enterprise environments.
Topics:
- Ensure reliable AI agent operations
- Deliver high-quality business outcomes
- Continuous improvement methods for enterprise AI
Module 09: Manage testing AI-powered business solutions
Learn to validate and maintain AI-powered business solutions with structured testing frameworks, metrics, and governance.
Topics:
- Recommend process metrics for testing AI agents
- Create validation criteria for custom AI models
- Validate effective Copilot prompt best practices
- Design end-to-end test scenarios for AI solutions using multiple Dynamics 365 apps
- Build a strategy for creating test cases using Copilot
Module 10: Design ALM process for AI-powered business solutions
Learn to design ALM processes for AI solutions, ensuring governance, security, and consistency across environments.
Topics:
- Design Application Lifecycle Management (ALM) for AI
- Establish governance and security controls
- Maintain solution consistency across environments
Module 11: Design responsible AI security, governance, risk management, and compliance
Learn to design secure, governed, and compliant AI systems that align with organizational policies and Responsible AI principles.
Topics:
- Secure and governed AI system design
- Risk management and compliance framework alignment
- Implement Responsible AI principles within organizational policies
