Who is this training for?
This course is suitable for:
- 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
An active Microsoft Associate‑level certification with experience architecting AI‑powered business solutions across Microsoft business applications and AI services.
Training objectives
- Analyze business requirements and identify suitable agentic AI use cases that align with organizational goals and measurable business outcomes.
- Design end to end AI powered business solutions using agents, copilots, and generative AI across Microsoft platforms such as Copilot Studio, Power Platform, Dynamics 365, and Azure AI.
- Architect multi agent and orchestrated AI solutions that integrate data, applications, and services securely and at enterprise scale.
- Evaluate architectural trade offs, costs, and ROI when selecting AI technologies and deployment approaches for business solutions.
- Apply governance, security, and responsible AI principles to ensure AI solutions are compliant, ethical, and production ready.
- Plan deployment, monitoring, and lifecycle management for agentic AI solutions, including testing, ALM, and continuous optimization
Summary
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.
Course outline
Module 1 : Introduction to agentic AI business solutions
- 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 2:Analyze requirements for AI-powered business solutions
- Assess the use of agents in task automation, data analytics, and decision-making
- Review data for grounding accuracy, relevance, timeliness, cleanliness, and availability
- Organize business solution data for AI systems
Module 3: Evaluate costs and benefits of AI solutions
- Evaluate ROI criteria for AI-powered solutions
- Create ROI analysis for a proposed AI solution
- Analyze whether to build, buy, or extend AI components
- Implement a model router to intelligently route requests to the most suitable model
Module 4: Manage testing AI-powered business solutions
- 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 5: Design extensibility of AI solutions
- Design AI solutions with custom models in Microsoft Foundry
- Design agents in Microsoft 365 Copilot
- Design extensible agents in Microsoft Copilot Studio
- Design extensible agents using MCP in Copilot Studio
- Design agents to automate tasks in apps and websites with Computer Use in Copilot Studio
- Design agent behaviors in Copilot Studio
- Optimize solution design for agents in Microsoft 365
Module 6: Design responsible AI security, governance, risk management, and compliance
- Design security agents for Microsoft clouds
- Design governance models for AI agents
- Design model security for responsible AI
- Analyze AI vulnerabilities and mitigations for prompt manipulation
- Review solution adherence to Responsible AI principles
- Validate data residency and movement compliance
- Design access controls for grounding data and model tuning
- Design audit trails for changes to models and data
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