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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. |
Audience | 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
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| | An active Microsoft Associate‑level certification with experience architecting AI‑powered business solutions across Microsoft business applications and AI services. |
Objectives | By the end of this course, learners will be able to: - 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
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Teaching method | Training led by a Microsoft Certified Trainer. |
Contents | 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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