This page provides role-based action plans and key takeaways from the Microsoft AI Decision Framework.

Table of contents

  1. Key Takeaways
  2. Stay current: Capabilities evolving rapidly, especially in preview
  3. Role-Based Next Steps
  4. Official Microsoft Documentation
  5. Communities & Learning
  6. Stay Current

Key Takeaways

Resources & Next Steps

  1. Start with user experience: Where users interact drives technology choice
  2. Choose simplest tool that meets requirements: Developers can use low-code or pro-code; makers limited to low-code; let complexity and time-to-market decide
  3. Match governance approach to your needs: M365 tenant-integrated (ready to use, fast) vs Azure workload-tailored (precise control for specific requirements)
  4. Plan for scale: Start simple, architect for growth
  5. Leverage integration: Technologies work together, not in isolation
  6. Prioritize governance: Especially for Microsoft 365 Copilot extensions and custom agents; keep agent inventory current via Agent Registry/Agent 365
  7. Adopt staged security blueprints: Use Microsoft Purview deployment models to secure agent data and interactions
  8. Think beyond agents: Connectors, plugins, and extensibility matter
  9. Budget appropriately: Understand per-user vs. consumption models
  10. Iterate and learn: Start small, measure, expand

  11. Stay current: Capabilities evolving rapidly, especially in preview

Role-Based Next Steps

For Architects & Technical Decision Makers

  1. Review this decision tree with stakeholders
  2. Map your requirements to the six decision questions
  3. Identify pilot scenarios for chosen technologies
  4. Plan proof of concept with clear success criteria
  5. Consider governance and compliance early

Key Resources:

For Developers

  1. Explore Azure AI Foundry portal and samples
  2. Install M365 Agents SDK Toolkit in VS Code
  3. Review Agent Framework documentation
  4. Experiment with prompt engineering
  5. Understand evaluation frameworks

Key Resources:

For Makers & Business Users

  1. Request Copilot Studio access from IT
  2. Complete Copilot Studio learning paths
  3. Identify high-value automation candidates
  4. Start with templates and pre-built components
  5. Collaborate with IT on governance

Key Resources:

For IT Admins

  1. Review M365 Copilot admin capabilities
  2. Understand agent approval workflows
  3. Configure Integrated Apps settings
  4. Plan connector governance
  5. Implement monitoring and usage tracking

Key Resources:

Official Microsoft Documentation

Core Platforms

SDKs & Frameworks

Data & Grounding

Communities & Learning

Microsoft Tech Community

Learning Paths

GitHub Repositories

Stay Current

Microsoft’s AI landscape evolves rapidly. To stay informed:

  1. Follow Official Blogs:
  2. Monitor Product Updates:
  3. Join Events:
  4. Re-Verify This Decision Tree:
    • Product names and capabilities change frequently
    • Preview features may reach GA or be deprecated
    • New technologies are announced regularly
    • Re-research every 3-6 months for active projects

Framework Maintenance

This decision tree represents a point-in-time snapshot of Microsoft’s AI portfolio. For the methodology used to research and maintain this content, see the Core Methodology documentation.

Next: Glossary - Definitions that keep discussions precise across teams

Back to top

Copyright © 2025. This documentation is based on official Microsoft sources and best practices.