3.4. Reflection Checkpoint
Key Takeaways
Before proceeding, ensure you can:
- Explain how Microsoft 365 Copilot uses Microsoft Graph to provide organizational context
- Distinguish between Microsoft Copilot (free) and Microsoft 365 Copilot (licensed)
- Describe Copilot Chat web/mobile experiences vs. in-app Copilot
- Explain how content safety and filtering controls protect AI interactions
- Identify when to use Copilot Studio versus standard M365 Copilot
- Describe the purpose of Researcher and Analyst agents
- Choose the right extensibility approach: Graph connectors, plugins, or custom agents
- Distinguish Security Copilot from M365 Copilot (audience, data sources, licensing)
- Explain when Microsoft Foundry is the appropriate choice
- Match Azure AI Services to developer use cases
Connecting Forward
In Phase 4, you'll learn how to implement AI responsibly and drive adoption—ensuring that the AI capabilities you select actually deliver value. Technology selection is necessary but not sufficient; responsible implementation and user adoption complete the picture.
Self-Check Questions
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A company uses the free Microsoft Copilot and wonders why it can't answer questions about their recent sales meeting. How would you explain this limitation and recommend a solution?
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An HR department wants a chatbot that answers employee questions about benefits, grounded on their benefits documentation. They're considering building it in Microsoft Foundry. What would you advise?
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Your development team needs to add automatic invoice data extraction to a custom application. Would you recommend Microsoft 365 Copilot, Copilot Studio, or Azure AI Services? Which specific service?
