Get Your Tenant Ready for AI and the Power Platform
The Copilot and Power Platform Administration and Governance Workshop is the most effective way to train your team to be fully capable on implementing and maintaining your Power Platform environment properly and AI in M365 Copilot.
Who Should Attend
This class is designed for:
- Power Platform Administrators
- Microsoft 365 / Entra ID Administrators
- Security and Compliance Administrators
- IT Operations and Cloud Platform Teams
- Center of Excellence (CoE) leads
- AI governance and risk teams
- Solution Architects responsible for Power Platform or Copilot
Why They Should Attend
Attendees will walk away with:
- A clear administrative operating model for Power Platform and AI
- Confidence in securing environments, data, and AI experiences
- Practical guidance to avoid accidental data exposure
- A framework to prepare their tenant for Copilot and AI safely
- A shared language to align IT, security, and AI teams
- Reduced risk around shadow IT, oversharing, and prompt abuse
Event Details
This hands-on workshop is designed to prepare administrators and architects to securely govern and scale Microsoft Copilot and the Power Platform. You’ll learn practical strategies for managing environments, deploying solutions, securing data and access, and implementing governance controls across apps, agents, flows, and AI experiences. The session also covers tenant readiness for AI, risk mitigation (including oversharing and prompt attacks), and core Microsoft Purview capabilities such as labeling, DLP, auditing, and monitoring to ensure a secure and compliant deployment.
Power Platform Strategies
Goal: Establish a scalable, governable foundation before users build anything.
Topics:
- Understanding the types of Power Platform workloads
- Canvas apps vs model-driven apps
- Power Automate cloud flows vs desktop flows
- Copilot Studio agents and AI-powered workloads
- Deciding what belongs where
- Business-led vs IT-led solutions
- Personal productivity vs enterprise apps
- Environment strategy
- Default environment pitfalls
- Dedicated dev, test, prod patterns
- Environment per department vs per solution
- Managed Environments
- When to enable them
- What controls they actually enforce
- How they support scale and governance
- Aligning strategy with licensing, security, and support models
Key outcome: Admins can explain and justify their Power Platform structure.
Power Platform Lifecycle
Goal: Move from manual exports to repeatable, auditable deployments.
Topics:
- Solution fundamentals
- Managed vs unmanaged solutions
- What should and should not go into solutions
- Deployment patterns
- Dev to test to prod flow
- Supporting multiple teams and makers
- Pipelines in Power Platform
- What they automate
- Security implications
- Common failure scenarios
- Versioning, rollback, and ownership
Key outcome: A sane deployment story that survives audits and incidents.
Securing the Platform
Goal: Protect data without breaking the user experience.
Topics:
- Environment-level security
- Who can create apps, flows, and copilots
- Restricting connectors and capabilities
- Dataverse security model
- Business units overview
- Row-level security concepts
- Building and managing security roles
- Least-privilege role design
- Common over-permission mistakes
- Sharing apps and flows correctly
- Individual vs group sharing
- Ownership risks
- Automation misuse patterns
Key outcome: Admins can answer “who can see what and why.”
Prepare Your Tenant for AI
Goal: Avoid turning on AI blindly.
Topics:
- Key tenant-level settings that affect AI
- Copilot and AI service controls
- Data access boundaries
- Understanding AI scope
- What Copilot can and cannot see
- How permissions carry into AI responses
- Readiness checklist
- Identity, data, and compliance prerequisites
- Common mistakes organizations make before enabling Copilot
Key outcome: A controlled, intentional AI rollout plan.
Securing your resources for AI
Goal: Prevent AI from becoming a data exfiltration tool.
Topics:
- SharePoint and OneDrive oversharing risks
- How AI amplifies poor permissions
- Inherited access and legacy links
- Prompt injection and AI abuse
- What prompt attacks actually look like
- Where they show up in Power Platform and Copilot
- Guardrails for AI integrations
- Connector restrictions
- Input and output validation concepts
- Monitoring AI usage patterns
- Identifying risky behavior early
Key outcome: Reduced likelihood of AI-driven data leaks.
Enabling Governance with Purview for Power Platform and AI
Goal: Use Microsoft Purview as a control plane, not an afterthought.
Topics:
- Sensitivity labeling
- How labels impact AI and Power Platform
- Label inheritance and conflicts
- Data Loss Prevention (DLP)
- DLP for Power Platform connectors
- DLP considerations for AI scenarios
- Auditing and activity tracking
- What admins can and cannot see
- Key logs to monitor
- Monitoring AI usage
- Detecting misuse and policy violations
- Insider risk awareness
- Where AI increases internal risk
- Early warning indicators
Key outcome: Admins know how to prove control, not just claim it.
