Building a Governance Framework for M365 Copilot in Government

Overview

Successful Copilot adoption in government requires more than just technical deployment—it demands comprehensive governance. This video walks through the essential components of a Copilot governance framework, from acceptable use policies to oversight structures to risk management processes.

Whether you’re establishing governance from scratch or enhancing existing AI policies, this guide provides practical frameworks you can adapt for your agency.

What You’ll Learn

• Policy Framework: Core policies needed for responsible Copilot adoption
• Acceptable Use Standards: What employees can and cannot do with Copilot
• Oversight Structure: Committees, roles, and decision-making authority
• Risk Management: Identifying and mitigating AI-related risks
• Monitoring & Compliance: Ensuring policies are followed and effective

Transcript

[00:00 - Introduction]

Welcome everyone. I’m Kevin Tupper, and today we’re tackling one of the most critical aspects of Copilot adoption: governance. Technology is the easy part. The hard part is establishing the policies, oversight, and cultural norms that ensure AI is used responsibly and effectively in your agency.

[00:45 - Why Governance Matters]

Governance isn’t bureaucracy for its own sake. It’s how you ensure that Copilot delivers value while managing risk. Without governance, you’ll see inconsistent usage, potential security incidents, and difficulty demonstrating responsible AI stewardship to oversight bodies.

Good governance enables innovation by providing clear guardrails and decision-making frameworks.

[02:00 - Core Components of a Governance Framework]

A comprehensive Copilot governance framework has five core components:

One: Acceptable Use Policies defining how employees should and shouldn’t use Copilot. Two: Oversight Structure establishing who makes decisions about AI adoption. Three: Risk Management processes for identifying and mitigating AI-related risks. Four: Monitoring and Compliance mechanisms to ensure policies are followed. Five: Continuous Improvement processes to evolve governance as you learn.

Let’s examine each component.

[03:30 - Acceptable Use Policies]

Your acceptable use policy should clearly define:

Approved use cases: what tasks Copilot can assist with. Prohibited uses: activities that are off-limits regardless of technical capability. Data handling: how to handle different classifications of data. Prompt engineering: guidance on writing effective and appropriate prompts. Output verification: requirement to review and validate AI-generated content.

Be specific. Don’t just say “use Copilot responsibly”—give concrete examples and scenarios.

[05:45 - Oversight Structure]

Establish clear decision-making authority for AI adoption. A typical structure includes:

AI Governance Committee: Senior leaders who set strategic direction and policy. Technical Working Group: IT and security staff who handle implementation details. User Champions Network: Representatives from different departments who provide feedback. Privacy and Legal Review: Counsel who ensure compliance with privacy laws and regulations.

Define escalation paths for decisions and incident response.

[07:30 - Risk Management]

Identify risks specific to AI and your mission context:

Data exposure: Risk of sensitive information appearing in AI suggestions. Bias and fairness: Potential for AI outputs to reflect or amplify biases. Over-reliance: Users accepting AI suggestions without appropriate verification. Operational security: AI revealing information about operations, capabilities, or intentions.

For each risk, define likelihood, impact, and mitigation controls.

[09:15 - Monitoring and Compliance]

Governance without monitoring is just documentation. Implement:

Usage analytics: Track who’s using Copilot, how often, and for what purposes. Security monitoring: Alert on unusual patterns or potential policy violations. User surveys: Gather feedback on governance effectiveness and pain points. Periodic audits: Review compliance with acceptable use policies. Incident tracking: Document and learn from AI-related issues.

[11:00 - Continuous Improvement]

Your initial governance framework won’t be perfect. Plan for evolution:

Quarterly policy reviews based on usage data and feedback. Annual comprehensive assessment of governance effectiveness. Regular training updates incorporating lessons learned. Governance roadmap aligning with broader AI adoption maturity.

[12:15 - Getting Started]

If you’re starting from zero, focus on these priority actions:

One: Draft acceptable use policy with concrete examples. Two: Establish AI governance committee with executive sponsorship. Three: Implement basic monitoring using M365 audit logs. Four: Conduct initial risk assessment with security and legal teams. Five: Launch pilot with governance framework and iterate based on lessons learned.

[13:00 - Conclusion]

Governance enables innovation. By establishing clear policies, oversight, and risk management from day one, you set your agency up for successful, responsible AI adoption. Download our governance policy template linked below to jumpstart your framework development.