The Hidden Risks of Copilot Studio Agents – and How to Govern Them Responsibly

This piece was originally published on the AvePoint Blog

Microsoft Copilot Studio Agents are quickly becoming an essential part of the modern workplace. These AI-powered tools can retrieve information, automate processes, and take action across business systems, making them a powerful asset for teams looking to work smarter and faster.

Forward-thinking organizations are already building the infrastructure to support this shift toward agentic AI. Some are even exploring new roles like “AI workforce manager” to help manage the growing collaboration between people and intelligent systems.

But as agents take on more responsibility, the conversation is shifting from what they can do to how we can ensure they’re operating safely, responsibly, and in alignment with business goals.  

Understanding Agentic AI Risks

As organizations begin to scale agent use, risk management becomes part of the equation. The goal isn’t to slow progress, but to ensure innovation happens with guardrails in place. Good governance enables teams to move fast without compromising security, compliance, or cost.  

Here are some of the most common risks to be aware of as you implement Copilot Studio agents: 

Data Exposure

Agents that connect to enterprise systems can expose sensitive information if permissions aren’t configured correctly. Some common scenarios include: 

• Over-permissioned connections: Agents connect to a data source using service accounts with broader access than necessary.
• Improper impersonation: Agents act with the creator’s permissions rather than the current user’s, bypassing intended access controls.
• No filtering or row-level security (RLS): Agents surface entire data sets instead of applying filters based on user roles or policies.
• Uncontrolled data flows: Business users unintentionally connect managed and unmanaged systems, such as syncing OneDrive with Box. 

Compliance Violations

If agents process or share regulated data without the right controls, you could inadvertently breach industry regulations or privacy laws. Examples include: 

• Handling PII, PHI, or financial data without appropriate safeguards for standards like GDPR, HIPAA, or SOX.
• Failing to capture user content when collecting personal information.
• Operating without audit logging, making it difficult to trace who accessed what data – and when.  

Cost Containment

Agent usage can lead to unexpected costs if not carefully planned. While Copilot Studio offers flexible licensing models – including messaging packs and pay-as-you-go options – understanding how agents will be used is key to budgeting effectively.  

Message packs work well for agents with stable, predictable usage. Pay-as-you-go, however, can be more cost-effective for seasonal or experimental use cases.  

To estimate costs, consider:

• How often users will engage with the agent
• Whether conversations will be short or include open-ended dialogue
• If users will perform courtesy interactions like greetings or thank-yous (yes, those count as messages) 

The best approach is to monitor usage patterns early, then refine your licensing model as needs evolve.

Agent Sprawl

As more users create agents, it becomes harder to keep track of what exists – and who’s responsible for maintaining it. Some common challenges include: 

• Duplicate agents built for the same purpose in different departments, each with inconsistent logic or branding
• Orphaned agents left active after the creator leaves or shifts roles
• Unreviewed connections to sensitive systems like HR or finance, created without IT involvement
• Inconsistent experiences that erode trust in enterprise AI, such as different personalities, naming conventions, or user flows across departments 

What Good Governance Looks Like

Agents aren’t just another tool. They’re digital endpoints with the ability to act – sometimes independently – on behalf of your users and your brand. That makes governance not just a technical consideration, but a strategic imperative.  

Managing these risks starts with visibility. You need to understand which agents exist in your environment, who built them, and how they’re being used.  

From there, a solid governance approach should include thoughtful policies around: 

• Who can build and manage agents
• What types of agents are allowed (knowledge, task, autonomous)
• Where agents can be deployed (Teams, Copilot, internal apps, public endpoints)
• Why an agent is chosen over other technical solutions
• How you'll monitor, support, and retire agents over time

These questions provide the foundation for balancing flexibility with control. When implemented thoughtfully, governance provides the foundation to scale Copilot Studio Agents safely, without losing sight of why they were built in the first place: to drive better outcomes faster.

Laying the Groundwork for Secure Agent Adoption

Even as agent-specific governance features continue to evolve, many foundational tools already exist within the Microsoft ecosystem – especially through Power Platform. These give organizations a starting point to manage Copilot Studio Agents in a structured, sustainable way.  

Here’s what you can focus on to put the right controls in place: 

• Environment Strategy: Create structured, secure spaces for agent development. Separate environments by purpose (personal, team, production) to reduce risk and make it easier to manage access and lifecycle.
• Data Loss Prevention (DLP) Policies: Enforce connector restrictions to prevent agents from moving sensitive data between unmanaged systems or exposing confidential content in unintended ways.
• Monitoring and Insights: Use platform analytics to track usage patterns, identify high-risk agents, and flag unusual activity that may indicate compliance or security issues.
• Admin Controls: Apply tenant-wide guardrails that govern where agents can be published, what data they can access, and which connectors are approved.  

These are the foundational building blocks that allow you to support responsible agent development without stifling innovation. As AI adoption grows, however, organizations should plan to scale their governance strategy in parallel, thinking beyond policies and settings to include automation, ownership, and long-term lifecycle planning.  

Some key areas to focus on going forward include:

• Agent ownership and business context: Require makers to document the purpose, data sources, and intended outcomes of each agent. This ensures alignment with business priorities and provides critical context for review and support.
• Cost containment and forecasting: Monitor message volume and resource usage. Use this data to refine licensing strategies, allocate budget, and flag agents that exceed expected thresholds.
• Sprawl management: Build processes to decommission unused or duplicate agents and prevent redundant development across departments.
• Governance automation: Leverage tools that automatically apply policies, track changes, and generate audit logs as agents are created, modified, or published. This reduces manual oversight and increases consistency. 

By approaching governance as an evolving discipline – grounded in visibility, reinforced by policy, and supported by automation – you can unlock the full potential of Copilot Studio Agents while protecting your organization’s data, reputation, and bottom line.  

Looking to move fast – without losing control? Discover how to effectively unlock the power of AI-powered agents while implementing proper governance and risk mitigation with our free webinar on demand: Understanding Copilot Agents in Microsoft 365.

And if you're ready to go beyond the basics, check out our latest webinar: Implementing Autonomous AI Agents in Microsoft 365, which offers a hands-on look at how to securely deploy and customize autonomous AI agents using Copilot – safely, securely, and at scale.