AI Agents Are the New Insider Risk: What MSPs Need to Know

As agentic AI adoption accelerates across the channel, managed service providers are facing a new class of operational and security challenges tied to autonomous systems. In an interview with CRNtv, N-able Chief AI Officer, Nicole Reineke, outlines how AI agents have evolved beyond passive software tools to active participants inside IT environments, and what MSPs need to know to keep clients secure.

Reineke explained that AI agents are no longer limited to analysis alone, but are now capable of executing tasks based on data inputs and predefined instructions. As these systems act with greater independence, MSPs face challenges that more closely resemble managing human users than traditional software. "You have to manage your agents exactly like you manage your employees,” said Reineke.

For solution providers already navigating security demands, customer expectations and operational efficiency needs, the agentic AI shift introduces new pressures around governance and control in client environments. One of the key risks arises from a lack of understanding about how agents behave and the importance of having the right guardrails and data restrictions in place to maintain security and business resilience.

Reineke said a helpful analogy is to manage AI agents as though you are training a new employee just out of college. “You want to restrict the information the agent has just like you would restrict an employee, and give very, very explicit operating manuals to that agent,” she said. “[That way] you have a much higher likelihood of the agent being able to succeed.”

Without the right restrictions, agents connected to critical systems can cause unintended consequences. “The danger comes in when we forget to do those little restrictions up front,” Reineke said.

Reineke also highlighted that rapid AI agent adoption and their value for efficiency and innovation comes with expanded attack surfaces, especially as agents gain access to security logs, endpoints and customer environments. To reduce risk, MSPs must adopt clear governance practices, including strict access controls, defined ownership and consistent documentation. Other critical guardrails: aligning agent permissions with least-privilege principles and treating agents as accountable entities.

For MSPs, this approach is essential to balancing AI agent innovation with control that maintains security and customer trust.

Learn more at www.n-able.com.