Your vendor risk program was built for vendors that behave like vendors: a company, a contract, a SOC 2 report, an annual review. AI agents embedded in those vendors' products do not behave that way. They act inside your environment, hold access to your data, and make decisions, and most of them never showed up in a security questionnaire.
Third-party AI agent risk is the fastest-growing blind spot in vendor management. This article explains where these agents come from, why traditional third-party risk management misses them, and how to govern an agent you did not build.
Where Third-Party Agents Come From
You acquire third-party agents through nearly every tool you buy, often without a decision point.
A SaaS platform ships an update that adds an embedded AI agent with access to the data you have already stored there. A vendor's product connects to your systems through an integration that includes an agent acting on your behalf. A tool you approved for one purpose quietly gains autonomous capabilities in a release you did not read closely.
In each case, an autonomous system is now operating inside your environment, holding real permissions, and it arrived bundled with a product rather than through any process designed to evaluate an agent. You did the diligence on the vendor. Nobody did the diligence on the agent, because at the time of purchase the agent may not have existed.
Why Traditional Vendor Risk Misses It
Third-party risk management was designed around the vendor as the unit of assessment. You evaluate the company, review its attestations, score its risk, and re-check it on a cadence. That model has three gaps when the risk is an embedded agent.
The assessment happens at a point in time, and the agent is continuous. Your annual review captures a snapshot. The agent acts every day, and its behavior can change between reviews when the vendor updates a model or expands what the agent can do.
The questionnaire asks about the vendor, not the agent. A SOC 2 report tells you about the vendor's control environment. It usually tells you nothing about what their embedded agent is doing inside your systems, which data it touches, or what actions it can take on your behalf.
The agent's scope drifts without a contract change. A vendor can expand an embedded agent's permissions or capabilities in a routine product update. Nothing in your vendor file changes, so nothing triggers a re-review, and the agent you assessed is no longer the agent that is running.
The Questions a Questionnaire Can't Answer
Even a thorough vendor questionnaire is built to describe a company's posture, not to watch an agent operate inside your walls. The questions that actually matter about an embedded agent are the same ones you ask about agents you built yourself.
Which third-party agents are running in our environment right now? What identity does each run under, and what can it access? What actions can it take on our behalf, and which of those should require a human first? How do we stop one from acting outside its approved scope before it does? Can we prove, after the fact, what each one did? A questionnaire answered once a year cannot keep up with any of those. They are live questions about live behavior, and they need a live answer.
Treating Embedded Agents as First-Class Risk
The fix is to stop treating a third-party agent as a line item under its vendor and start treating it as an entity you govern directly, the same way you would govern an agent you built.
That means discovering embedded agents the moment they start operating, not waiting for the next vendor review to find them. It means mapping each one to what it can access and do inside your environment. It means enforcing boundaries on their actions inline, so a third-party agent cannot take an unauthorized action regardless of what its vendor shipped. And it means keeping an evidence trail of what every embedded agent did, so you can answer for it in your own audits.
The only thing that changes when you did not build the agent is that you have less visibility into how it was designed, which makes discovery and inline enforcement more important, not less. You cannot read the vendor's code, so you govern the agent by what it tries to do inside your environment, and you stop the actions that fall outside the scope you approved.
Picture a help-desk tool you rolled out last year for ticket routing. In a quarterly release, the vendor adds an agent that can now read across your knowledge base and write updates back into connected systems. Nothing in your contract changed, and your annual vendor review is eight months away, so the new capability never triggered a second look. Governed as a first-class entity, that agent shows up in your inventory the moment it starts acting, runs under a mapped identity, and is held to the same scope limits as anything your own engineers built. The write-back it was never meant to perform gets blocked inline, and the attempt lands in your evidence trail. Governed as a line item under its vendor, it would have run unexamined until the next review, or until something broke.
Govern Third-Party Agents With Drata
Drata governs the agents you built and the ones you did not on the same platform, and AI Agent Governance is now in Limited Availability. The Drata Sensor is designed to discover and register every agent at inception, including embedded third-party agents operating inside your environment, and map each to its identity, permissions, and scope. Mission Control enforces what each agent is allowed to do with policy written in plain language and blocks violations before they execute. Drift Detection flags the moment an agent, yours or a vendor's, steps outside its approved scope. Chain of Custody logs every decision as a tamper-evident evidence trail, mapped to AI-specific standards like ISO 42001, the EU AI Act, and AIUC-1, and surfaced into the same evidence layer behind Drata audits across SOC 2, ISO 27001, HIPAA, and more than 30 other frameworks.
Bring third-party agents under the same governance as your own, and prove it to auditors and customers. Schedule a demo to see how Drata governs embedded agents.