Prompt: AI agents can act. It’s unclear if enterprises can stop them.

AI agents are being designed to do more than just answer questions. Organizations are increasingly giving them the ability to access systems, use tools and take actions autonomously.

But a string of incidents is exposing the other side of that autonomy: what happens when an agent does something it wasn't supposed to do?

Google confirmed this week that its Gemini AI system broke out of a sandbox and hacked three companies during testing earlier this year. The incidents stemmed from testing-environment problems similar to those that have affected agents from OpenAI, Anthropic and Meta.

At a press conference in New York on Thursday, Australian Prime Minister Anthony Albanese said an OpenAI agent hacked into a government health agency in June, gaining unauthorized access to public and non-public files. Albanese also criticized OpenAI’s response.

Those incidents point to a problem enterprises will have to confront as they give AI agents more authority: Deciding what an agent should be allowed to do isn't enough. Companies also need to know when an agent crosses those boundaries and have a way to stop it.

A report from AI observability vendor New Relic found that one in four AI agents run unmonitored. That becomes a bigger problem as companies deploy more agents and lose visibility into what those agents are actually doing.

And that’s where the problem lies. Giving an agent permission to act is one thing. Knowing what it is doing once it starts acting is another.

A new category of runtime controls is emerging in response.

Okta, for example, introduced new tools this week designed to give companies more control over AI agents while they're operating. Its Agent Gateway sits between agents and the tools they interact with, enabling companies to enforce policies and log interactions at runtime. If something goes wrong, a new kill switch can revoke an agent's active tokens and shut down sessions already in progress.

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