AI agent actions in physical AI: what do security teams need to govern?

TL;DR: Physical AI changes the security problem from protecting AI agents alone to governing what happens when their decisions become machine actions, according to VicOne, because malicious instructions, compromised tools, or overly broad permissions can push robots and vehicles beyond intended safety boundaries. Identity verification, authority limits, and action testing now sit alongside machine safety engineering.

Editorial analysis by NHI Mgmt Group, based on content published by VicOne: “AI Agents Can Shape the Physical World. We Can Secure Their Actions.”.

Key questions

Q: How should security teams govern AI agents that can take runtime response actions?

A: Treat them as privileged NHI workloads with explicit scope, short-lived authority, and full action logging.

Q: Why can an AI agent be authorised and still be unsafe in physical AI?

A: An agent can have valid permissions yet still become unsafe if its inputs are poisoned, its tools are compromised, or the operating context changes faster than the policy can adapt.

Q: What are the signs that AI agent governance is too broad for robots or vehicles?

A: Warning signs include agents that can act across multiple operational states, tool permissions that exceed the immediate task, weak audit trails for decision-to-action chains, and safety teams relying on static approval rather than runtime checks.

Practitioner guidance

• Define action-scoped agent permissions Map each AI agent to the smallest set of actions it needs, and separate read, planning, and actuation privileges so a compromised decision path cannot trigger broad machine behaviour.
• Verify identity before high-impact actions Require strong identity binding for any agent that can change vehicle, robot, or safety-state behaviour, including authentication of the agent identity and approval of the action context.
• Test manipulated-input scenarios Simulate poisoned data, compromised tool responses, and misleading instructions to see whether the agent changes machine behaviour in ways that violate safety boundaries.

Bottom line: Physical AI expands AI agent risk from software misuse into real-world machine behaviour, which means access control alone is not sufficient.

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