Cover of Perplexity’s “AI governance in the world of agents” guide, showing people working on laptops in a green landscape beneath a floating sphere.

AI governance in the world of agents

How to build an AI policy that gives teams clear rules for data, verification, and agent actions.

What’s inside

  1. Make responsible AI use practical

    Define approved tools, permitted uses, and data rules so employees know where AI belongs in their work and when to seek approval.

  2. Set boundaries for AI agents

    Distinguish between reading information, preparing work, and taking action. Match agent permissions, approval requirements, and monitoring to the authority delegated.

  3. Make human oversight meaningful

    Assign accountable owners, define source checks and review standards, and keep the policy current through role-specific training, usage measurement, and regular updates.

Summary

A practical AI policy gives teams clear direction on the work AI can support and the safeguards that work requires. For agents that can access company systems and take action, those rules must cover permissions and autonomy as well as outputs.

This guide organises AI governance around eight decisions: purpose, ownership, tools, uses, data, verification, agents, and training and measurement. Each section includes practical questions to help organisations turn policy principles into operating rules.

A risk-and-authority decision aid, data-category framework, and agent authority ladder help teams define appropriate controls. Use the guide to establish where AI can assist, where human approval is required, and who remains accountable for the result.

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