Govern AI agents

AI should prepare work, not replace accountability

Compliance work combines research, assessment, documentation, and coordination. AI agents can prepare much of it: structure documents, identify open points, summarize requirements, and draft proposals.

Professional accountability remains with the team. Every AI-assisted workflow therefore needs clear boundaries: what may the agent propose, what may it change, and which steps require approval?

• Limit agent permissions by task and data context
• Keep proposals visibly separate from approved decisions
• Enforce human approval in critical workflows

Sources are the foundation of trust

An AI proposal is only as strong as its sources. A plausible answer is not enough for compliance teams. They need to see which documents, requirements, or internal evidence informed it.

Every agent run should therefore include a source view: which files were read, which passages were relevant, and which assumptions were made?

• Display sources for every answer
• Explicitly mark uncertain or missing information
• Store agent activity as an audit trail

Where AI agents create value first

The strongest starting point is often recurring, well-bounded work: document extraction, gap analysis, pre-filling controls, summarizing changes, and preparing audit questions.

These tasks take substantial time but are easy to review. That is precisely where AI can save time without taking critical decisions away from the team.