19 Ways To Set Boundaries For Autonomous AI Agents

Gopichand Mannava, Independent Researcher, Chief Data & AI Architect, State of Connecticut.

Even when AI agents perform reliably in testing, certain actions warrant human oversight. For example, consider a semantic-integrity gate: automatically verify that each record’s meaning matches its metadata—not just its schema—before ingestion. An invoice date can be valid yet mislabeled as a payment date. Quarantine that mismatch before the model or vector store sees it. The failure this prevents is subtle: an AI answer that is perfectly grounded in the wrong business meaning.

Technology leaders must establish clear boundaries around agent autonomy. The challenge is enforcing those limits through system architecture rather than relying on prompts or trust alone. To help, I asked members of the Software Architects Group, a community that I lead through Forbes Technology Council, to share which actions they would reserve for human approval and how they build those safeguards into their systems.

1. Never Let AI Agents Expand Their Own Authority

Never let an AI agent expand its own authority without human approval. The bigger risk is not one bad action—it’s an agent quietly gaining the ability to take many consequential ones. The architecture for bounded autonomy is fixed permission ceilings, policy-based escalation and cryptographic auditability. This way, AI can act fast without redefining its own limits. - Swati Deepak Kumar (Nema), Citigroup

2. Treat AI-Designed Governance As A Proposal, Not A Final Decision

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