How to Evaluate an AI Agent Before Giving It Real Permissions
A successful demonstration cannot replace systematic testing of autonomous tools that act on behalf of users.
AI agents differ from ordinary chatbots when they can send messages, access accounts or alter records. Their errors can cause effects outside a conversation. NIST's risk management guidance emphasizes evaluating systems in their intended context and monitoring them after deployment, rather than relying on a single best-case sample.
A useful acceptance test includes ambiguous requests, missing information, unauthorized commands and degraded connections. For a booking assistant, check incorrect cancellations, duplicate appointments, privacy disclosures and whether a human receives context at escalation. Record failure severity as well as frequency: a rare unauthorized payment matters more than several cosmetic wording mistakes.
Start with the least privileges necessary, keep a reviewable action log and set explicit stop conditions. Repeat tests after model or prompt changes and track whether user satisfaction masks hidden operational problems. No universal accuracy score establishes that every agent is safe in every industry, and this guide does not certify any individual product.
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