Before accepting or acting upon an AI agent's findings, managers should critically examine the underlying evidence. AI agents frequently present statistics derived from small, skewed, or unrepresentative samples with the same confident tone as thoroughly supported conclusions, often correcting these discrepancies only when explicitly prompted. Directly asking pointed verification questions—such as identifying specific source surveys and exact response counts—reveals whether claims are well-supported or distorted.

Interrogating AI Agent Output

Several indicators signal that an AI agent's output may be flawed, misleading, or poorly supported. Key red flags include: highly precise numbers presented without an identifiable source, conclusions that suspiciously align with what the requester wished to hear, and summaries or analyses that omit the most comprehensive or recent data sets.

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