"Can we trust what it produces?" Not without review. AI can generate confident-sounding but factually incorrect information — a phenomenon widely called hallucination. It can also reflect biases present in its training data, produce outdated information, or miss nuance that a human expert would catch. This does not make the tools useless, but it does mean that unreviewed AI output carries real risk, particularly when it goes to clients, donors, or the public.

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Treat AI output like a capable intern's first draft: useful as a starting point, but always requiring a human check before it goes out the door. The more consequential the output — legal language, medical information, financial guidance, public-facing communications — the more rigorous that review needs to be. Building a culture of verification, rather than blind trust, is one of the most important habits an organization can develop.