A working explanation of what these systems do, where they are reliable, and where confident output should not be trusted.
It helps to separate uses by consequence rather than by technology. Lower risk: drafting, summarizing non-sensitive material, brainstorming, code assistance, training content. Higher risk: anything touching personnel decisions, patient information, discipline, or predictions that shape an operational response. The same tool can be entirely appropriate in the first group and unacceptable in the second.
If you read one thing on this subject, read this.
NIST's framework for assessing whether an AI system is trustworthy enough for the job you want it to do.
Why it matters
Neutral and free of both hype and panic. It gives you the vocabulary to ask a vendor a hard question about reliability without sounding like you are being obstructive.
Take these into the meeting. A vendor who answers them clearly is one worth continuing with.
What is above is the Hub’s framing and the best outside reading we could verify — useful on its own, and honest about being a starting point rather than the finished piece. If something here is wrong, or you know a better source, that is worth telling us before the long version is written.
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