Audit Trails in Plain English

"Audit trail" is one of those phrases that sounds complicated and means something simple. An audit trail is a chronological record of who did what, and when.

Think of a receipt tape at a cash register. Every sale, in order, with a timestamp. Nobody finds that intimidating. An AI audit trail is the same idea: a running record of what went into the system, what came out, and who made the key decisions along the way.

For an AI system, that usually means five things: the input it received, the version of the model that processed it, the output it produced, any human who reviewed or approved the result, and a note of anything that changed — new data, a settings tweak, an update.

What makes an audit trail trustworthy? Three qualities. It's complete — no mysterious gaps. It's timestamped — order matters. And it's hard to quietly rewrite — if someone can edit history without a trace, it isn't a trail, it's a draft.

You don't need special software to start. A shared log, updated honestly and regularly, beats an expensive tool nobody fills in. Start simple. The habit matters more than the format.

I explain frameworks; I don't give legal counsel.