Your AI summary got shorter. Your job of understanding it didn't.
A leader gets a long AI analysis recommending a vendor. Too much to read. So they ask for a shorter version, and get three tidy lines: "Vendor B. Lower total cost, faster rollout, acceptable risk."
That looks like progress. It isn't, necessarily.
Everything that made the recommendation true or false is still in there: the cost assumption, the rollout estimate, what "acceptable" was measured against. It's just been compressed out of sight. To challenge it, the reader now has to rebuild the whole analysis in their head, from fewer pieces. Or they approve it, because there's nothing obvious to push on.
Fewer words and less understanding work are different measures. Most AI output standards only track the first.
Now take the same recommendation, laid out differently. Three vendors compared on the same criteria. The deciding assumption stated plainly: "B wins only if migration takes under eight weeks." A route back to where that number came from.
It might even be longer. But the reader can point at one line and say "that's wrong, our last migration took five months." The correction takes ten seconds instead of an afternoon.
That's the standard worth holding AI output to. Not "is it short" or "does it read well." Can the person deciding explain the trade-off, and can they put their finger on the exact place it might be wrong?
A polished conclusion that hides its load-bearing assumption isn't clear communication. It's a governance problem with good formatting.
Legible doesn't mean true, so keep the evidence one step away. And sometimes one excellent paragraph is still the right answer.
But if your AI's output is easy to approve and hard to correct, it's not saving you time. It's moving the risk somewhere you can't see it.
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