Most companies buy the wrong first AI engagement. Not because either option is bad, but because the two answer different questions.
Two different questions
An AI audit maps the landscape. It inventories risk, checks whether your data is ready and finds the gaps in governance. You come out with a clear picture of where you stand.
A discovery sprint picks one use case and walks it. It designs something shaped like a production system and validates part of it on real data. You come out with a first working path.
Choose by the evidence you need
If leadership can't agree where AI fits, or compliance needs to see the risks before anything moves, start with the map. If you already know the problem and need proof it can be solved, start with the path.
In insurance and other regulated domains the wrong choice is expensive: a quarter disappears, and underwriters who were promised help stop trusting the next pitch.