Prototype
A working build of the highest-priority AI or automation opportunity, tested with the people who will use it on suitable data or realistic samples to judge accuracy, usability and benefit. It is step four of the audit's five steps, and its result decides whether the next step happens.
What it means in practice
The audit page says the highest-ranked opportunity is built as a working prototype and put in front of the people who would use it, running on real work or a realistic sample of it. The organisation supplies representative work, including the awkward cases, and what comes out is the prototype plus a documented result: what it did, where it broke, what a person still has to check, and whether it is worth building properly.
How we use it
It is step four of the five steps in how we audit, Build and Test a Prototype, after the opportunities are ranked and before anything is built for production. A tested prototype of the first opportunity, with its result written down, is one of the five things an audit produces. See how we audit and what an AI audit actually checks.
FAQ
Questions about Prototype
What is a prototype in an AI audit?
It is a working build of the highest-priority opportunity, put in front of the people who would use it and tested on suitable data or realistic samples. The audit page describes it as step four of five.
What if the prototype fails?
The audit page says a prototype that fails answers the question just as usefully as one that succeeds, and it does so before anything has been rolled out or rebuilt around it.
Who decides whether it worked?
The people who do the work being tested. The audit page says their verdict decides whether step five, building for production, happens.
What it means for a business
A prototype is narrow and specific on purpose. It exists to answer one question: whether the tool behaves well enough on this organisation's own work to be trusted with it. One that fails answers that question just as usefully as one that succeeds.
Ready to put this to work?
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