Banking
A bank could use AI to triage fraud and AML alerts, drafting first-pass narratives so investigators can focus on the cases that need human judgement.
Investigation queues are full of low-risk alerts that still have to be written up. The high-risk cases - where investigator time matters most - get squeezed.
The fastest way to test a use case like this is a tightly scoped 30-day pilot rather than an open-ended rollout. The shape we recommend in almost every UK SMB is the same: one workflow, one owner, one success metric, one decision date. The point is to learn quickly and cheaply, not to transform the business in month one.
In week one, map the current workflow end to end and time it. This baseline is non-negotiable - without it, you can't tell whether the AI made things better, worse, or about the same. In week two, set up the tool and train two or three people deeply rather than rolling it out widely. In week three, run the new workflow alongside the old one and capture friction in writing. In week four, review the data, decide go or no-go, and write up what you learned.
Even a no-go is a successful pilot if you understand why. The worst outcome is a 'maybe' that drags on for another month and quietly absorbs the budget.
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