Start with a recurring problem
List the work your team repeats every week. For each task, record who owns it, how often it happens and what makes it frustrating. A specific problem such as re-entering approved customer details is easier to evaluate than a broad ambition to “use AI.” Speak with the person doing the work before deciding what to build.
Compare value with effort
Consider the time spent, the frequency of mistakes and the consequences of a wrong result. Then check whether the required information is available and whether the existing tools can connect. A modest project with reliable inputs can be more useful than an impressive demo that depends on inaccessible data. Include ongoing review and maintenance in the estimate.
Define a pilot you can judge
Choose one process, one accountable owner and a representative set of cases. Write down what the current process achieves before changing it. Decide what must improve and what must stay under human control. Test normal work alongside missing information, duplicates and exceptions. A pilot should help you decide whether to expand, revise or stop.
Make the next step concrete
Produce a short brief: the trigger, required inputs, proposed output, reviewer, success measures and expected operating costs. Avoid purchasing several tools before this brief exists. The useful outcome of discovery is a decision your team understands, including a clear reason to defer ideas that are not ready.
Put the idea to work
AI strategy & discovery
Find practical opportunities, compare implementation effort and agree on a measurable pilot before investing in a larger build.
Explore this service ↗