I find and rank the AI initiatives genuinely worth pursuing, mapping value, feasibility and risk so your roadmap reflects where AI actually moves the business rather than where the hype points.
This includes the data-science work, modelling, evaluation and analytics, that turns raw data into decisions you can trust. You leave with a prioritised, costed roadmap and a clear view of what to fund first.
In practice it starts with listening. I sit with the people closest to the problems, your operators, analysts and leaders, and map where effort, cost and risk actually concentrate. Every candidate idea then gets pressure-tested against three questions: is the data there, is the value real, and can you live with how it might fail?
What comes back is deliberately honest. Some of the loudest ideas score badly and get parked; quieter ones that compound turn out to matter more. You get the sequence, the dependencies and the rough cost to stand each one up, so the first thing you fund is the thing most likely to pay off.
Sound like what you need?
Start a conversation about this engagement and where you're trying to go.