How do you run discovery with a new customer to find where AI will make the biggest difference?

Start from the business goal and the work as it is really done, not from the technology. Interview the sponsor about outcomes, then sit with the people doing the work, map the workflow step by step, measure where time, cost and errors pile up, and score candidate problems by value, feasibility, data readiness and risk. Leave with one or two well-defined use cases, each with a baseline and an owner.

1. With the sponsor (an hour)

• What business result matters this year: cost, speed, revenue, quality, compliance?
• How is it measured today, and what would "success" look like in numbers?
• Constraints: budget, timeline, regulation, data rules, systems that cannot change.
• Who owns the processes, and who will use the result?

2. With the people doing the work (half a day or more)

• Watch real work, not a slide about it. Ask them to share their screen while they handle real cases.
• Map each step: inputs, systems, decisions, hand-offs, waiting time.
• Ask: what is boring, what is slow, what goes wrong, what do you look up repeatedly?
• Collect real examples (anonymised): emails, documents, tickets, forms.

3. Size the opportunities

For each candidate step: volume × time per item × cost per hour, plus the cost of errors and delays. Often a dull step done 10,000 times a month beats an exciting step done 20 times.

4. Score and choose

Pick high value, high feasibility, data available, recoverable errors and a clear owner.

5. Play it back

Write a short summary: the workflow map, the opportunities with numbers, the recommended first use case, the baseline, what data and access are needed, and the risks. Agree it with the sponsor before building.

Pitfalls

• Taking the first request ("we want a chatbot") as the problem.
• Talking only to managers; the workers know where the time really goes.
• Ignoring data access until week three.
• Choosing the most impressive use case instead of the most valuable and achievable one.

What interviewers look for: curiosity about the work itself, numbers to size value, and the discipline to narrow down to one problem worth solving first.