
The client had no shortage of AI ideas. Senior leaders had generated almost 70 opportunities, and suppliers were arriving with more. The difficult part was deciding which ideas were real, which mattered to the business and which had a credible route to a return.
Some leaders saw GenAI as important; others saw an expensive distraction. Disconnected experiments risked wasting money, damaging trust and causing the wider programme to lose support. Waiting carried the opposite risk: competitors could learn faster and build useful capability first.
Commercial teams wanted to move quickly around customers, products and growth. Technology teams had to consider data, integration, security and scale. They needed a shared way to judge opportunities, choose useful experiments and connect those experiments to a bigger direction.



