Here is what I think is behind many senior leaders’ struggle to know how to think about AI in their business.
They tried ChatGPT and the output was not bad. It saved them some time. It just was not the business-transforming moment they were promised.
They tweaked prompts, maybe tried another model, but it was hard to see evidence of the “game-changing” impacts the media and analysts keep screaming about.
So they form a quiet view of AI: useful and worth having, but one of many conflicting priorities.
AI initiatives get prioritised on a “let’s see if this helps” basis, rather than a “this changes how we operate” one. There is lots of AI noise in the business, but nothing much showing in the KPIs or the P&L, so confirmation bias creeps in.
Adoption stalls at the ceiling set by the leader’s personal experience.
The leader is not wrong about what they experienced, but they are wrong about what it means.
Generic prompts on a model trained on the aggregate of the world’s information produce generic output. That is not a story about AI’s potential. That is a story about trying to fly a rocket on diesel.
The missing ingredients are judgement, domain expertise, and the patterns the leader carries in their head. The way they read a deal. The way they qualify a client. The way they spot a problem before it shows up in the numbers.
Unlock that leader’s knowledge and get it into a form an AI system can use, and it produces work that reflects their thinking and amplifies what makes them a leader.
Then their personal experience changes, their view of AI changes, and the ceiling lifts. For them, and for their business.
If you would like a taste of what this looks like in your business, we have built a 15-minute guided walkthrough at walkingwithrobots.com/robot-disco