Recent conversation with a client was interesting on many levels. They asked whether we do special AI Leadership workshops. This seemed curious to me because AI is a change in method, not in humans. But it makes some sense if you think that people expect so much change from AI.
Having worked in Process improvement and process reengineering consulting for years, especially in the 90s and 2000s (when Insurance policies and claims and bank deposits were still on paper, in desk drawers, and humans had to input them), it never occurred to me that people would think managing AI change was any different to managing every other change.
Here is Neil Perkin talking about how the approach to AI related change needs to be 70 20 10: 70% of the change is getting people to change, 20% tech and data, 10% models. He says that’s a BCG model. I suspect most people in organisations implementing change are under the impression that the AI will be all they have to think about it.
So they put themselves into the situation of solving the wrong problem, as outlined in this story sourced by Billy Oppenheimer. Statues were crumbling. The fix had been to wash the statues to get rid of the spiders, but that worsened the problem. Root cause / down stream, the flood lights used at night were attracting mites. These attracted spiders. This was causing the webs which caused the crumbling. Turn the lights on 1 hour later, the mites go elsewhere at dusk, crumbling slows.
Solving the model problem in AI is washing a statue or killing a single spider. It solves the wrong problem.
People are the “problem” and the key to making things happen differently.
