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As a leader, we are faced today with a proliferation of potential AI use cases. And some of them are more impactful than others, and some are frankly more realistic or less realistic than others. And there’s a lot of people selling you snake oil about, “Oh, we will make you an AI that will transform this or that.” And, frankly, some of that is just vaporware. It’s not really there. Like many things in life, you can put any potential use case for AI on in a two by two matrix.
Attractiveness versus feasibility. How attractive is a potential AI use case? Does it increase my efficiency of my organization if it worked by one percent, by five percent, by fifty percent?
And then how feasible is it really? How much, for example, would I have to entirely rearchitect the system around it to even introduce this AI into my existing organization? And then how real do I think this is? Do I trust that this organization that I’m dealing with can actually deliver on its promises?
And so I think if you’re coming into an AI use case, that is the same framework at which I would evaluate any technology. AI is just an example of that. And coming in with a critical lens: Do I believe in what I’m told? Can I do a small pilot to demonstrate feasibility to test whether the value that is being hyped is really there? I think that is the right lens for deploying any technology and certainly something in this very overhyped space.