There's real pressure on leaders to 'do something with AI'. That pressure produces a lot of motion and not much value, because the technology is adopted before the problem is defined.
Readiness is about three things: data you can actually use, processes clear enough to improve, and a team able to absorb change. Where those exist, AI can deliver outsized returns. Where they don't, it's an expensive distraction.
The pragmatic path is to score a handful of concrete use cases by value, effort, and risk — then start with one or two that pay back quickly and build confidence for the rest.
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