AI Failures? It's Not a Technology Problem

Here's the thing nobody wants to admit about AI:

Your AI problem is probably not an AI problem.

It's a strategy problem. A data problem. A people problem. Sometimes all three.

I've talked to teams who spent months evaluating AI vendors, comparing models, debating architecture - and never once asked the most important question: What specific problem are we actually trying to solve?

Not "how can we use AI." Not "what can AI do for us." What. Problem. Are we solving.

That shift in framing changes everything. It changes which technology you choose. It changes how you measure success. It changes whether you even need AI at all - or whether a simpler solution would do the job better.

The companies winning with AI right now didn't start with the technology. They started with a problem. A real, documented, understood problem. And then they found the right tool for it.

That's not a complicated insight. But it's one most organizations skip entirely.

Chapter 3 of my book walks through exactly how to do this - the Problem Definition Canvas. Check it out at https://www.amazon.com/AI-Enterprise-Lessons-Doing-Right/dp/B0H1WRNYRT to learn the hard lessons to doing AI right.

What problem are you trying to solve with AI right now? Tell me in the comments. I'm genuinely curious.

#AIintheEnterprise #AIStrategy #BusinessOwners #ProblemSolving #LucusLabs