Most AI projects fail not because the technology is broken, but because the business case was never clear. A company buys a tool, assigns an owner, and waits for something to change. Usually, nothing does.
I start with the opposite assumption: do not buy AI until you can explain, in business terms, what will be different if it works.
That means mapping how value actually moves through the company. Where does revenue come from? What are the fixed and variable costs? What decisions are slow, expensive, or inconsistent? Where is information trapped in one person's head? And what would have to be true six months from now for this investment to be worth it?
Only after that analysis do I look at tools. Sometimes the right answer is a large-language model. Sometimes it is a simpler workflow change. Sometimes it is nothing at all.
The companies that get value from AI are the ones that treat it as an operating decision, not an IT project. The technology is new, but the discipline is old: understand the business first, design the plan second, and own the outcome third.