CTOs Deploying AI Fastest Answer One Question the Same Way

Everyone’s hunting AI use cases. Winners are refusing them!

Figure 1. Successful CTOs don’t collect AI use cases. Instead, they judicially scrutinize ones naturally arising. Instead of many projects and initiatives, their boards just have at most three.

 

Across a dozen customers, one pattern keeps showing up:

The CTOs who deploy in weeks have a "Kill List" before they have a pilot. The stuck ones say "yes" to everything and tend to finish nothing.

My question:

"What AI use case are you saying NO to — and why?"

The fast deployers said NO to:

• AI that touches 3+ systems before proving value in ONE;

• Use cases where the training data classes don’t exist in the wild;

• "Transformational" pilots with no owner who’s canned for failure.

No owner, no hard calls. Eighteen months later, you’re still "learning." And "transformational" becomes its own special kind of misery. The best successes I’ve seen are "augmentational" in existing business context.

Strategic NO is your MOAT!
Competitors copy your use case in a quarter.
They can’t copy your discipline.

What I repeatedly see: same AI initiative; same vendor; same tech. One ships, another doesn’t.

What gives?!

Clarity about what NOT to do.

Because who cares about pilots? What’s in production?

That answer starts with what you refused.

What’s on your "NO" list?