AI Doesn't Fail - Bad Framing Does

I see companies throwing millions at AI and getting nothing back.

Not because the tech doesn't work. But because they're treating it like an IT project instead of a business strategy.

Here's what usually happens:

AI gets handed to IT. Success gets measured by uptime and accuracy.
Leadership waits for results. Nothing meaningful changes.

Then everyone blames "AI not being ready yet."

But here's the real problem:

When IT owns AI, success = deployment.

When the business owns AI, success = impact.

Big difference.

Look, I'm not saying IT shouldn't be involved. Of course they should. But if the person responsible for your AI initiative doesn't also own a P&L, a customer outcome, or a major cost center, you're setting yourself up for disappointment.

What actually works:

Start with a real business problem. Not a cool use case. A problem that's costing you money, time, or customers right now.

Give a business leader ownership. Someone who wakes up thinking about revenue, margins, or customer satisfaction.

Define ROI before you write a line of code or start shopping for solutions. If you're planning to "figure out the value later," you won't.

Ship something narrow that matters. One workflow that saves your team 1,000 hours beats a fancy platform nobody uses.

Treat it like a product. Keep iterating based on what actually moves the needle.

Bottom line:

AI isn't failing because the technology isn't ready. It's failing because you're asking it to behave like infrastructure when it should be driving growth.

If AI is on your roadmap this year, the most important question isn't "which model should we use?"

It's "who owns the outcome?"

I'd love to hear from you: Are you seeing AI projects succeed or stall in your world? What's making the difference? Drop a comment below.

And if you're wrestling with how to frame AI as a business initiative instead of just another tech project, let's talk. Reach out here or connect with me—happy to share what we're seeing work.

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