While you’re reading this, some founder is signing a check for “innovation” that will turn into expensive digital junk in six months.

RAND Corporation says about 80% of AI projects quietly die. That’s not just stats. That’s millions burned on hype.

The tech works. The problem is how it’s sold. The market pushes AI magic instead of real engineering. Nice promises on top, messy reality underneath. Skip the slides. Audit what you’re being sold, what it can break, and how to not pay for someone else’s mistakes.

Look what our agent can do

It books flights, writes code, juggles data. Future is here. What you’re seeing is a scripted demo. It works as long as nothing goes off track. One weird input and it falls apart. Sold as flexible. Breaks on first real task.
Ignore polished demos. Ask how it handles errors, messy data, edge cases.

AI that understands your company

“We plug into your knowledge base and it answers like an expert.” That’s not integration. It’s a wrapper. On your real data, the “genius” bot will make things up with confidence. Run a guerrilla test. Give 20 to 30 real, hard questions from your business before you buy. Ask for answers. Ask where each answer comes from. You want exact quotes, not guesses.

We’ll replace your team with AI

“You’ll cut support costs and save millions.” Full automation is rare. Hidden costs show up fast. People still need to check the output, especially when mistakes are expensive. Budget for review. Assume the model gets 10 to 20% wrong. Calculate from there.

Autonomous agents will run your workflows

“They make decisions and get things done.” This is risky. A chatbot can say something dumb. An agent with access can do something dumb. Delete data. Send the wrong file. Misread a task and act on it. Start with zero trust. No write or delete access without human approval. Not until you’ve seen it run safely many times.
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We’re great at prompt engineering

“The right prompt fixes everything.” Prompts are fragile. One quiet model update and they break. Now your system depends on guesswork. Turn it into something you can test. Add evals. Track output quality with numbers. If you can’t measure it, you’re not ready.

The market is overheated. The real asset in your AI plan is not what it can do. It’s what it can’t do and where it fails.

You don’t need a hype person. You need someone who thinks in tradeoffs and numbers.

If a consultant won’t show error logs, avoids token costs, and doesn’t push back on most ideas, walk away. Next time someone offers “AI turnkey,” ask one thing. Show me where it failed. That’s where the truth about your ROI shows up.

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