Why Most "AI Strategies" Fail (And What to Do Instead)

Everyone wants an AI strategy. Few people want to do the unglamorous work of figuring out what AI should actually do for them.

Section 01

The Problem

Every week, I talk to business owners who tell me they need an "AI strategy." They've read the articles, attended the webinars, and heard from their peers that AI is going to change everything.

They're not wrong—but they're also not asking the right questions. The problem with "AI strategy" is that it puts the technology first. It assumes that once you have the strategy, the applications will become clear.

In practice, the opposite is true: the best AI implementations start with a very specific problem and work backward to the technology.

Section 02

The Trap

Here's what typically happens when a business decides it needs an AI strategy:

Leadership reads about AI disrupting their industry

They hire a consultant to develop an "AI roadmap"

Months of meetings produce a document full of possibilities

Nothing actually gets built—possibilities are too abstract

Six months later, they're back where they started

→

The strategy becomes the goal, rather than a means to an end.

Section 03

What Works

The businesses that successfully implement AI don't start with strategy. They start with a single, specific question:

What takes too long, happens too often, or requires too much manual attention?

That's it. No grand vision required. Just an honest assessment of where time and attention are being wasted.

Question 01

What do you wish you could delegate but can't? This reveals tasks requiring judgment but repetitive enough to systematize.

Question 02

Where are your bottlenecks? Look for places where work piles up waiting for human attention.

Question 03

What information do you have that you're not using? AI excels at finding patterns in data you already collect.

System Insight_

"Strategy is a commodity. Execution is an art."
— Gary Vaynerchuk

The most successful AI implementations share a pattern: specific problem → minimal viable solution → measure → iterate.

// Skip the 50-page roadmap. Ship something small this week.

Section 04

Start Small

The best AI implementations share a common trait: they started with something small and specific, learned from it, and expanded from there.

A Coral Gables spa didn't build an "AI-powered customer experience platform." They started by automating appointment reminder texts. That worked, so they added personalized follow-up messages. Then automated rebooking suggestions.

Each step taught them something about their customers and their operations. That's not a strategy—it's a practice. And it's far more valuable.

Section 05

The Bottom Line

"We're experimenting with [specific application] to solve [specific problem], and we're measuring [specific outcome]."

That's a better answer than any 50-page strategy document. It's not a strategy—it's progress.

Want to find your starting point?

Let's talk about what's slowing you down—and whether AI can help. No sales deck, just a real conversation.

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Why Most "AI Strategies" Fail: And What to Do Instead