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

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.

The Strategy Trap

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

1. Leadership reads about AI disrupting their industry
2. They hire a consultant or form a committee to develop an "AI roadmap"
3. Months of meetings produce a document full of possibilities
4. Nothing actually gets built because the possibilities are too abstract
5. Six months later, they're back where they started

I've seen this pattern play out dozens of times. The strategy becomes the goal, rather than a means to an end.

What Works Instead

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.

From there, the question becomes: can AI help with this specific thing? Sometimes the answer is yes—automation, summarization, pattern recognition, or generation. Sometimes the answer is no—the problem is actually about process, not technology.

Three Questions to Ask Instead

Before you develop an AI strategy, try answering these:

1. What do you wish you could delegate but can't? This reveals tasks that require judgment but are repetitive enough to systematize.
2. Where are your bottlenecks? Look for places where work piles up waiting for human attention.
3. What information do you have that you're not using? AI excels at finding patterns in data you already collect.

The answers to these questions will tell you more about where AI can help than any strategy document.

Start Small, Learn Fast

The best AI implementations I've seen 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 their 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.

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

The Bottom Line

If someone asks you about your AI strategy, here's a better answer than a 50-page document: "We're experimenting with [specific application] to solve [specific problem], and we're measuring [specific outcome]."

That's not a strategy. It's something better—it's progress.