Why “AI Strategy” Is Overkill for Most Small Businesses
You don't need an AI strategy.
I know that sounds wrong. Every LinkedIn post, every conference keynote, every consultant pitch deck says otherwise. “You need a roadmap.” “You need a framework.” “You need to think strategically about AI or get left behind.”
Here's what I've learned after working with hundreds of small business owners: the ones actually winning with AI never wrote a strategy document.
They did something much simpler.
The Pattern I Keep Seeing
I've spent 20+ years coaching business owners through technology shifts. I watched the same pattern play out with websites in the late '90s, with social media in the 2010s, and with mobile apps somewhere in between. And now I'm watching it with AI.
The pattern is always the same. A new technology emerges. Consultants start selling “strategy.” Business owners feel pressure to have a plan. They try to create one. They get stuck. Meanwhile, someone else just starts using the thing, figures it out, and pulls ahead.
The strategy conversation is a trap. Let me show you why.
The Sequencing Problem
Here's the thing about AI strategy: it assumes you already know what to optimize.
But how would you know what's possible if you've never seen it?
Last week I met with an eCommerce company and their executive team. Smart people. They use Klaviyo for their CRM. They use Claude for various tasks. It never occurred to them that they could connect the two, that there's something called an MCP that lets their AI pull customer data, segment audiences, and draft campaigns without them copying and pasting between tabs.
They didn't know it was possible. So it was never on their radar as something they could even strategize about.
That's the exposure problem hiding inside the sequencing problem. You can't build a strategy around capabilities you don't know exist. And you won't know they exist until you see them working on your stuff.
The Abstraction Trap
Strategy documents stay abstract. They have to. When you're planning without experience, you end up with statements like “implement AI to improve customer experience” or “use automation to increase efficiency.”
Those statements are technically true and practically useless.
Real AI work is specific. It's “automatically categorize incoming support tickets and route them to the right person.” It's “generate first-draft responses to common customer questions.” It's “pull data from these three spreadsheets into a weekly summary.”
The gap between abstract strategy and specific implementation is where most small businesses get lost. They have a document full of aspirations and no idea what to actually do on Monday morning.
The Paralysis Pattern
Here's the cost nobody talks about: while you're trying to figure out your AI strategy, you're not using AI.
Every week you spend researching frameworks and evaluating tools and trying to build a roadmap is a week your competitors might be automating something that used to take them five hours. Over a year, that adds up to hundreds of hours they've reclaimed while you've been planning.
The paralysis is real. I've watched smart, capable business owners spend six months “developing their AI approach” and end up exactly where they started, just more frustrated and further behind.
Two Different Pictures
Let me paint two pictures.
Picture One: A business owner decides they need an AI strategy. They read articles, watch webinars, download frameworks. They try to map their business processes to AI capabilities. They evaluate seventeen different tools, get overwhelmed, and decide they need to “think about it more.” Six months later, they're still thinking.
Picture Two: A different business owner calls someone who knows AI and says, “I spend three hours every week copying data from invoices into my accounting software. Can we fix that?” Two weeks later, it's automated. The business owner didn't become an AI expert. They just stopped doing a task they hated.
Here's what I've noticed: the businesses in picture two learned more about AI in those two weeks than the businesses in picture one learned in six months of strategizing.
Why? Because they saw AI work on their actual problem. They understood what it could and couldn't do. They got a feel for how it fits into their business, not in theory, but in practice.
That's when the real strategy starts to emerge. Not before the work, but because of it.
What to Do Instead
Skip the strategy. Get a little help.
Find someone who understands AI, a fractional consultant, a technically-minded contractor, maybe even a friend who's been figuring this stuff out. Don't ask them to build you a roadmap. Ask them to fix one thing.
Pick your most painful, repetitive, boring task. The one that makes you groan every time you have to do it. Data entry. Invoice processing. Email follow-ups. Report generation. Whatever it is that eats your time and adds nothing to your expertise.
Automate that. Just that one thing.
Watch what happens.
Here's an example from my own company. We have an SEMRush account. If you've ever logged into SEMRush, you know how quickly it overwhelms you. Data everywhere. Dashboards on top of dashboards. Reports you'd need a PhD to interpret.
We connected it to our LLM. Now we ask questions in plain English. “What keywords are we ranking for that we weren't ranking for last month?” “Which competitors gained the most visibility this quarter?” “What content gaps should we focus on?”
We didn't build an SEO strategy first. We just made the tool usable. And in doing that, we learned what questions to ask, which is the foundation of any real strategy.
Strategy Emerges From Doing
You'll learn more about AI's capabilities from a single automation project than from any amount of strategic planning. You'll see what's easy and what's hard. You'll understand the limitations. You'll start noticing other opportunities you couldn't have identified from a planning document.
Strategy emerges from doing. It doesn't precede doing.
The businesses that will win with AI aren't the ones with the best roadmaps. They're the ones who got started, learned from the work, and kept going.
You don't need a strategy. You need a starting point.
Find your most painful repetitive task. Get someone to help you automate it. Learn from what happens.
That's your AI strategy.