Back when EVs first became a thing, the incumbent automakers did what you might expect: they buried their heads in the sand, dismissing EVs as a passing fad. When they did wake up as EVs went mainstream, they responded by simply swapping electric motors into their existing gas-powered platforms. The result? Clunky, expensive, and underwhelming EVs that couldn’t compete with Tesla’s sleek, software-first vehicles. They approached EVs like a simple component swap, not a fundamental rethinking of what a vehicle could be.

Eventually, some got the memo. Companies like VW, Porsche, and Hyundai started building EVs from the ground up — rethinking vehicle layouts and form factors, integrating software and UX, and designing for a different kind of driver. Those brands are now legit competitors to Tesla, not just playing catch-up. Why? Because they figured out how to combine what they already had (brands, expertise, supply chains) with a totally new operating model enabled by EV technology.

And now, the same thing is happening with AI — except this time, it’s small and mid-sized businesses (SMBs) that are standing at the edge of the transformation. I’m talking about white collar service-based SMBs — the ones working in industries like medical coding and billing, logistics, legal, accounting, and staffing. These businesses make up around 40% of all U.S. firms and generate roughly 15% of GDP. That’s not a niche — that’s a major slice of the economy.

The question is: will SMBs learn from the mistakes that the automakers made with EVs?

The 5 Most Common Mistakes SMBs Make with AI

The risk isn’t just in doing nothing — it’s in doing the wrong things and thinking you've done enough. Here are some of the flawed approaches I see most often, each ceding market share to competitors or, more dangerously, AI-native upstarts:

1. Thinking AI is just task automation. A lot of SMBs treat AI as a way to speed up existing workflows. The issue here is that it’s not just about doing things faster or cheaper — it’s about doing things differently. Like the EV example above, you can’t just plug AI into an old process and expect it to work seamlessly. AI requires that businesses reimagine entirely how they solve problems and bring value to their customers.

2. Expecting quick fixes. AI can feel like a magic bullet, but it’s not. No AI tool is going to solve everything with a single click, out of the box. SMBs looking for quick fixes will be disappointed.

3. Quitting after being overwhelmed by the noise. A lot of SMB leaders start taking meetings and hearing pitches from AI software vendors and come away paralyzed by the breadth of options, rapidly changing capabilities, and confusing jargon — and that’s if they already kinda get what AI is and what it can do. It’s enough to just throw in the towel and forget the whole thing. And that’s exactly what many do.

4. Thinking you need to implement everything at once. SMB leaders often think of AI in the same way they’ve encountered previous tech shifts like cloud or SaaS. After evaluating the costs and benefits of (finally) upgrading existing systems, they pursue big “lift and shift” projects. These massive efforts are disruptive, expensive, and hard to get right — and they’re a major reason many SMBs avoid change altogether.

5. Lacking the right talent. If you’re going to reimagine and redesign your business, you need the right people on your team. Many SMBs try to adopt AI without bringing in product, tech, or design specialists who can build use cases, test products, and actually integrate these capabilities into the business. This is especially difficult for legacy businesses that have been optimized, over decades in some cases, to operate like an assembly line – focused on performing tasks versus adapting solutions.

What SMBs Should Do Instead

Here’s the good news: SMBs have real advantages in this moment. They’re close to their customers. They understand the nuances of their industries better than anyone. That kind of domain expertise and trust is something most tech startups would kill for.

The opportunity isn’t about chasing shiny tools — it’s about using these new capabilities to serve customers better and build smarter, higher margin businesses. The key is to be intentional: start with the problems you’re already positioned to solve, and redesign how you solve them.

Start with the Customer Experience

SMBs often start with what they already do and try to overlay AI capabilities from there. Don’t begin with what you do — start with what your customer is trying to achieve. Sit with them and really understand the context of their work, where they waste time on repetitive tasks, run into friction, or where their work outcomes could be enhanced with additional tools or functionality.

Don’t Just Add AI — Redesign Around It

Once you’ve taken the time to understand what your customers are really trying to achieve, start exploring how AI might help deliver those outcomes more effectively. This is where having a basic understanding of AI’s capabilities matters — not deep technical fluency, but enough to imagine what’s possible.

From there, you can begin developing grounded, practical use cases. And this is the moment to re-enter the market and start evaluating tools. Instead of being overwhelmed by a flood of AI pitches and vendor noise, you’ll be approaching the space with a clear sense of purpose: “Here’s the problem we’re trying to solve. What tools can help us solve it better?”

That shift — from browsing features to solving problems — changes everything.

Test and Iterate

You don’t need a 5-year roadmap. You need a pilot. Start with small experiments. Pick a specific process or customer interaction, and test an AI-powered solution. See how it works, learn from it, and build on what’s successful. AI is iterative by nature, so approach it with a mindset of experimentation.

Invest in the Right Talent and Skills

You’ll need more than just AI tools. You need people who understand how to apply those tools effectively. This might mean hiring new talent, upskilling your existing team, or partnering with experts and consultants. It’s crucial to have people who understand product management, design thinking, and engineering so that AI can be integrated meaningfully into your service delivery.

This is where I spend most of my time — helping SMBs redesign their teams, workflows, and org structures to actually deliver on the promise of AI.

Embrace Continuous Learning

AI isn’t a one-off transformation; it’s an ongoing process. The landscape will keep changing. Your company has to be ready to evolve continuously — embracing new tools, learning from mistakes, and iterating on the process. That requires a mindset shift: from seeing AI as a project to treating it as a continuous journey.

Don’t Be Afraid to Ask for Help

If any of this sounds overwhelming or beyond your company’s current skill set, you’re not alone — and it’s okay to ask for help. Most of my clients are SMB services companies trying to redesign their talent, workflows, organizational structures to do a lot of this stuff. And I’ve found an increasing number of strategy, engineering, and product management consultants doing similar work. From identifying the right AI tools to integrating them seamlessly into your operations, these experts can help bridge the gap between your current state and the future you want to build.

AI doesn’t have to be an intimidating, insurmountable challenge. You don’t have to go it alone — and sometimes, partnering with the right expert is the smartest way to move forward.

The Opportunity (and the Risk)

This is a once-in-a-generation shift. For SMBs, it’s a chance to leapfrog slower competitors and build modern, higher-margin businesses around what they already do best. But only if they’re willing to rethink their models from the ground up — and avoid the mistakes the automakers made.

AI won’t replace you.

But someone who builds a better version of your business with it just might.

The only question is whether you’ll wait until it’s too late — or get moving now, while you still have the edge.

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