Every company can buy the same AI. Very few can use it the same way.
Sooner or later someone in the room asks the question. It might be a board member, a partner, or the owner’s brother-in-law who read an article on the flight in. “What is our AI strategy?” The answer that follows is usually a list of subscriptions. A chatbot on the website, a writing assistant for marketing, a pilot with a vendor whose name nobody can quite remember by the next meeting.
That list is not a strategy. It is a shopping history. A strategy is a set of choices about where a business will be better than its competitors and why that advantage will last. A subscription that every competitor can sign up for this afternoon does neither.
I built the Lean AI® framework around that gap. Its practical value is easy to see: less waste, faster work, fewer tools. Its strategic value takes a little longer to explain, and it is the part most owners underestimate.
The tool is not the advantage
The uncomfortable fact about artificial intelligence in 2025 is that almost nobody owns anything special. A twelve-person roofing company and a national contractor can open the same models on the same afternoon for roughly the same monthly fee. The capability that would have cost a research department a decade ago now arrives as a line item next to the phone bill.
When a resource is equally available to everyone, it stops being a source of advantage and becomes a cost of doing business. Electricity did not make any factory better than its competitors once every factory had it. What separated factories was how they arranged the work around the power. The ones that simply swapped a steam engine for an electric motor saw modest gains. The ones that redesigned the floor around what electricity made possible changed their industries.
AI is following the same path, only faster. The model is the motor. The advantage belongs to whoever redesigns the floor.
Where the value actually shows up
The research from the past year points in one direction. In late 2024, Boston Consulting Group surveyed executives across industries and found that 74% of companies had yet to show tangible value from their AI investments. The companies that were getting value were not spreading AI thinly across every department. They concentrated on a few priorities, and they found most of the return inside core business processes such as operations, sales, and R&D.
McKinsey’s March 2025 State of AI survey reached a similar conclusion from a different angle. It tested twenty-five organizational practices against bottom-line results, and the one most strongly tied to earnings impact was fundamentally redesigning workflows. It was also one of the least common. Only about one company in five had redesigned any workflow at all, and more than 80% reported no meaningful effect on earnings.
Read those two findings together and the pattern is hard to miss. Most companies bought the motor and left the floor alone. The few that changed how the work itself was organized are the ones collecting the return.
That is not a technology insight. It is an operations insight, and it is the foundation Lean AI® was built on.
Two ways to approach AI
Most businesses default to a tool-first approach without ever deciding to. A vendor makes a convincing case, a department head wants to try something, and a year later the company has a stack of subscriptions and no clear answer about what any of them changed. Lean AI® reverses the order. It starts with how work moves through the business and brings AI in only where it strengthens that flow.
The difference looks small at the start and very large two years in.
| Tool-first AI | Lean AI® | |
|---|---|---|
| Starting question | Which AI tools should we buy? | Where does our work slow down, and why? |
| What gets automated | Whatever the tool does well | The constraint that limits the business |
| Broken processes | Run faster | Fixed or removed first |
| Software stack | Grows with every pilot | Shrinks or consolidates |
| Accountability | Assumed, often unclear | Named owner for every process |
| How success is measured | Adoption, usage, activity | Cycle time, margin, capacity, error rate |
| What competitors can copy | All of it, by signing up | Very little, because it lives in the operation |
The last row is the one that matters strategically. A competitor can buy your software tomorrow. It cannot buy the clarity, ownership, and discipline that let the software work inside your business. Those take time to build, and the time is the moat.
What the business actually gains
The operational benefits of Lean AI® show up first: hours recovered, reports produced faster, follow-ups that no longer slip. Those are real, but they are not the reason an owner should care at a strategic level. The strategic returns arrive more slowly and last longer.
Capacity without proportional headcount. When waste is removed before automation is added, the business can take on more work with the same team. Growth stops being a hiring problem first and becomes a sales problem, which is the problem most owners would rather have.
Margin that holds. Tool-first AI tends to add cost in layers: a subscription here, an integration there, a consultant to make them talk to each other. Lean AI® favors fewer tools and integrated systems, so the savings are not quietly eaten by the stack that produced them.
Resilience when people leave. In most small and mid-sized companies, critical processes live in the heads of a few long-tenured employees. Documenting and clarifying those processes is a prerequisite for applying AI to them. The side effect is that the business no longer depends on one person’s memory to function.
Less dependence on the owner. This is the return owners notice last and value most. When work is clearly defined and owned, decisions stop routing through one desk. AI can then support the people making those decisions instead of the owner making all of them.
A compounding advantage. Every process that is clarified makes the next one easier, because the data is cleaner, the handoffs are known, and the team has learned how to adopt change. A company two years into this work is not just two years ahead of a tool-first competitor. It is moving faster, on a better foundation, in a direction the competitor cannot see.
Where to start
The instinct is to start with a list of everything AI could do for the business. Resist it. A list of possibilities is how companies end up with eleven pilots and no results.
Start instead with one question: what is the single constraint that limits this business right now? It might be how long it takes to turn an estimate into a signed job, how many days pass between finished work and a sent invoice, or how much of the owner’s week disappears into approvals. Every business has one constraint that governs the pace of everything else, and improving anything other than that constraint produces activity rather than results.
Once the constraint is named, the Lean AI® sequence follows naturally. Map how that work moves today and who owns each step. Remove the steps that no longer serve a purpose. Then, and only then, decide whether AI can shorten what remains. Sometimes it can. Sometimes the fix turns out to be a clearer handoff and a shared calendar, and the AI budget is better spent on the next constraint.
Both outcomes count as success. The goal was never to use AI. The goal was a business that runs better, and AI is one of several ways to get there.
A better answer to the question
So the next time someone asks about the AI strategy, the list of subscriptions is the wrong answer. A better one sounds like this: we know where our work slows down, we know who owns each step, and we are using AI to remove the constraint that matters most before we move on to the next one.
It is a less exciting answer. Nobody in the room will picture a robot. But it is the only one of the two that describes something a competitor cannot buy this afternoon.
Ryan Gartrell is the creator of the Lean AI® framework and founder of Ryan Gartrell, P.A., a consulting firm that helps owner-led businesses build operations strong enough to benefit from AI. To learn how Lean AI® could apply to your business, start with a conversation.
