You’ve already done this math. If AI lets your team finish in one hour what used to take five, the invoice shrinks by 80%. The output is the same. The client is happy. Your revenue just dropped.
Every managing partner I talk to has run some version of this calculation. Many ran it months ago. The repricing calculator puts a real figure on it, from your sector and billing mix. The diagnosis isn’t the problem.
The problem is that “change what you sell” is obvious advice and almost nobody has acted on it. They don’t disagree with it. They don’t know where to start.
“Partners are talking about AI but aren’t quite sure where to start.” Jody Padar wrote that about accounting firms. Every vertical I work in has the same sentence in it.
Where the AI advice runs out
“I know we need new services. I just don’t know what they look like for my firm.” That’s a design problem, and most of the AI advice available right now doesn’t touch it.
The AI consulting market is full of adoption guidance: which tools to buy, how to train people, where to automate. That work has value. But it stops short of the revenue question. And the revenue question is the one that decides whether the firm grows.
Redesign, reprice, find the first buyer
When I talk with firms about this, the design work has three parts. None of them require more AI knowledge. They require commercial thinking applied to capabilities you already have.
Start with the delivery model. If AI handles the research, the analysis, or the first draft, your people spend their time on judgment and client relationships, which is a different service than the one you sell today. A law firm that uses AI for contract analysis has stopped selling contract review. What it sells now is risk assessment with attorney judgment on top. The scope, the staffing, and the client experience all change with it, and each of those is a decision somebody has to make on purpose. For the ladder, posture by posture, see The Delivery Ladder.
The pricing is downstream of that. Hourly billing on AI-assisted work is a race to zero, and you know it, but switching to fixed-fee or value-based pricing requires knowing your actual cost of delivery under the new model. Most firms haven’t measured that yet because they haven’t designed the new model yet. For the ladder, model by model, see The Pricing Ladder.
Then comes the part where firms stall even after they’ve sketched the new service: the first buyer. They try to sell it to everyone. Pick one client who has the problem this offering solves, have a specific conversation, run a pilot, and get a reference. The first sale is the hardest part of the whole exercise, and it’s the part nobody talks about.
Why this hasn’t happened yet
It isn’t inertia and it isn’t ignorance. A few real things are in the way.
Your senior practitioners are the people who understand your clients and your market, and they’re busy delivering work. They don’t have 40 hours to design a new service line from scratch. The people selling you AI tools don’t know your clients, your pricing, or your competitive position. And the firm’s existing incentive structure (billable hours, utilization targets) actively discourages the experimentation required to build something new.
Those are real obstacles. But none of them are permanent. They’re design constraints, and design constraints have solutions.
Efficiency has a ceiling. New revenue doesn’t.
Every technology cycle follows the same pattern. The firms that figure out how to commercialize the new capability (how to turn it into something clients will pay for) capture the market. The rest cut costs and lose ground they don’t recover.
The efficiency path has a ceiling, and the speed it buys isn’t durable. Under hourly pricing, every hour you save is an hour you can no longer bill, so the better your firm gets at the work, the less the work pays. The efficiency that was supposed to save the model is the thing accelerating its decline. After that ceiling, the only path is changing the model.
You’ve had the diagnosis for months, and it hasn’t changed a line item yet. A number tells you what you’ll lose. It never tells you what to sell. The funded competition is designing the answer while your firm re-runs the math.