“We’ve got the tools. We’ve done the training. I don’t know what to do next.” That sentence, or a close cousin of it, ends most of the conversations I have about AI in professional services firms.
The cousin usually goes: three AI workshops last year, and what came back was a list of tools and no plan.
Everyone in those conversations has already adopted. They know AI changes what’s possible. What they don’t have is a path from “our people are more efficient” to “we earn new revenue at better margins.”
That path is the strategy part. And almost nobody is helping with it.
The distinction that matters
Adoption is tools, training, and implementation: which AI products to buy, how to train people to use them, where to automate a workflow. Infosys surveyed 3,800 executives and ranked professional services first in AI viability across 15 industries, so the tools are delivering. But every use case Infosys measured is about how a firm operates, not what it sells.
A firm can run a flawless adoption program and still watch its margins compress.
Adoption lowers what it costs your firm to do the work. Under hourly billing, a lower cost of delivery reaches the client as a smaller invoice.
The revenue question is the one almost nobody has worked: which new services become possible, how to price them, who buys them first, and how to hold your ground against a competitor selling the same old work at a lower price. That’s the commercial question most firms haven’t asked yet.
Why the advice gap exists
The AI consulting market has exploded. Fractional CAIOs, prompt engineering training, tool evaluation frameworks, readiness assessments. The supply of adoption advice has never been higher.
Almost none of it addresses the commercial question. The reason is straightforward: the people selling AI advisory services come from technology backgrounds. They know AI tools, implementation, architecture. They don’t know how to design a service offering, price it for a market, position it against alternatives, and get it to a first client.
That’s a different skill set. It’s commercial strategy, not technology strategy. And it’s the skill set that’s missing from most firms’ AI plans right now.
The commercial work an AI plan skips
The conversation I have with a managing partner starts where the adoption program stops, and none of it is about technology.
Once AI handles the research, the analysis, the first draft, and the monitoring, a firm can sell services that were previously too expensive or too slow to offer at all. That’s where new revenue lives, and it is a different list from the current work delivered faster.
Everything else follows from that list. A service nobody has sold before has no delivery model, so somebody decides what AI does, what the people do, and what the client actually sees. The work your people used to perform is work they now check, and the hours that come back go into judgment, oversight, and time with the client. That’s a change in what your best people do all day, and a firm either designs that shift or improvises it under deadline.
The price is the decision that settles whether any of it reaches the bottom line. Hourly billing on AI-assisted work hands the savings straight to the client. A fixed fee, a value-based price, a retainer, a subscription: a firm keeps a different share of what AI created under each one, and it either chooses on purpose or defaults to the model it already uses.
Then there is the client who buys it first, which is never the client list you already have. It’s the one firm whose problem this offering solves, and the conversation you have with them is the pilot.
None of that requires more AI knowledge. Your team already knows the business. What’s missing is a way to turn AI capability into an offering a client can buy.
Where firms get stuck
Treating adoption as a strategy lands a firm in one of a few predictable places.
Some deliver faster, invoice less, and wonder where the margin went. They got more productive and nobody built a service around it. Some sent everyone to AI workshops, and now their people know how to work ChatGPT and Copilot while the knowledge sits there, because nobody connected it to revenue. Some bought the platforms, configured the workflows, and ran the pilots. Then the CFO asked about ROI and there was no answer, because the tools went in without a commercial plan.
All of these firms adopted AI successfully. None of them have an AI strategy.
The next step
The adoption work isn’t wasted. Your firm needed the tools and the training. For most firms it stops there, and that’s the expensive part.
A firm that keeps its current offerings will meet a competitor charging less for work that got cheap to do. The way out runs through the question the adoption program never put on its agenda: what the firm sells differently now. The training took, the pilots worked, and the price sheet is the one the firm printed before any of it started.