The structural answer to the objection that AI cannibalises the billable hour.
Start a conversation with the AI Adoption Concierge, already scoped to productised offerings. Pick a starting point, or describe your situation directly.
The most common internal objection to AI is that a firm cannot earn a return on it: fewer hours means less revenue, and the beneficiary is the client. Under hourly billing that objection is correct, and no amount of enthusiasm resolves it — ethics guidance is unambiguous that a lawyer billing hourly may charge only for time actually spent, so a four-hour task compressed to one is billed as one. The answer is structural rather than rhetorical. Price the outcome instead of the time and the same efficiency becomes margin. That is why the firms moving fastest on AI are also the ones moving on pricing, and why one large firm's publicly-described bet was explicitly framed as being about value-based pricing rather than speed. The move that works is productising the top of the funnel, not the bottom.
Repeatable, scope-definable, and compressed most by AI. Judgment work stays as it is.
High volume, standard architecture, decisions that fit a decision tree. The classic productisation candidate.
Playbook-driven review and drafting priced per agreement rather than per hour.
AI acceptable-use, privacy, employee handbook sections. The governance ladder is itself a product line.
Defined document set, defined output, defined turnaround.
Already the most productised area of law in many markets, and the one AI compresses further.
Recurring revenue against recurring need — regulatory updates, contract volume, fractional counsel.
How to price a product rather than an hour.
It converts an efficiency gain from a revenue loss into a margin gain.
Consumer research in 2026 found substantial resistance to AI appearing in client communication — with comfort at its lowest for anything touching the bill. The workable pattern is AI inside the product and a person on the invoice. Sell the outcome and the price; do not market the machinery.
Not straightforwardly, and this is worth getting right because it is a fee-reasonableness question rather than a commercial one. Ethics guidance has addressed it directly, noting it may be unreasonable to charge the same flat fee for work a tool has made substantially faster, and that a fee for work where little or no actual effort was performed is unreasonable regardless of the billing structure. The defensible position is that a fixed fee prices an outcome and a risk allocation rather than a duration — but a firm that keeps a fee constant while the work collapses to a fraction should expect the question, and should have an answer that is not merely "the market bears it."
Many of them already do, and the survey evidence is that clients expect commercial models to change while far fewer firms have actually changed them. That gap is a negotiating position clients will occupy whether or not firms engage with it, and some corporate clients have written it directly into their outside counsel guidelines — declining to pay full hours for work they consider AI could have done. A firm with a productised offering is in a much stronger position in that conversation than a firm defending an hourly estimate, because the conversation shifts from how long it took to what it is worth.
Disclose in the engagement terms with specific language rather than boilerplate — ethics guidance has been explicit that a general clause purporting to authorise AI use is not sufficient where consent is required. Beyond the ethical floor there is a marketing judgment: the research on AI disclosure in commercial contexts consistently finds that labelling reduces perceived trust, and the effect is strongest in premium positioning, which is exactly where professional services sit. The reconciliation most firms reach is to disclose process honestly where required and to sell the outcome rather than the tooling.
Partly, deliberately, and mostly at the end you were losing anyway. The work that productises well is the work most exposed to being done by a cheaper provider, an in-house team, or a consumer platform — so the realistic alternative to productising it is frequently not keeping it at hourly rates but losing it. Large firms have said openly that they would take on lower-margin work previously done by smaller firms if AI let them deliver it efficiently, which sharpens the point: the competitive pressure on repeatable work is arriving from above as well as below.
Describe the matter type. The Institute will help you work out whether it productises and how to scope it.