As law firms accelerate investment in AI, many are recognising the technology is driving productivity gains. The question now is how firms convert that time into measurable value through better pricing, protected margins, increased capacity, faster delivery or new client services.
Clients are also watching closely. While 59% of in-house legal teams want their law firms to be using generative AI, 71% of law firm clients said they don’t know if their firms are using Gen AI tools on their legal work, according to a Thomson Reuters survey. This reveals a communication challenge. Clients may expect AI to reduce fees, while firms are still working through how AI changes matter economics.
“There’s an assumption that AI will lead directly to price reductions, but that is not yet happening at scale, says Kirsten Maslen, senior director for growth & commercial strategy at Thomson Reuters. “Many firms are still experimenting at a task level. The next step is translating those productivity gains into clear commercial models.”
For Maslen, the key is to avoid treating time saved as the whole ROI story. “Time saving is only the starting point,” she says. “The real question is what happens to the capacity AI releases? Does it protect margin on fixed-fee work? Does it reduce write-offs? Does it allow the firm to handle more matters with the same resources? Does it enable faster service delivery, better client service or new types of legal product? That is where AI becomes business value.”
The answer varies significantly by matter type. In fixed fee work, the commercial case is often more direct: if AI reduces the cost of delivery while the fee remains fixed, it can protect margin. In hourly-rate work, the position is more complex because reducing time may also reduce billable hours unless firms rethink pricing, scope or value.
“There is no single ROI model for applying AI to legal work,” says Maslen. “A due diligence exercise, a fixed-fee employment matter, a major dispute and non-billable legal research all have different economics. Firms need to segment their work and understand where AI creates cashable value.”
That segmentation also helps firms communicate more confidently with clients. Rather than making broad claims about AI adoption, firms can explain where AI is being used, how outputs are checked and how the use of AI affects scope, pricing or delivery.
“Where AI materially changes how a service is delivered or price, firms need to be able to explain the use case, the safeguards and the human accountability around the output,” says Maslen. Verification is central to that trust equation. AI-generated legal work only creates value if lawyers can quality-check the sources, reasoning and accuracy of the output. “A research answer generated in minutes is only valuable if the lawyer can verify it efficiently,” says Maslen. “If verification is difficult, the time saving can disappear in review. Trusted content and frictionless verification are what turn AI productivity into usable professional value.”
AI is also likely to accelerate existing pressure on the hourly rate billing. As more work can be completed faster, firms may need to consider where fixed fees, capped fees, subscriptions, expedited services or productised deliverables make more sense.
Fixed fees may become easier to price accurately where AI makes parts of the work more predictable. At the same time, firms may use AI to add value rather than simply reduce cost, for example through explanatory materials, transaction guides, client dashboards, self-service tools or risk-analysis products that were previously too resource intensive to produce at scale.
“AI is not just a time-saving tool; it is a capability expander,” says Maslen. “It can allow firms to deliver more consistent work, support more matters with the same resources and create services that were previously uneconomic.”
The shift also has implications for talent. Firms are trying to figure out what AI adoption is going to mean for how work is performed and by whom. With AI taking on a greater proportion of work that was previously handled by junior lawyers, firms need to reconsider how to manage training and future talent pipelines and be more deliberate about developing judgement, reasoning and verification skills.
“The skill is not simply getting to an answer faster,” says Maslen. “Lawyers need to know how to challenge an AI-generated answer, verify the sources, identify what may be missing and defend the reasoning.”
Used well, AI can also become a learning tool, helping trainees explore unfamiliar issues and test their thinking before seeking supervisor input. But that requires firms to build AI literacy into training and supervision, rather than treating AI as a shortcut.
The firms that benefit most from AI will not necessarily be those that adopt it fastest, but those that can connect adoption to value: clearer pricing, stronger margins, better client communication, trusted verification and more intentional talent development.
As law firms accelerate investment in AI, many are recognising the technology is driving productivity gains. The question now is how firms convert that time into measurable value through better pricing, protected margins, increased capacity, faster delivery or new client services.
Clients are also watching closely. While 59% of in-house legal teams want their law firms to be using generative AI, 71% of law firm clients said they don’t know if their firms are using Gen AI tools on their legal work, according to a Thomson Reuters survey. This reveals a communication challenge. Clients may expect AI to reduce fees, while firms are still working through how AI changes matter economics.
“There’s an assumption that AI will lead directly to price reductions, but that is not yet happening at scale, says Kirsten Maslen, senior director for growth & commercial strategy at Thomson Reuters. “Many firms are still experimenting at a task level. The next step is translating those productivity gains into clear commercial models.”
