How Smaller Law Firms are Using AI to Meet Client Needs

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Smaller law firms often work with leaner teams and fewer dedicated resources for adopting new technology. They can also make decisions quickly and stay close to the work they want to improve. That closeness to the work helps smaller firms spot where AI could make a difference, test it quickly, and put what works into practice.

At Harvey FORUM in Sydney, Grant Guenther, National Managing Principal Lawyer at Macpherson Kelley; Ben Phi, Managing Director at Phi Finney McDonald; and Samantha Hocking, Chief AI & Knowledge Officer at Gilchrist Connell, discussed how their boutique firms are putting AI to work. Their clients have different expectations, but each leader is working through the same practical question: Where can AI make the biggest difference, and how do you bring lawyers along?

Start With the Work That Needs Attention

The best place to start depends on the firm’s clients and the work they need done. Hocking said some insurance clients now expect her firm to use AI for initial drafts and are questioning how much they should pay for work that AI can help complete faster.

For Phi, speed matters early in a class action. His team needs to assess potential cases, explore different approaches, and decide which are worth pursuing. AI helps lawyers work through possibilities and narrow the field, even when they’re up against much larger legal teams. The analysis still needs careful verification, but the firm can get to the questions that require legal judgment sooner.

In both cases, the opportunity is tied to a specific demand on the firm’s time. That makes it easier to see where AI helps and where lawyers should focus their attention.

Look Beyond Time Saved

Faster work doesn’t always mean fewer hours on a matter. For Guenther’s team, AI can make it practical to consider questions they might previously have set aside because the time required would have been hard to justify to a client. “I’m not entirely sure that it’s shrinking what we’re spending time on, but I do think it’s reallocating what we’re spending time on,” he said.

That can mean exploring another approach or examining an issue in greater depth before deciding how to advise. Many of the businesses his firm serves have small in-house legal teams or none at all. They come to outside counsel with a problem rather than a prescribed way to solve it, so the value may lie in the additional possibilities their lawyers can consider within the time available.

Hocking described a different use of that time. After a senior associate drafted questions for construction experts, she put the draft through Harvey for feedback. The response flagged where questions might be leading or moving from objective inquiry toward advocacy. Hocking shared that feedback with the associate as an opportunity to learn from the review, as well as improve the questions at hand.

Make Adoption Part of the Work

Smaller firms may be able to make decisions quickly, but they still have to find time to put those decisions into practice. Building a useful workflow with AI takes input from lawyers who know the work: examples of a good result, feedback on the output, and revisions when the first attempt falls short. Practice leaders need to review and refine those workflows alongside their client work, which can slow the rollout.

The firm also needs to decide where people can experiment safely. Hocking described a targeted rollout that let her team manage risk and assess results before expanding access. Phi emphasized protections for client data and privilege, then put the goal plainly: “Establish a safe space within which you can then put this tool into the hands of your employees and let them experiment.” Importantly, lawyers still need to verify the work produced within those boundaries.

Learning from colleagues can help a small team make progress without a large innovation function. At Gilchrist Connel, Harvey users share prompts and examples in an internal chat. Lawyers can see how others are using the tool, ask questions, and build on what early adopters have learned.

Smaller firms are close to their clients and the work their lawyers do every day, giving them a clear view of where AI might help. By starting with one problem and involving the people who know it best, they can learn what works and build from there.

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