AI Consultancy for UK Law Firms
Law firms face a version of the AI question that almost no other sector does, because the efficiency gain lands directly on the thing the firm sells. Doing the work faster is not straightforwardly good news when the work is billed by the hour, and that tension, rather than the technology, is what most firms are actually stuck on. Our founder held CTO and CIO roles in the legal sector, so this is familiar ground.
The commercial model is part of the problem, so it is part of the work
Advice that treats a law firm as a generic professional services business tends to stop at the productivity case, which is the easy half. The harder half is what happens to pricing, to leverage and to how junior lawyers learn their craft when the tasks they used to learn on are the tasks most easily automated. A firm that improves throughput without answering those questions has created a partnership problem rather than solved a business one.
We treat that as central rather than as a footnote. That means the roadmap covers where the recovered time goes, how matters get priced when the effort profile changes, and what training looks like when the first two years of a career no longer contain the same work.
We are paid by the client, and only by the client. We take no commission, referral fee or resale margin from any vendor, we have no implementation arm that needs feeding, and we are not tied to a single platform. That is worth something in a market where almost every legal technology product now claims an AI capability and very few of the claims are comparable.
Confidentiality, privilege and the assurances clients now ask for
Before any of the commercial questions get settled, a firm has to answer a narrower one: where does client material go, who can see it, and what happens to privilege when a document passes through a third party's model. Clients are increasingly asking this in writing, and outside counsel guidelines that restrict or prohibit AI use on a matter are now common enough that a firm needs a defensible position rather than an intention to form one.
The practical answer is usually a tiered one, where general research and internal knowledge work sits in one category, client matter material sits in a much tighter one, and the boundary between them is enforced by the architecture rather than by a policy asking people to be careful. Getting that boundary right early is what allows a firm to say yes to the useful cases instead of blocking everything.
We also see a great deal of unsanctioned use in this sector, because the tools are good enough to be tempting and the pressure is real. That is worth confronting directly rather than assuming a policy has settled it, which we have written about in the risk your leadership team cannot see.
How we work with law firms
Breathe is our 5 to 10 day discovery sprint. We map your practice areas against realistic use cases, assess where your matter and knowledge data actually sits, establish the confidentiality boundary and return a costed roadmap with a three-year view of the spend, including the commercial consequences rather than only the efficiency ones.
Flow is implementation. Over 4 to 8 weeks we take one contained problem, often in knowledge retrieval or document handling, and build something usable with the confidentiality controls and the audit trail designed in, so it can go to your risk partner rather than only to an enthusiastic team.
Grow is a fractional Chief AI Officer, which suits firms that need someone accountable for AI strategy and governance at management board level without creating a permanent role for it.
We work with the wider sector through our financial services page and with insurers through our insurance page, and we work across the UK from a base in Leeds.
Related reading
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Responsible AI on a Mid-Market Budget
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