Brian Kennedy, who leads innovation across BCLP’s global Real Estate practice, says the real measure of AI adoption is whether it becomes part of the core workflow, rather than sitting on the shelf as an optional tool. His advice to law firms is practical: match success measures to the job, keep learning continuous, and redesign work instead of simply bolting AI onto old processes.
Watch Desk analysis
What happened
In an interview published by Artificial Lawyer on 30 October, Kennedy describes how law-firm innovation teams are taking on a broader role as generative AI reshapes legal work. They are expected not only to assess tools, but also to advise on skills, resourcing, organisational culture and the firm’s wider direction.
Kennedy says measures of success should fit the purpose. For internal efficiency, look at time savings and their effect on profitability. For client-facing tools, ask whether the client experience improved. For everyday productivity tools, lawyer satisfaction and ease of use may be more useful than a single grand return-on-investment figure.
He also argues that training cannot be a once-a-year exercise when tools change quickly. Formal courses provide a foundation, but regular show-and-tells and sharing what lawyers learn through exploration can keep that knowledge moving.
Why it matters
Access to the same AI platforms is unlikely, on its own, to set one firm apart from another. Kennedy argues that firms need to choose where AI fits their commercial strategy and tailor its output to their own judgement, preferred approaches and know-how. That is a more demanding test than counting pilots, but a more useful one.
There is a concrete lesson here for anyone trying to put AI into an organisation: decide what the work is meant to improve, choose a measure that fits, and change the process where needed. “We bought the tool” is not the same as adoption. It is, however, a sentence many procurement teams have probably already heard.
Our read
Kennedy’s strongest point is that adoption is organisational change, not a software installation with a training session taped on afterwards. Firms should judge success by what changed in the work and for whom, rather than by the number of licences or pilots.
His proposed edge is also a useful challenge to the idea that everyone having similar AI means everyone gets similar results. The advantage may lie in knowing where to apply it, and shaping the work around what a firm does distinctively.
What to watch
- Whether law firms publish measures tied to efficiency, client experience or other specific goals.
- Whether informal, continuous learning becomes part of how firms train lawyers.
- Whether firms redesign workflows and tailor AI to their own expertise, rather than simply adding tools to existing processes.
Discussion spark: If law firms have access to similar AI tools, will competitive advantage come from redesigning workflows around them, or from preserving the judgement and expertise that make each firm distinctive?
Sources and evidence
- Source update (30 October 2026, 08:37 UTC)
- AI Didn’t Cause the Weil Crisis – Artificial Lawyer (30 October 2026, 08:37 UTC)
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