Legal operations leaders shift from AI experimentation to execution as governing, measuring, and proving AI value becomes the new priority
Legal operations (the function within law firms and in-house legal teams responsible for efficiency, technology, and process management) leaders are moving decisively from experimentation with AI to active deployment and governance, according to reporting from the New York City Bar Association's Artificial Intelligence Conference and analysis published this week. The shift is characterised as moving from asking 'what might AI do?' to 'how do we govern it, measure it, and prove its value to the business?' This framing is significant: it marks a maturation of the legal AI market in which return on investment (ROI), accountability frameworks, and measurable outcomes are replacing enthusiasm and piloting as the primary drivers of adoption decisions. Separately, panellists at the NYC Bar AI Conference argued that law school curricula must keep pace with the AI tools legal professionals are already using in practice. Oliver Roberts, founder of Wickard.ai and co-director of Washington University Law's AI Collaborative, argued that professors need to understand the market reality of AI in legal work and build backwards from that reality to prepare students. The point is directly relevant to students targeting commercial law firms: the expectation that trainees will understand and use AI tools is now embedded in hiring and training assumptions at elite practices. A third strand of the week's commentary — in FinTech Futures — addressed whether regulation can move at the speed of AI, noting the UK's post-2008 regulatory reform (which created the FCA) as a model for how statutory architecture can be rebuilt in response to structural market change.
Why this matters
The transition from AI experimentation to execution in legal operations has direct practice-area implications: law departments and law firms are now commissioning AI governance policies, vendor assessment frameworks, and ROI measurement tools — all of which require legal drafting and technology advisory input. The legal education dimension matters for City firm recruitment: firms are increasingly expecting trainees to arrive with baseline AI literacy, and those who can demonstrate genuine understanding of AI governance obligations will be better positioned at assessment centres. The regulatory commentary — whether legal frameworks can keep pace with AI development — is a live tension in UK practice, particularly as the EU AI Act enters its implementation phase and the UK's more principles-based approach to AI regulation takes shape.
On the Ground
A trainee working on an AI governance matter would assist with AI governance policy drafting — translating regulatory guidance and firm risk appetite into operational policies governing how lawyers can use AI tools on client matters. They might also assist with vendor due diligence questionnaires, assessing the data processing and security practices of an AI tool provider before the firm commits to a deployment.
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“If a partner asked you to draft an AI use policy for the firm's litigation practice, what key provisions would you include, and what regulatory guidance would you draw on?”
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