LegalTech Diaries - interview with James Quinn

James Quinn, Co-Founder and CEO of Clarilis, was recently interviewed for LegalTech Talk's LegalTech Diaries series, where he discussed Clarilis's approach to AI in legal drafting, why the managed service model succeeds where self-serve automation often fails, and what it takes for firms to move from AI pilots to enterprise-wide deployment.

On Clarilis's precedent-first approach to AI

James was asked how Clarilis makes the case for restraint in a market where competitors are leading with AI-first messaging. He explained that Clarilis is genuinely bullish on AI and continues to build new capability into Clarilis AI Draft, particularly for blank-page drafting problems. But he was clear that enthusiasm has to be grounded in ROI. James argued that the real comparison isn't AI output versus a blank page, it's AI output including all the downstream review and error-correction it demands, versus a deterministic approach built on trusted precedent. In his words, every AI-generated clause a lawyer has to interrogate carries a "tax" that compounds across a large practice. Rather than asking whether firms are pro- or anti-AI, James suggested the better question is where AI actually improves ROI, and where it just moves the risk around.

On why the managed service model prevents shelfware

James was also asked about Clarilis's managed service, where our team designs, implements, and maintains automations for clients. He shared that automation projects most often fail because firms underestimate the ongoing effort required, not just to build automation, but to keep it current as precedents and market practice evolve. In self-serve models, maintenance typically falls to a small group of motivated individuals whose priorities shift or who move on, which is how strong projects quietly become shelfware. James explained that at Clarilis, maintaining and improving automations is our team's core job, giving firms the continuity and specialist expertise needed to keep automation aligned with current practice, and to keep lawyers using it.

On scaling AI from pilot to enterprise

Finally, James addressed what he's called the defining question of 2026: the shift from "can AI do this?" to "how do we operationalize it safely and at scale?" He noted that managing partners are often asked to make enterprise-wide commitments based on pilot evidence that was never designed to support them, since a pilot shows a tool works in a contained setting but says little about how AI should reshape pricing, staffing, or competitive positioning across practices like Corporate, Employment, or Real Estate. His advice: rather than trying to build that strategic vision top-down, firms should scale AI capability through proven vendors first. It's a faster, lower-risk path that lets the evidence accumulate to inform bigger decisions later.

Read the full interview here: https://www.legaltech-talk.com/ltd-vol-16-james-quinn/  

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