The fluency gap: why AI adoption creates permanent competitive advantages
Legal AI adoption isn't just about efficiency gains—it's about positioning for a market where early adopters build compounding advantages that become nearly impossible for late adopters to overcome.
The conversation around legal AI adoption usually focuses on implementation challenges and risk management, but Subroto Mukerji's insights in the ABA Journal point to something more fundamental: we're creating a profession where technological fluency determines market position.
Mukerji's background—30 years in technology before joining Integreon the same week ChatGPT launched—gives him a perspective that pure legal professionals might miss. He understands how technology adoption curves work in enterprise markets, and his observations about legal AI carry warning signals that law departments should heed.
His most significant point isn't about AI capabilities but about timing effects. Legal departments developing AI fluency today will "widen the gap between themselves and nonusers, making it harder for fast followers to catch up." This reflects a crucial property of learning systems: early adopters don't just get a head start, they get access to compound learning opportunities that accelerate their advantage over time.
Think about what this means operationally. A legal department that integrates AI tools into contract review, regulatory analysis, and client communications doesn't just work faster—it develops organizational knowledge about how to optimize these tools. They learn which prompts work best, how to structure workflows, where human oversight adds value, and how to train team members effectively. This institutional knowledge becomes a competitive moat.
The traditional model of legal services—where expertise and judgment were the primary differentiators—is shifting toward a model where technological leverage amplifies expertise and judgment. Legal departments that master this combination can deliver higher quality work at lower cost with faster turnaround times. Those that don't find themselves competing on price alone against organizations with superior operational capabilities.
Mukerji emphasizes that "the AI available today is the worst it will ever be," which means early adoption gets you on a trajectory of continuous improvement rather than a fixed capability gain. Organizations that build fluency with current tools are positioned to leverage next-generation capabilities as they emerge. Those waiting for mature solutions miss the learning curve entirely.
For in-house legal teams, this creates strategic pressure that goes beyond operational efficiency. Product teams, business units, and executive leadership will increasingly expect legal support that matches the pace and sophistication of other AI-enabled business functions. Legal departments that can't deliver risk becoming internal bottlenecks rather than strategic partners.
