In this piece for the New York Law Journal, attorney Mark A. Berman examines how artificial intelligence is moving beyond its well-established role in legal efficiency tools and into a fundamentally different category: proactive legal intelligence that identifies risk and surfaces potential cases before violations become public or escalate into litigation.
Berman opens by acknowledging what AI has already accomplished in legal practice. Document review is faster, research is more efficient, and routine workflows have been meaningfully automated. But he argues these applications only scratch the surface of what AI can contribute. The more consequential development is a growing category of AI-powered technologies that redefines how attorneys identify legal risk and develop cases at the earliest possible stage — before harm compounds, before a client walks in, and before a violation has generated enough noise to attract attention through traditional channels.
The core value proposition he identifies is scale. Trend analysis of the kind that can surface systemic legal risk — scanning regulatory filings, consumer complaints, market data, and public records for patterns that indicate actionable violations — has historically required enormous resources. Most companies and law firms simply could not afford to do it comprehensively or continuously. AI changes that equation entirely, making it possible to monitor the landscape for legal risk in a way that was previously out of reach for all but the best-resourced organizations.
The practical implication is significant: rather than waiting for problems to become visible enough to generate litigation, attorneys and their clients can now identify issues early and address them proactively — either by intervening before harm spreads or by being positioned to act the moment a viable case materializes. For plaintiff firms, this means a larger and earlier-identified universe of potential cases. For corporate counsel and compliance teams, it means the opportunity to get ahead of exposure before it becomes expensive.
Darrow is highlighted as an example of this emerging category — a platform built specifically to operate at the front end of the legal lifecycle, using AI to detect signals of legal harm in public data and transform them into structured, actionable intelligence for legal teams.
