Legal tech · Industry brief
Top three stories shaping Legal tech today, written for someone who already works in the industry: regulation, M&A, new entrants, notable filings, and any precedent worth pulling. Cite the trade publication (e.g. trade press, government source, court docket) directly so I can follow up.
← Zur aktuellen AusgabeLaw firms weaponize homegrown AI, indemnity gaps widen
Law firms build in-house AI
Build versus buy is shifting decidedly toward build.
Law firms are now developing proprietary AI tools and wrestling with whether to monetize them by selling to clients or peer firms [Quelle: American Lawyer]. The math works: subscription revenue, stickier clients, faster automation of routine work. The risk cuts both ways—sharing tools can train clients to handle work in-house, starving firms of billable hours, while keeping tools private leaves money on the table. This mirrors Setfords' playbook from earlier this week; expect more firms to follow as white-label software proves too rigid for niche practice models.
The question is no longer whether to build—it's how to monetize without cannibalizing your core business.
AI indemnity clauses remain unsettled
Insurance and contracts are playing catch-up to AI risk.
Following up on yesterday's update, indemnity clauses are being rewritten in real time as insurers and companies scramble to allocate risk for AI-generated outputs, data breaches, and system failures. Coverage gaps are widening faster than precedent can close them, creating windows where liability lands on whichever party has the worse legal counsel. Risk allocation for AI outputs, privacy implications, and reliability remain active battlegrounds in rider provisions and contract amendments—often with conflicting assumptions about who bears the loss. Litigation will follow within 18 months as edge cases hit claims handlers unprepared for the gap.
Watch which insurers launch AI-specific products first; they will own the market.
Legal publishers fight for training data control
Two appellate dockets could lock in training moats for AI incumbents.
Federal courts are hearing Fastcase v. Alexi Technologies and Thomson Reuters v. ROSS Intelligence—both cases hinge on whether legal publishers retain control over caselaw used to train competing AI models [Quelle: American Lawyer]. Winners lock in moats; losers face recurring licensing costs that kill margin. Settlement odds are rising as discovery costs mount—expect confidential resolutions by fall that will reshape how legal AI startups source training data and negotiate with LexisNexis and Thomson Reuters going forward.
The outcome determines whether legal AI remains capital-light or becomes permanently tethered to incumbent publishers.
Law Firms Are Building Their Own AI Tools. Should They Share ...5 hours ago ... In June, Cooley launched Cooley Go Lab, a workspace for startups developed in collaboration with Legora on the legal AI provider's Legora Portal platform.law.com