Legaltech Hub

For the last three years, the defining question inside European law firms was whether to adopt artificial intelligence. Today, that question has largely been answered. New data from the European Law Firms and Legal AI 2026 survey (LTH–Lexpo 2026 Survey), conducted jointly by Legaltech Hub and Lexpo, points to a new, harder question law firms are grappling with: how to turn AI that is already deployed into AI that actually changes the economics of the business. 

New research and a legal context engineering benchmark reveal that providing AI models with context about the work they are asked to do not only increases model accuracy but can also decrease token cost through substantially better efficiency.

For years, buying legal AI meant buying seats—flat annual subscriptions that priced predictably regardless of use. That model is now under real strain. As AI platforms take on more autonomous work, the cost of running them has become far more variable, and vendors are beginning to price accordingly. At the same time, corporate clients are pushing in the opposite direction, asking for fixed fees and predictable spend on AI-assisted work. This piece traces the squeeze that opens up between those two shifts, why it is showing up in real invoices, and what firms can do about it.

AI is supposed to make legal work easier, but what happens when every efficiency gain creates room for another task, client, or tool? As legal departments race to keep up, an unexpected problem is emerging: people may not be struggling with AI itself, but with the pace of change around it. Here’s what that looks like inside legal departments and what you can do about it. 

After more than a decade trying to automate patent practice at an Am Law 100 firm, the advent of GenAI allowed two top patent attorneys to push the needle in a way they’d always wanted to. The result was Landfall IP, a scalable patent law firm built from the ground up that simultaneously offers high quality, cost savings, and faster turnaround.