Why Transactional Teams Adopt Embedded AI
Director of Innovation at large law firm on why firms adopt Harvey over Legora
AI is landing hardest in transactional law because it finally automates the most repetitive part of deal work, reading, comparing, drafting, and revising long Word documents that lawyers previously handled almost entirely by hand. That makes the gain immediate and obvious. A team can upload precedents, generate a first draft, pull clauses into tables, and redline faster, while litigation already had older e-discovery and research tools so AI feels more like an upgrade than a step change.
-
Transactional lawyers have long worked in Microsoft Word and email with little workflow software beyond templates. Contract focused products like Spellbook plug directly into Word, flag issues, apply playbooks, and edit agreements with track changes, which makes adoption easier because lawyers do not need to leave the document they are already working in.
-
Litigation was not untouched by legal tech. E-discovery and Boolean research already gave litigators software for document search, evidence review, and case research. That means AI improves speed and accessibility there, but it does not create the same from zero to one change that transactional teams are seeing.
-
This is also why specialists keep finding room beside Harvey and Legora. General assistants are useful for broad research and review, but drafting quality often improves when the tool is built around a specific practice, asks the right follow up questions, and works off the firm's own precedent set or knowledge vault.
The next phase is a split market. Broad legal AI platforms will stay important for general research, review, and firm wide visibility, but the deepest daily usage will keep concentrating in transactional workflows and practice specific drafting tools. That is where legal AI turns from an impressive demo into software attorneys open on every live deal.