InicioAI Use-Case Library › AI in Legal: 5 real deployments

AI in Legal: 5 real deployments

Named Legal organisations and what they run, grouped by business function.

5deployments
4in production or with results
2with a reported outcome
0halted or reversed
Aug 30, 2026last updated

Legal work 5 deployments

Cleary Gottlieb

piloting Gemini Enterprise for Legal with contract-review and regulatory-scanning skills and pre-built agents

Pilot Aug 25, 2026 Gemini Enterprise for Legal Legal and document work Source: unite.ai
Thomson Reuters

Deployed proprietary Thomson LLM trained on Westlaw, Practical Law, Checkpoint and Reuters content inside CoCounsel Legal's Tabular Analysis feature for law firms and corporate legal departments

In production Aug 24, 2026 Thomson, CoCounsel Grounded knowledge assistants Source: thomsonreuters.com
Harvey

Deployed Harvey II legal AI platform featuring Memory that learns individual lawyer drafting style across Harvey, Word and Outlook, and Tenet, an in-house proprietary legal model trained on mock disputes and case files using a version of Moonshot's Kimi K3

In production Aug 18, 2026 Harvey II, Tenet Legal and document work Source: artificiallawyer.com
Knighthawk Engineering

Expert witness Josh Autenrieth used ChatGPT to produce approximately 85-90% of an expert report defending 3M in the Watson Grinding fatal explosion lawsuit, prompting it to show 3M is at zero fault

Reported: Jury awarded plaintiffs $61M assigning 30% fault to 3M; 350 pages of ChatGPT prompts entered discovery and were used to impeach the expert witness at trial

Results reported Aug 17, 2026 ChatGPT Legal and document work Source: 404media.co
Thomson Reuters

Thomson Reuters is deploying AI across legal, tax and regulatory workflows while reshaping its engineering organization.

Reported: The company confirmed up to 500 engineering layoffs and plans to hire more than 250 net-new, mostly senior AI-native engineers over two years.

Results reported Jul 14, 2026 Legal and document work Source: The Next Web

Every entry names the organisation and links its source. Outcome figures are quoted as reported, never estimated. Vendor announcements without a named customer are excluded. Halted and reversed deployments are kept on purpose.