Law firms that need AI document review should keep the pipeline inside their own infrastructure or a provider with strict data residency, not on platforms whose terms of use can quietly expand to cover model training. The Meta episode this week is a reminder that platform language shifts and client files should never depend on a vendor's goodwill.
Meta had added a line to its commercial terms allowing the company to use any content from a business account's domains, web pages, or URLs to train and improve its products. Legal experts flagged this to TechCrunch and Nieman Lab as a remarkably broad grant. Meta then removed the language and said it only applied to ads and business products, and that nothing changed in how it crawls the web.
What it means for small business automation
If your workflow sends contracts, invoices, or client data through a third-party cloud, re-read the terms every quarter - they get rewritten and nobody emails you about it. For legal and finance work I build on self-hosted n8n plus LLM calls with explicit no-training clauses, or fully local models when the client requires it; same approach as in a legal archive audit pipeline I built, where contradictions across 1000+ files are found without sending documents outside the firm.
Why it matters: Terms of service are policy, not technology, and policy can change overnight. If your automation depends on data staying private, the architecture - not the vendor's statement - has to enforce it.
Source: TechCrunch