Clients are increasingly turning to AI before they speak with outside counsel, and sometimes after, by pasting legal advice, contract language, or other work product into a public AI model to ask follow-up questions. Used thoughtfully, these tools can help clients frame questions and organize information, but an answer that sounds confident is not necessarily grounded in the facts, current law, or the company’s actual obligations. Additionally, sharing sensitive business or legal information with a public tool can raise separate confidentiality and data-handling concerns.
A familiar example is the California Consumer Privacy Act (CCPA). AI-generated privacy-policy suggestions often recommend adding CCPA disclosures, even when the business may not be subject to the law or the suggested language does not fit its practices. Adding statements about consumer rights, data uses, or processes that the company does not actually follow can create confusion and potential legal exposure; removing language counsel drafted can create its own problems. The issue is not that AI is always wrong, it is that generic answers can turn on facts the tool was never given, or cannot reliably assess.
The practical question for clients and counsel is how to use AI without letting plausible-sounding outputs become an unreviewed legal position or business commitment. That means being deliberate about what information goes into a tool, checking its sources and assumptions, and treating its output as a starting point, not a substitute for advice grounded in the company’s facts. This is a useful conversation for General Counsel and outside counsel to have together: where AI can help, where it can mislead, and what review practices make its use safer and more productive. Outside counsel, General Counsel, and AI platforms can work as an efficient, effective team if parameters and expectations are put in place.