Client Confidentiality & Model Privacy: Are You Feeding the Machine?

Attorney–client privilege and confidentiality are cornerstones of legal practice. But when lawyers paste client details into public AI tools, they may be exposing sensitive information to third parties — and even to future users of the same system.

How public AI tools handle data

Many free or consumer-grade AI tools retain prompts and responses. Some use them to train their models. That means client names, facts, or strategies could end up in a dataset outside the lawyer’s control.

Why this matters for privilege

If privileged information is disclosed to a third party without safeguards, courts may treat it as a waiver of privilege. Even accidental disclosure can undermine legal protections and damage client trust.

Data residency and vendor terms

AI vendors may store data in different jurisdictions, each with its own privacy laws. Without clear agreements, lawyers may not know where data is stored, how long it is retained, or who can access it.

Safer practices for lawyers

1. Don’t paste sensitive client details into public AI tools.
2. Use enterprise versions with privacy guarantees (e.g., no training on your data, private storage).
3. Review vendor terms for confidentiality, retention, and jurisdiction rules.
4. Consider internal deployments for highly sensitive work.

Takeaway

Confidentiality is not optional. Public AI tools may be convenient, but without strong privacy protections, they can put privilege at risk. The safest path is to keep client data out of consumer-grade AI entirely.