AI is rapidly becoming part of the day-to-day infrastructure of how litigation teams research, review, and prepare cases. From natural language searches of deposition transcripts to automated chronologies and draft outlines, AI-driven tools can dramatically compress timelines and surface insights that might otherwise be missed.

However, in a profession built on confidentiality, privilege, and trust, any technology that touches client data must be held to a much higher standard. In the era of AI, data privacy and confidentiality are going to become even more important. Firms that do not have solid practices in place for handling confidential material with AI may find themselves liable if that same material ends up in a large language model, available to parties that should never have had access.

At the same time, consumers and witnesses are becoming more aware of how their data is captured and processed, whether through facial recognition, biometrics, or analytics. As that awareness grows, regulators are already moving to provide additional protection, either with new AI-specific regulations or by strengthening existing privacy frameworks. We may even face a future where consumers, witnesses, and staff have rights similar to those granted under the California Consumer Privacy Act (CCPA), but tailored to AI systems.

For legal teams, the challenge is not whether to adopt AI, but how to capture the efficiency gains without compromising confidentiality, ethics, or compliance.