The AI Privilege Problem Is Control, Not Code: EDiscovery Best Practices

Key Takeaways

• AI hallucinations identified in over 1,000 global incidents.
• UK Munir case flags privilege risks of feeding confidential data to AI.
• US Heppner ruling treats public AI communications as non‑privileged.
• Legal teams must assess data flow, access, and usage terms before AI.
• Five critical questions guide AI confidentiality controls for law firms.

Pulse Analysis

Artificial intelligence is reshaping legal research, document review, and client counseling, but its rapid adoption has outpaced risk management. While AI hallucinations—fabricated citations or authority—have been documented in more than a thousand incidents worldwide, a subtler danger is emerging: the inadvertent disclosure of privileged material to cloud‑based models. The 2026 Munir decision in the United Kingdom marked the first explicit judicial warning that feeding confidential data into AI tools can jeopardize attorney‑client privilege, echoing the United States v Heppner ruling that public AI interactions are not protected. Both cases pivot the conversation from the underlying code to the governance of data inputs.

The distinction between "code" and "control" forces law firms to treat AI platforms as third‑party processors subject to strict contractual and technical safeguards. Effective controls include data minimization, encryption at rest and in transit, and clear vendor terms that prohibit model training on client content. Firms must also audit where data is stored, who can retrieve it, and how long it is retained. By embedding these safeguards into existing information governance frameworks, legal departments can mitigate the risk of privilege loss while still harnessing AI’s efficiency gains.

Practitioners seeking to adopt AI responsibly should start by answering five essential questions: (1) What specific data will be uploaded? (2) Where will the data reside and who can access it? (3) What contractual clauses govern its use and deletion? (4) How does the provider ensure model isolation to prevent cross‑client contamination? (5) What incident‑response procedures exist for accidental disclosures? Addressing these queries creates a defensible audit trail and aligns AI usage with professional ethical standards. As courts continue to shape the privilege landscape, proactive control measures will become a competitive differentiator for forward‑looking law firms.