Key Takeaways from Both Decisions

AI Tools Are Not Lawyers. Both courts agreed that communications with AI platforms cannot, on their own, establish attorney-client privilege. No lawyer-client relationship exists and AI platforms usually expressly disclaim that they provide legal advice.
Consumer AI and Confidentiality: A Divided Landscape. Under Heppner, consumer AI platforms that reserve rights to collect user inputs, train models on submitted data and disclose information to third parties destroy any reasonable expectation of confidentiality. Judge Rakoff likened sharing information with such a platform to discussing legal strategy in a public space. In contrast, the Warner court characterized generative AI platforms as tools rather than persons, holding that disclosure to an AI tool does not constitute a waiver of privilege. Waiver, the court emphasized, requires disclosure to an adversary or someone likely to transmit material to an adversary.
Privilege Cannot Be Applied Retroactively. Sharing non-privileged, AI-generated documents with counsel after they are created does not transform them into privileged materials. Confidentiality must exist at the time of creation. This principle was applied in Heppner and remains a foundational rule.
Work-Product Protection: Counsel Involvement Matters. In Heppner, the absence of attorney involvement in the creation of AI-generated materials was fatal to the defendant’s work-product claim. The court noted that the outcome might have been different had counsel directed the defendant to use the AI tool. By contrast, in Warner, the court extended work-product protection to the plaintiff’s AI materials, emphasizing that such materials reflect the litigant’s mental impressions and litigation strategy, regardless of whether counsel was involved. The court also criticized the defendant’s request for these materials as a “fishing expedition” into the plaintiff’s internal thought process.
AI Interactions May Be Discoverable ESI. Under Heppner, courts may treat AI prompts, outputs and activity logs as ordinary electronically stored information (ESI) subject to discovery. Opposing counsel may now routinely request “AI prompts and outputs” in discovery. However, the Warner decision suggests that such requests may be denied as disproportionate or as attempts to obtain protected mental impressions.
Heppner: A Slippery Slope? Litigants seeking to leverage the reasoning of the court in Heppner regarding the confidentiality element of attorney-client privilege may face challenges due to the potential floodgates opened by such reasoning. On its face, the logic underpinning the decision could be extended to virtually any online or SaaS-based digital communication platform routinely used by clients, including Gmail and the cloud-based versions of Outlook and Microsoft Teams. Similar to the privacy policy at issue in Heppner, these platforms’ privacy policies often include terms that allow for the collection of user data for operational purposes and permit disclosure to governmental authorities under certain conditions. If broadly applied, the reasoning in Heppner could lead to a conclusion that the use of such services inherently eliminates confidentiality, effectively undermining the foundation of attorney-client privilege in the digital age. However, such an expansive interpretation is unlikely to gain widespread judicial acceptance, as it would disrupt modern legal practice and create untenable consequences for privilege protections.
Governance Remains the Differentiator. Enterprise-grade AI platforms with contractual confidentiality protections, deployed under counsel’s direction, may present a different analysis. The key factors are supervision, purpose and reasonable confidentiality expectations. The court in Heppner explicitly left open the possibility that enterprise tools with confidentiality guarantees could support a stronger privilege argument.

AI and Legal Privilege: Lessons from the Heppner and Warner Rulings in the United States

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