Federal courts are splitting over whether generative AI outputs stay shielded in discovery. On 10 February 2026, two rulings arrived within hours yet pointed opposite directions. The civil matter, Warner v Gilbarco, protected AI material under the Work Product doctrine. Meanwhile, United States v Heppner refused any privilege for 31 Claude-generated files. These contrasting orders illuminate how judges assess confidentiality, technology, and traditional Legal tests. Consequently, litigants must monitor venue, AI platform type, and counsel involvement when preparing Evidence. Moreover, corporate teams now ask whether common consumer Tools jeopardize long-standing protections. This article unpacks the holdings, provides comparative analysis, and distills practical next steps. Additionally, it offers expert commentary and certification resources for professionals navigating evolving discovery risks. The stakes grow with every prompt sent to a model.

Divergent February Court Rulings

Judge Anthony Patti’s order in the Eastern District of Michigan stemmed from an employment retaliation suit. Importantly, the magistrate denied defendants’ bid to inspect the plaintiff’s ChatGPT drafts and prompts. Patti wrote that generative AI programs are mere Tools, not persons, so disclosure does not equal waiver. Therefore, the documents qualified as opinion Work Product reflecting mental impressions.

In contrast, Judge Jed Rakoff confronted a criminal fraud prosecution in Manhattan. Rakoff allowed prosecutors to view 31 files the defendant created through Anthropic’s consumer model, Claude. Consequently, he ruled the materials lacked attorney-client privilege and also failed the Work Product test. Rakoff emphasized public privacy policies that authorize data retention, undermining any reasonable expectation of confidentiality.

Both orders arrived on 10 February 2026 yet adopted divergent frameworks. Such split decisions fuel forum shopping and uncertainty for multinational defendants. These facts reveal an emerging doctrinal rift. However, deeper analysis shows consistent attention to tool design and disclosure risk. The next section drills into how Warner protected drafting materials.

Warner Protects Work Product

Sohyon Warner sued Gilbarco and parent Vontier without formal counsel. She relied heavily on ChatGPT to draft pleadings, motions, and interrogatory answers. Defendants demanded every prompt, intermediate output, and revision history.

Magistrate Patti applied Federal Rule 26(b)(3) and labeled the requested material classic opinion Work Product. He reasoned that no waiver occurred because Warner never shared her ChatGPT session with an adversary. Moreover, Patti likened AI to a spell-check utility rather than a human consultant.

The order referenced earlier discovery skirmishes involving proprietary model code and training data. Nevertheless, Patti found the instant request neither relevant nor proportional to the claims. Consequently, Warner v Gilbarco now stands as the first decision treating consumer AI work as protected. Warner reinforces that drafting aids remain shielded when no external disclosure occurs. However, that protection depends on strict confidentiality with the chosen platform. The criminal ruling reached the opposite endpoint.

Heppner Opens AI Evidence

Bradley Heppner used Claude to refine talking points and financial spreadsheets during government investigations. Investigators later seized the documents under a search warrant. Unlike Warner v Gilbarco, no civil claims or counterclaims shaped the privilege debate.

Judge Rakoff applied a three-part analysis focusing on privilege, Work Product, and privacy terms. He concluded Claude is not counsel, so attorney-client privilege never attached. Furthermore, the consumer service reserves rights to store and train on inputs, destroying confidentiality.

Rakoff rejected defense arguments invoking the Kovel doctrine because no lawyer instructed the AI interactions. In contrast to Warner, he deemed the defendant’s files factual Evidence open to review.

Key passages from the memorandum illustrate the reasoning:

• “Claude is not an attorney, communications with it are unprivileged.”
• “User lacked a reasonable expectation of confidentiality under the published terms.”
• “The 31 AI Documents were drafted without counsel direction, so no protection applies.”

Heppner warns practitioners that platform terms can strip crucial protections. Therefore, platform selection now drives discovery risk assessment. Companies must evaluate enterprise versus consumer offerings immediately.

Enterprise Versus Consumer Tools

Enterprise AI platforms promise contractual firewalls, encryption, and zero-training guarantees. Consequently, several firms recommend migrating sensitive Legal workflows there.

Debevoise’s alert advises documenting counsel direction and maintaining strict access controls. Proskauer calls consumer chatbots dangerous Evidence factories once litigation begins.

Moreover, experts suggest updating privilege logs to flag AI assisted documents clearly. Professionals can deepen expertise via the AI+ Design Strategist™ certification.

The following checklist summarizes immediate steps:

1. Select enterprise Tools with written non-training clauses, following Warner v Gilbarco guidance.
2. Train staff about privilege dangers of consumer models.
3. Record counsel oversight for any AI drafting, echoing Warner v Gilbarco best practices.
4. Store AI outputs securely under access controls.

These actions reduce privilege waiver risk and improve litigation readiness. However, governance must evolve as jurisprudence shifts. Next, we translate the rulings into actionable counsel guidance.

Practical Guidance For Counsel

First, map every workflow that injects client data into AI Tools. Subsequently, classify each platform by privacy commitments and server location.

Second, embed step-by-step instructions in existing Legal hold notices. Moreover, craft internal FAQs explaining why certain prompts may create discoverable Evidence.

Third, update engagement letters to authorize enterprise AI and forbid consumer alternatives without approval. Nevertheless, leave flexibility for rapid technological advances.

Fourth, coordinate with cybersecurity to monitor API logs that could reveal inadvertent disclosures. Consequently, counsel can detect and remediate privilege threats early. Courts after Warner v Gilbarco may apply identical reasoning to email assist bots.

Proactive governance aligns business agility with courtroom defensibility. Therefore, counsel should circulate revised playbooks this quarter. Attention now turns to emerging appellate activity.

Monitoring Future Legal Shifts

Neither Warner nor Heppner sits before an appellate panel yet. However, the losing parties may seek review, offering needed clarity.

Observers expect the Sixth Circuit to weigh proportionality strongly if Warner v Gilbarco reaches appeal. In contrast, Second Circuit precedent on technology privacy could affirm Rakoff’s analysis.

Meanwhile, Congress and regulators are drafting reporting rules on AI training data usage. Consequently, statutory changes could influence future privilege expectations.

Litigation funding entities also track rulings because AI cost controls affect case valuation. Moreover, insurance carriers may condition coverage on enterprise AI adoption. Corporate counsel repeatedly cite Warner v Gilbarco during policy negotiations with carriers.

Appellate outcomes and legislation will reshape discovery arguments rapidly. Therefore, professionals must remain vigilant and adaptive. We close with central lessons and an invitation to act.

Conclusion And Next Steps

Recent cases sketch a moving target for AI discovery. Warner v Gilbarco shows robust protections when confidentiality holds. Heppner, however, exposes fatal weaknesses in consumer platforms. Consequently, platform choice now equals risk choice. Counsel should audit workflows, harden privilege protocols, and shift drafting to enterprise environments. Moreover, technologists must brief leadership on privacy term changes. Proactive teams will refine training, adjust logs, and monitor appellate dockets continuously. Therefore, explore leading certifications and stay ahead in this pivotal Legal transformation. Start today by reviewing the AI+ Design Strategist™ pathway and future-proofing your practice.