Legal briefings

Case law, analysis, and governance references

The first wave of decisions on AI privilege — now spanning federal and state courts — establishes a clear pattern: process design, attorney direction, and confidentiality posture determine whether AI-assisted work is protected. This page tracks the primary sources that inform Saidebar architecture.

Executive summary

Privilege is process-dependent

Courts evaluate who directed the AI use, for what purpose, and whether confidentiality was preserved. Attorney involvement at the front end is the key differentiator.

Workflow controls matter more than model choice

Enterprise buyers need supervision, review, and governance built into the operating path. Model performance alone is not a defensible position.

Policy pressure is increasing

Multiple states are evaluating restrictions on AI legal and medical advice. Governance-ready systems become a procurement and regulatory advantage.

Latest updates

Activity is accelerating: a new state-court work-product ruling (June 3), a third federal decision, and the first state attorney general lawsuit against OpenAI.

Tate Group Automotive v. Legacy Automotive Capital (Tex. Bus. Ct. Jun. 3, 2026) is the newest decision and the first from a state court. It protected a non-lawyer principal’s ChatGPT conversations as work product but ordered disclosure of every discovery document fed into the tool, reinforcing that the fact and scope of AI use are discoverable even when the content is shielded.

Morgan v. V2X, Inc. (D. Colo. Mar. 30, 2026), cited as 2026 WL 864223, is the third federal decision on AI and discovery. The court protected a pro se litigant’s AI-assisted work product but ordered disclosure of the AI tool’s identity, and imposed an AI-specific protective order requiring contractual safeguards before any confidential material is entered into an AI platform. Among the federal courts — Heppner, Warner, and Morgan — there is still no consensus on whether attorney direction is required.

State of Florida v. OpenAI (Fla. 10th Judicial Circuit, June 1, 2026) is the first state attorney general action against OpenAI and CEO Sam Altman. The complaint alleges the company concealed serious risks in ChatGPT — including content that drove users toward self-harm and violence — and pleads deceptive trade practices, negligence, strict liability, and public nuisance, seeking to hold Altman personally liable. It signals escalating enforcement pressure on unsupervised consumer AI, the exact exposure attorney-supervised channels are designed to contain.

The leading privilege authority remains United States v. Heppner (S.D.N.Y. Feb. 17, 2026), 2026 WL 436479, with Warner v. Gilbarco (E.D. Mich. Feb. 10, 2026) as the counterpoint. The practical takeaway is unchanged: privilege and work-product outcomes are process-dependent.

Primary case materials

Federal decisions that directly address AI privilege, work product, and discovery.

Privilege

United States v. Heppner

S.D.N.Y., Feb 17, 2026

A represented defendant used Claude AI to draft defense strategies without attorney direction. The court held that privilege did not attach because no attorney was involved at the front end, the AI platform is not an attorney, and the platform’s privacy policy permitted data disclosure. Reuters coverage cites the opinion as 2026 WL 436479. The court noted that attorney-directed AI use may have preserved a privilege claim.

Takeaway: Consumer AI use outside counsel direction can undercut both privilege and work product arguments. Process and direction matter.

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Work product

Warner v. Gilbarco

E.D. Mich., Feb 10, 2026

A pro se plaintiff used AI tools in litigation preparation. The court protected the materials as work product, rejecting the argument that AI platform use constituted waiver. The court emphasized that the plaintiff was the party, and her internal analysis and mental impressions were protected.

Takeaway: Work product outcomes are fact-specific. Process design, party status, and the nature of materials drive discovery results.

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Work product

Morgan v. V2X, Inc.

D. Colo., Mar 30, 2026

The third federal decision to address AI and discovery. Magistrate Judge Dominguez Braswell held that a pro se litigant’s AI-assisted preparation is protected work product under Rule 26(b)(3), but that the identity of the AI tool used is not protected and ordered its disclosure. The court also imposed an AI-specific protective order barring confidential information from any AI platform unless the provider is contractually prohibited from training on inputs or disclosing them to third parties, and permits deletion on request. Cited as 2026 WL 864223.

Takeaway: Even where work product holds, the choice of AI tool can be discoverable, and confidential material may not be entered into consumer AI absent enforceable contractual safeguards — precisely the controls Saidebar builds into the workflow.

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Work product

Tate Group Automotive v. Legacy Automotive Capital

Tex. Bus. Ct., 11th Div., Jun 3, 2026

The newest decision and the first from a state court. After an in camera review, Judge Dorfman held that a non-lawyer principal’s ChatGPT conversations prepared in anticipation of litigation are protected work product under Tex. R. Civ. P. 192.5(a)(1), and that using the tool did not waive protection. As in Morgan, the court still ordered the party to disclose, by Bates number, every discovery document it had fed into ChatGPT — including material designated confidential under the protective order — and invited the parties to amend that order to govern AI use. Cause No. 25-BC11B-0020.

Takeaway: Aligning with Warner and Morgan and splitting from Heppner, courts increasingly protect AI-assisted work product but treat the fact and scope of AI use as discoverable. Feeding confidential discovery into consumer AI can itself breach a protective order.

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Discovery

Tremblay v. OpenAI

N.D. Cal., June 24, 2024

In a discovery dispute, the court compelled production of AI prompts, outputs, account settings, and testing process. The court held that placing a subset of test results in the complaint waived work product protection over related negative results.

Takeaway: AI prompts, outputs, and testing process can become central evidence in litigation. Account settings and interaction history are discoverable.

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Analysis and market context

Secondary sources explaining why attorney-supervised AI workflows are accelerating.

Reuters: AI tools as third-party disclosure risk

Recent legal analysis of United States v. Heppner emphasizing that uploads to public AI platforms may be treated as third-party disclosure, undermining confidentiality and privilege.

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JD Supra: A Tale of Two Cases

Comparative analysis of Heppner and Warner, framing practical implications for corporate counsel and best practices including employee policies, litigation hold updates, and closed AI tool requirements.

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Bond, Schoeneck & King: No Counsel, No Privilege

April 2026 practitioner alert framing Heppner as a warning that unsupervised client-side AI use may fall outside attorney-client privilege.

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Blakes: AI and legal privilege practical considerations

April 2026 practical guidance for in-house teams and firms on preserving confidentiality and privilege posture in AI-assisted legal workflows.

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Missouri Lawyers Media: Heppner discovery risk summary

Concise April 2026 coverage of Heppner focused on litigation and discovery exposure when AI interactions are outside attorney-directed channels.

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Mintz: Three Courts, No Consensus on GenAI privilege

Comparative analysis of Heppner, Warner, and Morgan, noting an emerging split over whether attorney direction is required for protection, and the open question of how courts will treat a represented party who uses AI without counsel.

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Law.com: Florida becomes the first state to sue OpenAI

Coverage of State of Florida v. OpenAI (June 1, 2026), the first state attorney general action against OpenAI and Sam Altman. The state alleges OpenAI concealed serious risks in ChatGPT — including content that drove users toward self-harm and violence — and seeks to hold Altman personally liable. A marker of accelerating enforcement pressure on consumer AI.

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Standards and governance

Professional duty and risk management frameworks that inform our operational approach.

Fed. R. Civ. P. 26

Federal discovery rules and work product doctrine framework.

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ABA Model Rule 1.6

Confidentiality of information and duty to prevent unauthorized disclosure.

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ABA Formal Opinion 512

National ethics framework for lawyers using generative AI: informed client consent before confidential data enters self-learning tools, plus competence and supervision duties.

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NIST AI Risk Management Framework

Federal framework for trustworthy AI controls, risk management, and governance.

View reference

Policy watchlist

We are monitoring legislative proposals across multiple states, including New York and Maryland, where stakeholders are advocating restrictions on AI legal and medical guidance.

Enforcement is also escalating: on June 1, 2026, Florida became the first state to sue OpenAI and its CEO under consumer-protection and public-nuisance theories, and practitioners expect further state-led actions to follow.

On the ethics side, ABA Formal Opinion 512 and guidance from more than 35 state bars now require lawyers to vet AI data-handling and obtain informed client consent before entering confidential information into self-learning tools — obligations that favor attorney-supervised channels with enforceable vendor confidentiality terms.

Our position: preserve responsible public access to research tools while requiring stronger safety engineering, transparent disclosure, and professional supervision for higher-risk usage. As specific bill numbers and committee materials become available, they will be tracked here.

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