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.
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.
View documentWarner 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.
View documentMorgan 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.
View documentTate 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.
View documentTremblay 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.
View documentAnalysis 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.
Read analysisJD 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.
Read analysisBond, 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.
Read analysisBlakes: 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.
Read analysisMissouri 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.
Read analysisMintz: 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.
Read analysisLaw.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.
Read analysisStandards and governance
Professional duty and risk management frameworks that inform our operational approach.
ABA Model Rule 1.6
Confidentiality of information and duty to prevent unauthorized disclosure.
View referenceABA 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.
View referenceNIST AI Risk Management Framework
Federal framework for trustworthy AI controls, risk management, and governance.
View referencePolicy 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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