AI Securities Class Actions Tracker (2024-2026)

Overview and trajectory

AI-related securities class actions began appearing in 2023 and accelerated meaningfully in 2024 and 2025. Industry tracking reports approximately a 100% year-over-year increase in AI-related cases from 2023 to 2024, with continued growth through 2025 and into 2026. The trajectory is recognizable as the early phase of a new litigation category, comparable to the cybersecurity-related litigation arc that began in the mid-2010s.

The driver of this growth is straightforward. Companies are making increasingly bold claims about AI capabilities, AI use, and AI-driven business outcomes. Some of those claims are durable and accurate. Others are not. The plaintiffs' securities bar has developed AI-specific expertise and is systematically filing cases where representations cannot be substantiated. Parallel SEC enforcement, organized through the new Cybersecurity and Emerging Technologies Unit (CETU), has created reinforcing public pressure on companies to substantiate AI claims.

For directors and officers, the implication is clear. The AI litigation wave is real and growing, the legal theories are being tested in courts, and the cases that survive motions to dismiss are creating precedent that will guide subsequent filings. This tracker catalogs notable cases through May 2026 and will be updated quarterly.

Methodology

Cases are identified through several sources:

• Stanford Securities Class Action Clearinghouse
• Cornerstone Research annual securities class action reports
• SEC press releases and litigation releases
• Specialized securities-litigation databases (PACER, Bloomberg Law)
• Practitioner reporting in legal trade publications

Inclusion criteria: cases where AI-related allegations are central to the claim, including AI washing, AI capability misrepresentation, AI risk-disclosure failures, and AI-related fraud. Cases that mention AI peripherally without AI being central to the allegation are excluded.

The tracker emphasizes cases that have produced precedential rulings (motion to dismiss decisions, summary judgment, settlement approvals) and SEC enforcement settlements over generic case filings without dispositive activity.

Case patterns and legal theories

AI-related securities cases fall into four patterns:

Pattern 1 — AI washing (capability misrepresentation)

Allegations that the company has overstated its AI capabilities, AI use, or AI-driven results in periodic reports, earnings calls, investor presentations, or fundraising materials. These cases generally allege violations of Section 10(b) of the Securities Exchange Act and Rule 10b-5. The SEC's enforcement framework for AI washing under the Investment Advisers Act provides parallel regulatory authority for cases involving registered investment advisers.

Pattern 2 — AI risk disclosure failures

Allegations that the company failed to disclose material AI-related business risks. The Reddit class action filed in June 2025 illustrates this pattern: the allegation is that Reddit failed to disclose the impact of Google's AI Overviews search feature on Reddit's traffic and advertising revenue. This pattern is structurally different from Pattern 1 (which involves affirmative misrepresentation) — the AI risk disclosure pattern involves alleged omissions rather than misstatements.

Pattern 3 — AI-driven adverse events

Allegations of securities fraud arising from specific AI failures or AI-related adverse events. This pattern includes cases where AI products have malfunctioned, caused customer harm, or triggered regulatory action, and where the resulting decline in company value is alleged to have been foreseeable to officers and directors.

Pattern 4 — Caremark derivative actions

Derivative claims alleging that directors failed in their Marchand-style oversight duty, leading to AI-related harm. As of May 2026, no AI-specific Caremark claim has produced a published decision permitting the case to proceed past a motion to dismiss, but the theory is being actively developed by plaintiffs' counsel and is expected to produce its first successful pleadings in 2026-2027.

SEC enforcement actions

The SEC has built a small but consequential AI washing enforcement docket since 2024. Key actions:

February 2024 — Brian Sewell / Rockwell Capital Management

The SEC settled charges against Brian Sewell and his company, Rockwell Capital Management, for raising $1.2 million for a fund purportedly using AI and machine learning for cryptocurrency trading. The SEC alleged the AI and machine learning technology did not exist. Settlement: $1,602,089 in disgorgement and prejudgment interest from Rockwell Capital Management; $223,229 civil penalty from Sewell.

March 2024 — Delphia (USA) Inc.

The SEC settled charges against Delphia for false and misleading statements about its use of AI in investment processes. Delphia falsely claimed to be the "first regulated AI financial advisor" and misrepresented that its platform provided "expert AI-driven forecasts." Settlement: $225,000 civil penalty plus censure and cease-and-desist order. This was one of the SEC's first explicit AI-related enforcement actions.

March 2024 — Global Predictions, Inc.

Companion action to the Delphia settlement. The SEC alleged Global Predictions made false and misleading statements about its use of AI in investment processes, in SEC filings, in press releases, and on its website. Settlement: $175,000 civil penalty plus censure and cease-and-desist order.

January 2025 — Presto Automation Inc.

The SEC's first AI washing enforcement action against a public company. Presto Automation, formerly listed on Nasdaq, allegedly misrepresented the capabilities of its AI-powered restaurant ordering technology. The SEC alleged that Presto falsely claimed its system eliminated the need for human intervention when in fact the vast majority of orders required human handling. The SEC also noted the AI speech recognition technology was owned and operated by a third party, contrary to Presto's marketing.

April 2025 — Albert Saniger / Nate, Inc.

The SEC and DOJ jointly charged Albert Saniger, founder of Nate Inc., for fraudulently raising more than $42 million from investors by falsely claiming Nate's mobile shopping app used AI to complete purchases automatically. In reality, transactions were processed manually by overseas contractors. The case represents the highest-profile AI fraud action to date and is proceeding as both civil enforcement and criminal prosecution.

Notable securities class actions

Apple — Tucker v. Apple Inc. et al. (June 2025)

Filed in the U.S. District Court for the Northern District of California, Case No. 25-05197. Plaintiffs allege Apple's June 2024 Worldwide Developers Conference led the market to believe that AI would be a key driver of the iPhone 16 through the unveiled "Apple Intelligence" initiative. The complaint alleges that Apple's AI claims amounted to securities fraud once the company's actual AI readiness (or lack thereof) was disclosed to the market. As of May 2026, the case is in early stages.

GitLab Inc.

Securities class action alleging GitLab made misleading statements about its AI capabilities, claiming AI could optimize its product and increase market share. The case is part of the early wave of public-company AI washing actions targeting representations about AI-driven business outcomes.

Reddit (June 2025)

Securities class action filed against Reddit alleging risk disclosure failure rather than capability misrepresentation. The complaint alleges Reddit failed to disclose how Google's introduction of AI-powered search features (AI Overviews) reduced Reddit traffic, given Reddit's heavy reliance on Google search referrals. The "zero-click" dynamic allegedly materially reduced Reddit's traffic and advertising revenue without timely disclosure. This case is structurally important as an example of Pattern 2 (risk disclosure) rather than Pattern 1 (capability misrepresentation).

DocGo Inc.

Mobile healthcare provider whose securities case proceeded past a motion to dismiss in March 2025 in the Southern District of New York. Plaintiffs alleged DocGo misled investors regarding its "proprietary central AI system" that purportedly managed complex logistics operations. The court denied DocGo's motion to dismiss, in part because plaintiffs alleged the company falsely represented that the CEO held a master's degree in computational learning theory — a credential tied to claimed AI expertise. The court rejected DocGo's argument that educational misrepresentation was immaterial.

C3.ai, Inc.

Securities class action filed in August 2025 alleging that C3.ai misled investors about the adoption and performance of its AI technology. C3.ai is among the most prominently AI-positioned public companies, making it a natural target for AI washing claims.

Elastic N.V.

Securities class action filed in early 2025 alleging that Elastic executives overstated AI integration in the company's products. Part of the broader pattern of public-company AI washing cases.

Innodata, Inc.

Federal securities class action against the data engineering firm after Wolfpack Research published a report describing Innodata's AI claims as "smoke and mirrors." Innodata's stock allegedly dropped over 30% following the report. The case illustrates the role of activist short sellers in surfacing AI washing claims that plaintiffs' counsel then convert into class actions.

Caremark derivative actions

AI-specific Caremark derivative actions have not yet produced successful pleadings as of May 2026. However, the Marchand framework applies cleanly to AI risk: the Marchand standard requires directors to establish information systems for monitoring mission-critical compliance, and AI has reached mission-critical status at most public companies given the converging factors of regulation, litigation, SEC enforcement, and operational centrality.

Plaintiffs' counsel are expected to file AI-specific Caremark actions in 2026-2027 as specific AI failures provide factual predicates for the bad-faith pleading standard. Directors should not interpret the absence of successful AI Caremark claims as evidence the theory will fail; the trajectory of comparable theories (cybersecurity, food safety, drug safety) suggests AI Caremark exposure will materialize.

The SEC Cybersecurity and Emerging Technologies Unit

In 2025, the SEC's Enforcement Division reorganized its technology-focused work under the new Cybersecurity and Emerging Technologies Unit (CETU), which absorbed and expanded the predecessor Crypto and Cyber Unit. CETU has identified AI washing as an immediate enforcement priority. Speaking at the Securities Enforcement Forum West 2025, senior CETU officials reiterated that AI washing — materially false and misleading statements about AI capabilities — is a sustained focus, not a passing concern.

CETU's priority signals for AI-related enforcement include:

• Investment adviser representations about AI in investment processes
• Public-company representations about AI capabilities
• Disclosures about AI in periodic reports and registration statements
• Marketing rule compliance for AI-related claims
• Books and records requirements supporting AI representations

Companies should expect continuing SEC enforcement activity in 2026 and beyond, with the cases used to build precedent that informs both subsequent enforcement and parallel private litigation.

Implications for D&O underwriting

The AI litigation landscape is shaping D&O underwriting in several ways. Carriers are using the case data to inform pricing models, design AI-specific exclusions and sublimits, and structure renewal questionnaires that probe for the kinds of representations and oversight failures that have produced cases.

Specific underwriting implications:

• AI-related claims sublimits have appeared at $5-25 million in 2025-2026 renewals, particularly for companies with weak AI governance documentation
• "AI washing" exclusions have appeared in some renewals, carving out coverage for claims arising from AI capability misrepresentations
• Premium increases of 15-40% for companies unable to demonstrate AI governance maturity
• Narrower coverage at higher attachment points for excess D&O layers, with primary carriers absorbing more AI-related risk
• Renewal questionnaires systematically probing for the specific risk factors that have produced cases (see D&O Underwriting Questions for AI Governance reference)

Implications for board oversight

For directors, the litigation pattern produces several practical implications:

1. AI representations require disclosure-level rigor

Statements about AI capabilities, AI use, and AI-driven results in SEC filings, earnings calls, investor presentations, and marketing materials should be treated with the same rigor as financial disclosures. The disclosure committee should specifically review AI representations.

2. Documented oversight is now table stakes

Boards that cannot point to a documented AI oversight program face increased risk of Caremark exposure as plaintiffs adapt the Marchand framework to AI. The documentation should include policy, committee oversight, regular reporting cadence, and incident response infrastructure.

3. Risk disclosure failures are emerging as a discrete category

The Reddit case demonstrates that risk disclosure failures (Pattern 2) are a discrete and growing category, distinct from capability misrepresentation (Pattern 1). Boards should ensure that AI-related business risks — including risks from competitive AI products, AI-driven changes in customer behavior, and AI-related regulatory exposure — are properly disclosed in 10-K and 10-Q risk factor sections.

4. Independent review is increasingly defensive

Independent advisory review of AI compliance posture serves multiple defensive purposes: it informs board oversight, supports D&O renewal documentation, and creates a defensive record in the event of a future Caremark or securities claim. The cost of independent review is increasingly small relative to the risk it mitigates.

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This tracker is updated quarterly. For the most recent case filings and dispositions, see the date stamp at the top. Companion reference pages cover AI Risk and D&O Liability for Directors and D&O Underwriting Questions for AI Governance. Boards seeking organization-specific compliance review may find the Multi-Jurisdictional AI Compliance Review or Board & Committee Briefings services useful.