AI-Related Class Action Lawsuits are Becoming More Common

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AI-related class action lawsuits are becoming more common at a pace that outstrips almost every other litigation trend in the market. For CFOs, general counsel, and investor relations teams, the numbers are hard to ignore. AI has reshaped how public companies talk about growth, risk, and innovation, and it's now reshaping the litigation landscape too.

Securities Class Action Filings Are Surging

Overall securities class action filings in federal and state courts jumped to 121 in the first half of 2026, up sharply from 93 in the second half of 2025 and modestly ahead of the 114 filed in the first half of last year. That's the highest semiannual total in years, and it's well above the historical average of roughly 113 filings per half-year going back to 1997.

Within that broader wave, AI litigation is doing a disproportionate share of the driving. There were 15 AI-related federal court filings in the first six months of 2026 alone, nearly matching the 16 filed across all of 2025. If the current pace holds, 2026 could see roughly double last year's total, making AI easily the most active litigation trend Cornerstone Research tracks, ahead of cryptocurrency, cybersecurity, and even COVID-19-related matters (which, notably, had zero new filings in the period).

Why Investor Lawsuits Involving AI Are Increasing

The reasoning behind the spike is fairly intuitive. AI has become the growth story that public markets reward most aggressively, which means AI-linked stocks often trade on very high expectations. When a company tied to AI misses those expectations, or when a disclosure suggests the story isn't playing out as promised, share prices can fall hard and steep. Sudden drops are exactly the kind of event that tends to trigger shareholder litigation. Cornerstone Research's Sasha Aganin has pointed out that when a fast-growing company hits a setback, the resulting share-price decline can be significant enough to invite a class action.

In short, the more capital and enthusiasm that flows into AI companies, the more legal risk builds around any disclosure that disappoints the market.

AI Development, Infrastructure, and Data Centers Lead the Filings

Not all AI lawsuits look alike. Of the 15 AI-related core federal filings in the first half of 2026, the largest group (seven filings) centered on AI development. This means the allegations tied directly to how a company built or represented its AI models and algorithms. Five filings involved data center litigation, reflecting the enormous capital being poured into physical AI infrastructure. Four filings touched on AI infrastructure and AI hardware more broadly, including claims connected to computing capacity and chip supply, and three of those overlapped with data center allegations.

Notably absent this period: autonomous vehicle-related AI filings, which had appeared in prior years but produced none in the first half of 2026. Every single AI-related filing included a claim under Section 10(b) of the Securities Exchange Act of 1934, and only one also carried a Section 11 claim, underscoring that these are overwhelmingly fraud-based securities claims rather than registration-related disputes.

Which Technology Companies Are Most Exposed?

The technology sector absorbed the brunt of this activity. Filings against tech companies jumped from nine in the second half of 2025 to 24 in the first half of 2026 (roughly twice the sector's 1997–2025 historical average) largely because of the AI surge. Most of these cases landed in two courts in particular: the Second Circuit (covering New York) and the Ninth Circuit (covering California), which together accounted for 70% of all core federal filings during the period.

That concentration matters for technology litigation strategy. Companies headquartered in these jurisdictions, or that raise capital through New York- or California-based exchanges, should expect heightened scrutiny of how they characterize AI capabilities, timelines, and risk in their public disclosures.

Disclosure Dollar Loss Tells the Bigger Story

The financial stakes behind these filings are enormous. Disclosure dollar loss (the drop in a defendant's market value tied to the end of a class period) reached $529 billion in the first half of 2026, up 77% from the prior half-year and nearly matching the all-time high set in early 2022. AI-related cases made up only 13% of all core filings but accounted for 73% of that total dollar loss, a clear sign that when AI-linked disclosures go wrong, the market reaction is outsized.

Maximum dollar loss, a broader measure of market capitalization decline during a class period, climbed to $1.858 trillion. This is nearly three times the historical semiannual average. "Mega" filings, those involving losses of at least $5 billion, made up 85% of total disclosure dollar loss for the period, the third-highest share ever recorded.

Other Litigation Trends Worth Watching

AI isn't the only story shaping litigation trends this year, but it is the dominant one. A few other patterns stand out:

Non-U.S. issuers are facing a growing share of federal securities litigation, with filings against foreign companies on pace to more than double 2025's total, driven in part by so-called "pump-and-dump" allegations.
Securities fraud claims tied to tariff policy and private credit arrangements involving business development companies have also emerged as smaller but notable trends since late 2025.
Cryptocurrency-related filings are on pace for their lowest annual total since 2019, and cybersecurity-related filings dropped to zero for the first time since 2016, suggesting plaintiffs' attorneys are redirecting their attention toward AI.

What This Means for Risk Management and Compliance

For companies developing, deploying, or heavily promoting AI capabilities, this data is a signal to revisit compliance and disclosure practices now rather than after a lawsuit arrives. A few practical takeaways for regulatory compliance and litigation risk teams:

Align public statements with technical reality. Claims about AI development timelines, model performance, or infrastructure capacity should be reviewed carefully before they reach investors, since overstated AI narratives are precisely what plaintiffs' firms are targeting.
Treat data center and infrastructure disclosures as investor-facing risk. Capital commitments tied to AI hardware and data centers are increasingly scrutinized, so cost overruns, delays, or capacity shortfalls deserve the same disclosure rigor as core financial results.
Watch jurisdiction exposure. Companies with significant investor bases or operations tied to the Second and Ninth Circuits should factor that heightened litigation activity into their risk management planning.
Expect Section 10(b) to remain the primary vehicle. Nearly every AI-related filing tracked by Cornerstone Research relied on Section 10(b) fraud claims, which typically hinge on whether a statement was materially misleading when made. This is a standard that puts a premium on precise, well-supported disclosure language.