AI Lawsuits Double to 75 in 2026, Force Compliance Over Compute

The dramatic rise in AI lawsuits, which doubled to 75 by early 2026, has forced the technology industry to prioritize compliance over compute power. This wave of litigation targets developers, data brokers, and end-users, with legal costs now threatening to eclipse research budgets.

Plaintiffs allege a wide spectrum of harms, from copyright infringement to consumer fraud, fundamentally shaping the future of AI development. In response, defense attorneys warn that litigation expenses could soon rival R&D spending.

A tidal wave of copyright claims

The surge in AI litigation stems primarily from copyright infringement claims over training data and concerns about algorithmic fairness. As creators and large enterprises file suits, courts are issuing mixed rulings, while state governments are simultaneously introducing stricter regulations and fines for AI misuse and lack of transparency.

By early 2026, the number of copyright lawsuits filed against AI firms since 2022 had climbed to at least 75 - more than doubling in just one year. Landmark cases like Thomson Reuters v. ROSS Intelligence and NYT v. OpenAI are scrutinizing the 'fair use' defense for training models on proprietary data. The legal landscape remains unsettled, with conflicting verdicts: a Delaware court found infringement in the ROSS case, while a California court deemed Anthropic's model training highly transformative.

Generators for music, images, and video are facing similar legal challenges. In 2025, Disney and Universal initiated lawsuits against two visual-AI startups. Meanwhile, Warner Music settled with the music generator Suno, mandating a model rebuild using licensed content. Courts are increasingly signaling that unfavorable rulings could lead to compulsory licensing, adding pressure for companies to negotiate settlements.

State attorneys general step in

While federal agencies proceed cautiously, state attorneys general (AGs) are acting decisively. A bipartisan coalition of 24 state AGs has pushed back against federal preemption of state-level AI rules, positioning states as the primary responders to harms from deepfakes and privacy violations. For example, New Jersey applied its anti-discrimination laws to automated systems, and Texas secured a 2024 settlement from a health-tech company over false claims about its diagnostic AI.

Several states now empower their AGs to sue developers of frontier models for inadequate safety reporting. Notably, New York's RAISE Act, which took effect this year, imposes civil penalties of up to $3 million for inaccuracies in required transparency reports.

Building trust before subpoenas arrive

Proactive governance is becoming critical as consumer skepticism grows. Research indicates that 46% of consumers lose trust in a brand upon discovering undisclosed AI use, and only 29% believe AI technology currently meets their expectations. Experts advise that building trust depends more on transparent, predictable governance than on impressive product demonstrations.

Reflecting this shift, PwC's 2025 forecast predicts a move from isolated experiments to strategic, enterprise-wide AI programs directed by leadership. These programs emphasize workflows where both value and risk are quantifiable. Centralized platforms that log AI decisions and flag errors are gaining traction, as they generate the clear audit trails that regulators demand.

• These audit trails directly address the four highest-ranked AI risks from McKinsey's 2025 survey: privacy, explainability, reputation, and compliance.

A compact playbook for 2026

• Audit all training datasets for license status and data removal rights.
• Integrate risk officers into model release committees and grant them clear veto authority.
• Release plain-language model cards that detail intended uses, limitations, and safety testing outcomes.
• Implement automated dashboards to track and correct model hallucinations in real time.
• Establish a litigation contingency fund that grows in proportion to user adoption.

Organizations adopting these measures not only reduce their legal exposure but also gain the 'transparency dividend' increasingly valued by regulators. Conversely, inaction leads to a stark reality of discovery deadlines, protracted settlement negotiations, and reputational harm, diverting resources that could otherwise fuel innovation.

Looking ahead

Looking forward, the trend of settlements, partnerships, and licensing agreements that defined 2025 is set to accelerate through 2026. Courts are indicating that such voluntary deals could temper demands for stricter government regulation. Companies that act now to align their governance with public expectations will build a foundation of trust - an asset that, once established, can compound more valuable than any dataset.

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Why have AI lawsuits jumped to at least 75 by early 2026?

Copyright filings more than doubled in 2025 alone, rising from roughly 30 cases at the end of 2024 to over 70 within twelve months. Courts are now weighing commercial harm and transformative use at the same time, turning every training run into a potential exhibit A.

Which cases are moving fastest toward a verdict?

• Thomson Reuters v. ROSS Intelligence - a Delaware court already rejected ROSS's fair-use defense at summary judgment, sending the question to the Third Circuit on interlocutory appeal.
• NYT v. OpenAI & Microsoft - discovery is "contentious" and the plaintiffs were allowed a second amended complaint in January 2026, signaling the judge sees merit in at least part of the claim.
• Perplexity AI was sued twice in one week (Chicago Tribune and NYT) over both training and RAG output, and the cases are likely to be consolidated, accelerating the timetable.

What new legal risks appeared in 2025?

Beyond copyright, 2025 added AI-washing (FTC brought a dozen cases), voice-spoofing fraud, trademark clashes (OpenAI's "Sora" v. OverDrive's "Sora"), and data-misappropriation suits such as the proposed class action against Figma for allegedly training on private customer files. Average number of AI risks that companies now mitigate has jumped from two in 2022 to four in 2025, with privacy, explainability, reputation and compliance topping the list.

How are state Attorneys General reshaping enforcement?

A bipartisan coalition of 36 AGs warned Congress not to preempt state AI laws, while 24 AGs told the FCC to back off for Tenth-Amendment reasons. New York's new RAISE Act lets the AG sue frontier-model developers for up to $3 million per reporting failure, and Texas already extracted a first-of-its-kind settlement from an AI healthcare company for false safety claims. Expect state-led litigation to outrun federal rule-making in 2026.

What concrete steps reduce lawsuit exposure right now?

1. Document licenses - Secure written permission for any copyrighted, trademarked or personal data used in training or RAG retrieval.
2. Publish transparency cards - 46 % of consumers trust a brand less when they discover hidden AI use; disclosing model purpose and limitations flips that dynamic.
3. Build a centralized AI-governance platform - PwC data shows enterprise-wide programs cut incident response time and satisfy emerging due-care standards.
4. Adopt an 80/20 redesign rule - Eighty percent of value comes from re-engineering workflows for human oversight, making fair-use defenses far more persuasive.
5. Monitor four key risks - Privacy, explainability, reputation and compliance; organizations that track all four are half as likely to face regulatory inquiry within 18 months.