Artificial intelligence is being litigated right now across nearly every corner of American law, and AI court cases already on federal and state dockets are producing real verdicts, settlements, and sanctions. Copyright suits over training data, wrongful death claims against self-driving software, discrimination charges against hiring algorithms, biometric privacy class actions, a new federal deepfake statute, SEC fraud actions over exaggerated AI claims, an FTC antitrust inquiry, and sanctions against lawyers who filed chatbot-invented citations all sit before judges today. What follows is where each of those fights stands.
Copyright Lawsuits Over AI Training Data
The largest cluster of AI litigation asks whether feeding copyrighted works into a machine-learning model is infringement. Federal copyright covers original works of authorship fixed in a tangible medium, from literary and musical works to visual art and software.1Office of the Law Revision Counsel. 17 U.S. Code 102 – Subject Matter of Copyright: In General The disputed question is whether ingesting those works to train a model counts as copying them.
In Andersen v. Stability AI, a class of visual artists alleges that Stability AI and co-defendants scraped roughly five billion copyrighted images into datasets used to train the Stable Diffusion image generator, and that the resulting model can produce output “in the style” of their work.2Justia. Andersen et al v. Stability AI Ltd. et al, No. 3:2023cv00201 – Document 223 A federal judge in the Northern District of California has allowed most of the artists’ claims to proceed, with summary judgment briefing scheduled into 2027.
The New York Times Co. v. Microsoft Corp. raises the same issue for text. The Times and other news organizations allege that OpenAI and Microsoft reproduced journalistic content to train large language models capable of generating substitutes for the original articles. In April 2025, a judge in the Southern District of New York denied the defendants’ motions to dismiss on direct and contributory copyright infringement and allowed trademark dilution claims to move forward, while dismissing some claims under the Digital Millennium Copyright Act and common-law misappropriation.3Justia. The New York Times Company v. Microsoft Corporation et al, No. 1:2023cv11195 – Document 514
The First Rejection of a Fair Use Defense
AI developers rely on fair use, which weighs the purpose and character of the use, the nature of the work, how much was taken, and the effect on the market for the original.4Office of the Law Revision Counsel. 17 U.S. Code 107 – Limitations on Exclusive Rights: Fair Use The first federal court to reject that defense in an AI training case was the District of Delaware in Thomson Reuters v. Ross Intelligence. The court found that Ross’s use of Thomson Reuters headnotes to train a legal research AI was not transformative because both products served the same purpose, legal research, and that the effect on the potential market for AI training data weighed decisively against fair use even though Thomson Reuters had not yet licensed its data for that use.5U.S. District Court for the District of Delaware. Thomson Reuters Enterprise Centre GmbH v. Ross Intelligence Inc.
The exposure is severe. Willful copyright infringement carries statutory damages of up to $150,000 per work, and training datasets contain millions of items.6Office of the Law Revision Counsel. 17 U.S. Code 504 – Remedies for Infringement: Damages and Profits The outputs, meanwhile, may not be protectable at all: the U.S. Copyright Office maintains that copyright requires human authorship, and material generated solely from text prompts without meaningful human creative control does not qualify for registration.7Federal Register. Copyright Registration Guidance: Works Containing Material Generated by Artificial Intelligence
Autonomous Vehicle Lawsuits
When AI controls physical machinery, litigation shifts to product liability. In one wrongful death case involving Tesla’s Autopilot, a jury returned a $243 million verdict after finding that defects in the system contributed to a fatal crash. Plaintiffs in multiple Autopilot cases argue that Tesla’s marketing creates a false impression of full autonomy, leading drivers to over-rely on software that cannot reliably detect obstacles.
The 2018 Uber self-driving vehicle fatality in Tempe, Arizona produced a different outcome. The vehicle’s software detected a pedestrian 5.6 seconds before impact but did not correctly classify her or predict her path, and the National Transportation Safety Board found that Uber had deactivated the vehicle’s automatic emergency braking system while relying on a human backup driver who was not monitoring the road. Prosecutors declined to charge Uber as a corporation. The backup driver pleaded guilty and received three years of supervised probation.
Federal regulators have not set binding safety standards for autonomous driving software. The National Highway Traffic Safety Administration acknowledges that even the most advanced driver-assistance technologies currently available to consumers still require “the full engagement and undivided attention of drivers.”8NHTSA. Automated Vehicles for Safety That gap makes product liability suits the main tool for holding manufacturers accountable.
Hiring Algorithm Discrimination Cases
Algorithms that screen job applicants are generating discrimination lawsuits when they produce biased outcomes. Title VII prohibits discrimination based on race, color, religion, sex, and national origin regardless of whether a human or an algorithm makes the decision.9U.S. Equal Employment Opportunity Commission. Title VII of the Civil Rights Act of 1964 Separate federal law protects workers 40 and older.
The clearest case so far is EEOC v. iTutorGroup, Inc., where the tutoring company programmed its application software to automatically reject female applicants aged 55 or older and male applicants aged 60 or older. More than 200 qualified applicants were rejected on age alone, and iTutorGroup settled for $365,000.10U.S. Equal Employment Opportunity Commission. iTutorGroup to Pay 365,000 to Settle EEOC Discriminatory Hiring Suit The case established that the EEOC will pursue companies whose automated tools produce discriminatory results even when the bias is written into code rather than voiced by a manager.
A harder question arises when software produces biased outcomes without anyone intending them. An algorithm trained on historical hiring data can learn to penalize characteristics correlated with race or gender without those categories appearing as explicit inputs. Under a disparate impact theory, a company can be liable regardless of intent. Proving that the algorithm caused the disparity is the plaintiff’s practical hurdle, especially when the model’s internal logic is opaque. Similar questions extend to credit and tenant screening under the Fair Credit Reporting Act, which requires clear reasons when consumers are denied credit, housing, or employment based on a consumer report.11Federal Trade Commission. Fair Credit Reporting Act
Biometric Privacy Class Actions
AI systems depend on personal data collected at scale, and the most aggressive litigation targets biometric identifiers like facial geometry, fingerprints, and voiceprints. Illinois’s Biometric Information Privacy Act is the primary vehicle because it gives individuals a private right to sue and imposes statutory damages of $1,000 per negligent violation and $5,000 per intentional or reckless violation. Those per-person figures compound quickly.
Clearview AI is the leading defendant. The company scraped billions of photos from social media to build a facial recognition database and sold access to law enforcement and private entities without consent. In settling a class action under the Illinois law, Clearview agreed to a permanent nationwide ban on selling or granting free access to its database to private companies and individuals, agreed to block its database from any Illinois government entity, including law enforcement, for five years, and agreed to maintain an opt-out mechanism for Illinois residents. The settlement did not include a large cash payout but imposed operational restrictions that limit how Clearview can operate.
Other biometric suits have targeted facial recognition in retail stores, employee timekeeping systems, and social media photo-tagging features. The common thread is the absence of informed written consent before collection, and class actions in this area routinely allege damages in the hundreds of millions.
Deepfake Criminal Cases and the TAKE IT DOWN Act
Congress passed the TAKE IT DOWN Act in May 2025 to criminalize publishing nonconsensual intimate visual depictions of identifiable individuals, whether authentic or AI-generated.12Congress.gov. S.146 – TAKE IT DOWN Act, 119th Congress (2025-2026) For depictions of adults, violations carry fines and up to two years in prison. For depictions of minors, the maximum rises to three years. Threats to publish such images are a separate offense, punishable by up to 18 months for threats involving AI-generated adult images and 30 months for minors.13Congress.gov. The TAKE IT DOWN Act: A Federal Law Prohibiting Nonconsensual Intimate Visual Depictions Online platforms must remove reported images within 48 hours of notification, and victims are entitled to mandatory restitution.
SEC Enforcement Against AI Washing
Public companies that exaggerate their AI capabilities face securities enforcement. The SEC calls the practice “AI washing” and treats it like any other material misstatement to investors. The agency’s first enforcement action in the area targeted Presto Automation, a restaurant-technology company. Presto claimed in public filings and press statements that its AI-powered drive-through ordering system operated autonomously, when the technology was initially owned and operated by a third party, and even after Presto deployed its own version, the vast majority of orders required human intervention. The SEC settled the charges without a civil penalty, crediting Presto’s cooperation and remedial efforts.14U.S. Securities and Exchange Commission. SEC Charges Restaurant-Technology Company Presto Automation
For 2026, the SEC’s Division of Examinations has identified AI as a focus area and will analyze registrant disclosures for accuracy about AI capabilities. Companies describing products as “AI-powered” or claiming proprietary models without substantiation should expect scrutiny.
The FTC Antitrust Inquiry Into AI Partnerships
The Federal Trade Commission is investigating whether the largest technology companies are using strategic investments to lock up the AI market. In January 2024 the FTC launched a formal inquiry into the relationships between Microsoft and OpenAI, Amazon and Anthropic, and Google and Anthropic, examining whether these arrangements “risk distorting innovation and undermining fair competition.”15Federal Trade Commission. FTC Launches Inquiry into Generative AI Investments and Partnerships
The FTC’s report found that the partnerships involve more than $20 billion in cumulative investment and include equity stakes, revenue-sharing rights, billions in cloud-computing commitments, exclusivity provisions, and the exchange of sensitive technical information. The agency flagged three concerns: the partnerships could restrict access to scarce computing resources like specialized chips; they could create technical and contractual switching costs that lock AI startups into a single cloud provider; and they give large incumbents access to proprietary information that competitors cannot obtain.16Federal Trade Commission. Behind the FTC’s 6(b) Report on Large AI Partnerships and Investments Whether the FTC brings enforcement actions is still open.
Sanctions for AI-Generated Legal Filings
Lawyers who let chatbots write their briefs are being sanctioned. The landmark case is Mata v. Avianca, where attorneys representing a personal injury plaintiff filed a brief containing fabricated judicial opinions with fake quotes and citations, all generated by a chatbot. Opposing counsel could not locate the cited cases because they did not exist. The court found that the attorney of record and a second attorney who assisted had acted in bad faith and imposed a $5,000 sanction on the lawyers and their firm jointly.17Thomson Reuters. Mata v. Avianca, Inc., 678 F.Supp.3d 443 (2023)
That case was the start. A database tracking court decisions involving AI-generated hallucinations documented over 1,450 such cases as of May 2026, with outcomes ranging from monetary sanctions and public reprimands to bar suspensions and disciplinary referrals. Recent sanctions have included fines of $1,000 to $2,700 for individual fabricated citations, mandatory continuing legal education, and in at least one case a lawyer’s license was suspended for submitting AI-generated fabricated case law without verification.
The mechanism is Federal Rule of Civil Procedure 11, which requires that any attorney who signs a court filing certify, after reasonable inquiry, that the legal contentions are warranted by existing law and that the factual assertions have evidentiary support.18Legal Information Institute. Federal Rules of Civil Procedure, Rule 11 – Signing Pleadings, Motions, and Other Papers Citing cases that do not exist fails that standard on its face. A growing number of federal judges have issued standing orders requiring attorneys to disclose whether they used generative AI and to certify that a human verified every citation. Lawyers can use AI for research and drafting, but they own every word in the filing.