Businesses that embed AI into hiring, customer support, and decision-making workflows are facing a rising number of lawsuits grounded in traditional legal theories - product liability, agency, misrepresentation, and copyright - while a patchwork of new state and federal disclosure laws forces companies to reevaluate their compliance posture.
Product liability reaches AI chatbots and screening tools
In Garcia v. Character Technologies, Inc., a Florida federal court allowed product liability claims to proceed after a 14-year-old allegedly had emotionally manipulative and sexually suggestive conversations with a 'Character.AI' chatbot before dying by suicide. The court's decision to treat the AI system as a product, rather than a mere online service, matters because product liability claims are generally easier for plaintiffs to pursue than ordinary negligence claims. The case later settled.
Mobley v. Workday, Inc. extended potential liability to technology vendors themselves. The plaintiff alleged that automated screening tools disproportionately filtered him out based on age, race, and disability. A California court permitted claims under Title VII, the ADEA, and the ADA to proceed on an agency theory, reasoning that Workday performed functions traditionally handled by human resources departments. The case remains active and is influencing how employers and vendors share exposure nationwide.
Chatbot misstatements, copyright fights, and FTC enforcement
When a commercial chatbot gives wrong information, companies can be on the hook. In Moffatt v. Air Canada, a British Columbia tribunal held the airline liable after its chatbot incorrectly advised a passenger about bereavement fare policies, rejecting the airline's argument that it should not be bound by the AI-generated response.
Copyright claims are also testing the boundaries of AI training. In Thomson Reuters Enterprise Centre GmbH v. Ross Intelligence, Inc., a Delaware court found that Ross Intelligence infringed Thomson Reuters' copyrighted headnotes by using them to train a legal research model without a license. The court rejected Ross Intelligence's fair use defense.
The Federal Trade Commission has used its authority under Section 5 of the FTC Act to pursue companies that exaggerate AI capabilities. Recent actions against Air AI and Workado focused on deceptive marketing practices. The agency is also increasingly demanding information from firms that operate consumer-facing AI chatbots on how those systems measure, test, and monitor potentially negative effects on children and teens.
Disclosure mandates and sector-specific rules
Healthcare and employment are drawing some of the strictest state-level requirements. California's AB 3030 mandates disclosure when generative AI is used in patient communications, and its SB 1120 bars insurers from relying solely on automated systems for adverse coverage decisions. Illinois requires disclosure when AI analyzes video interviews, and New York City enforces independent bias audits for certain automated hiring tools.
Consumer-facing bots now face transparency rules. California's SB 1001 makes it unlawful to use an online chatbot to market goods, services, or influence electronic voting without conspicuously disclosing its non-human identity. A wave of state laws also criminalizes deceptive political deepfakes within 90 days of an election and broadly prohibits the distribution of non-consensual sexually explicit deepfakes.
Outside the United States, the European Union's AI Act has been in force since August 2024. The regulation sets up a tiered risk framework (EU AI Act text). Unacceptable-risk practices, such as certain social scoring systems and subliminal manipulation, are banned. High-risk systems - covering medical devices, critical infrastructure, employment screening, law enforcement, and education - must meet conformity assessments, registration, transparency, and human-oversight requirements before deployment.
Why this matters for Legal professionals
Attorneys advising corporate clients must move beyond generic software licensing reviews. A company's exposure can turn on whether an AI tool is treated as a product, service, or agent - and on the patchwork of disclosure and bias-audit laws that differ by jurisdiction and sector. In-house counsel and outside practitioners need to map client AI usage across HR, customer service, marketing, and vendor contracts, while tracking how courts and regulators are applying decades-old legal frameworks to systems that learn and adapt. For lawyers who need to build fluency in these technologies, resources such as AI for Legal training can provide structured grounding in the liability and compliance issues now surfacing in litigation.
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