Fragmented AI Regulation and Litigation Activity is Accelerating

Artificial intelligence developments are outpacing the legal structures designed to govern them and no comprehensive federal AI statute exists. Nevertheless, enforcement activity is accelerating at both the federal and state levels, as Morgan Lewis writes in a recent article.

Companies deploying AI in sectors ranging from healthcare to marketing are facing a fragmented and increasingly complex compliance environment. Federal agencies are leveraging existing statutes to address AI-related conduct.

The Federal Trade Commission (FTC) is using Section 5 authority to target deceptive AI practices. The Securities and Exchange Commission (SEC) is pursuing “AI washing” cases involving inflated investor disclosures. The Department of Justice (DOJ) is focusing on False Claims Act exposure where AI is used in government-funded programs.

A 2025 White House action plan favored centralized federal innovation policy and sought to limit conflicting state-level regulation.

The Morgan Lewis article surveys the layered enforcement landscape governing AI deployment. States including California, Colorado, New York, and Texas have enacted targeted AI statutes addressing algorithmic pricing disclosure, healthcare oversight, and high-risk decision systems.

State attorneys general are applying “unfair and deceptive acts or practices” (UDAP) statutes and coordinating multi-state investigations. Private litigation is increasing, using antitrust, copyright, securities fraud, biometric privacy, and employment discrimination theories.

A regulatory-litigation feedback loop is emerging, where court decisions shape regulation and new laws spawn fresh litigation risk. The article also identifies priority risk areas for 2026 and recommends governance measures, including bias audits, cross-functional oversight committees, and vendor contract reviews.

Legal teams should note the growing state enforcement patchwork and its implications for jurisdictional risk when advising clients with multi-state operations. Disclosure obligations and insider trading controls warrant attention, given the SEC’s focus on AI washing in public company filings.

Transactional due diligence should incorporate review of AI governance frameworks, training data practices, and algorithmic pricing arrangements that could trigger antitrust scrutiny.