United States: Trade Secrets

Two Georgia employees allegedly misappropriated trade secrets and proprietary software to launch a competing insurance brokerage, prompting their former employer to sue. When their professional liability insurer denied coverage, a critical question emerged: what types of actions by an insured actually constitute "professional services" under Georgia law, and does establishing a rival business using stolen confidential information fall within that definition?

A Ninth Circuit decision reversed a $40 million trade secrets verdict because a single jury instruction placed the burden of proof on the wrong party under federal law. The case highlights a critical divergence between the federal Defend Trade Secrets Act and California's trade secret statute regarding who must prove whether information was "readily ascertainable," and explores whether plaintiffs can recover both avoided-cost damages and injunctive relief without double recovery.

Artificial intelligence has revolutionized workplace productivity, but many companies have adopted AI faster than they've implemented policies to protect their confidential information. As employees routinely upload sensitive data into AI chatbots to improve efficiency, organizations face an invisible but growing risk: the inadvertent disclosure of valuable trade secrets that could undermine legal protections and competitive advantages.

The Fifth Circuit's decision in EnvTech v. DeBusk examines whether allegations of trade secret theft can satisfy RICO's pattern requirement when supported by evidence from multiple lawsuits. This ruling clarifies how companies accused of systematically misappropriating confidential information may face escalated liability beyond traditional trade secret remedies, including treble damages and broader discovery obligations.

Organizations face mounting risks as employee mobility and technology create new pathways for trade secret theft and data exfiltration. Understanding behavioral red flags, implementing layered prevention strategies, and maintaining coordinated departure protocols can mean the difference between preventing information loss and responding to costly misappropriation. What steps should legal, HR, and IT teams take to protect confidential information in today's high-risk environment?

As AI companies increasingly rely on synthetic data for model training, M&A transactions involving these assets face novel legal uncertainties around ownership, provenance, and regulatory compliance. This analysis examines the critical due diligence considerations and contractual protections buyers need when synthetic datasets constitute a material component of deal value, from copyright ambiguities to inherited infringement risks and quality degradation concerns.

Navy contractors and defense suppliers face growing scrutiny over AI use in government work. Federal agencies now demand greater transparency into AI-assisted decisions, raising critical questions about when internal methods must be disclosed and how contract language can inadvertently expose valuable competitive advantages.

Minnesota’s comprehensive per- and polyfluoroalkyl substances (PFAS) pollution prevention law, commonly referred to as Amara’s Law, includes a product reporting requirement with broad reach and deadlines later in 2026...

A Kansas federal court applied a selective enforcement theory in a trade secret case, holding that inconsistent pursuit of legal remedies against former employees can demonstrate failure to protect trade secrets.