Mass web-scraping for AI training, authorship of AI-generated works, and the scope of fair use in data-hungry systems are reshaping what “copyright risk” even means for a business. Companies that treat copyright as a mere box-checking exercise, or that assume long-standing internal practices are low-risk, increasingly find themselves out of step with how courts and regulators are thinking about AI-driven uses of content.
Together, EO 14365 and the National Policy Framework for Artificial Intelligence raise questions about the future of state and local laws governing employers’ use of AI, many of which are intended to protect against discrimination in connection with the use of AI.
After more than a hundred conversations with general counsel, chief legal officers, and legal operations leaders over the past seven months, I expected to hear complaints about AI accuracy or capability. The same five barriers appeared in conversation after conversation. Here’s what’s actually stopping deployment, and how to diagnose which barriers are blocking your team.
The use of AI does not alter fundamental obligations of accuracy, reasonableness and accountability. The legal risk lies not in the existence of hallucinations but in the failure to govern and verify them.
The Court held that intent is required and that mere awareness of infringement does not establish secondary liability.
The cyber insurance industry has long been dominated by conversations around security threats. Privacy concerns were often treated as an afterthought. But recently, there has been a critical shift: privacy risks that arise outside of traditional breaches are now front and center.
State app store age verification regimes do more than reallocate responsibility between platforms and developers. They create a new data supply chain for age knowledge, one that can move COPPA questions from “do we ask age?” to “what do we do when the platform tells us?” The teams that handle this best will treat platform age signals as sensitive compliance inputs: minimize them, tightly control where they flow, and design product behavior so that minors do not trigger unnecessary collection or disclosure.
A recent decision from the U.S. District Court for the Southern District of New York (SDNY), United States v. Heppner, has generated outsized commentary suggesting that the use of generative AI tools may jeopardize attorney-client privilege. A closer reading shows something far less dramatic.
The 2025 legislative cycle marked a pivotal year in U.S. privacy law, defined not only by continued nationwide expansion into AI) governance, children’s and teen privacy and online safety, as well as emerging data categories. In this article, we detail what enterprises need to be prepared for in 2026 and explain why we believe next year will be a watershed period for consumer privacy in the U.S.
Every decision to onboard a client, partner, lateral hire, contractor, consultant or expert witness carries risk. Yet despite the increasing complexity of that risk, many firms continue to rely on onboarding practices that have not kept pace with the digital world in which their clients and people operate. The result is a widening gap between how risk actually manifests today and how it is assessed at the point of onboarding.
© Copyright 2026 ALM Global, LLC trading as Centellic.
Advertise with Us Customer Support Terms of Service Privacy Policy
