Cybersecurity

The autonomy and proactivity of AI agents will potentially unlock extraordinary efficiencies, but also may introduce new, untraversed surface area for cyberattacks. When AI systems are empowered to act, errors and compromises can cascade faster and farther than human-driven incidents.

This article is the first in a multipart series examining litigation risk in the modern technology supply chain. Here, we set the stage by looking at the role of third-party data processors, the types of disputes that commonly arise and the contract provisions that most often determine outcomes when those disputes turn into litigation.

As AI becomes embedded in everyday business and legal operations, organizations are confronting a new expectation: simply disclosing AI use is no longer enough. A critical shift is taking place in the legal industry: transparency is no longer just about disclosure; it’s about comprehension.

Clients have pushed back on what they are willing to pay for since long before anyone heard of a large language model. AI is the latest chapter in a long story about legal fees. But it introduces a wrinkle that prior tools did not.

Across practices, offices, and partner relationships, firms operate with limited visibility into where meaningful connections exist and when those connections signal real business potential. The idea of a fully captured “single view of the client” remains difficult to achieve. The question is no longer how to improve CRM adoption. It is whether the underlying model is fit for purpose.

The Illinois Department of Human Rights has drafted rules for the implementation of the new amendments. Below is a list of questions employers should be able to answer before integrating any new AI tool into their business in order to avoid costly penalties for violations of the new rules.

Businesses and investors are increasingly including AI-specific representations and warranties in commercial contracts and agreements, reassessing longstanding data strategies and sharpening their focus on protecting the rights in data that parties provide to one another.

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.