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.
For decades, firms have invested in CRM systems with the expectation that better data and more attorney adoption would translate into better business development. In practice, that assumption has never fully held up. The question is no longer how to improve CRM adoption. It is whether the underlying model is fit for purpose.
This article covers potential landmines for the average elected official or public employee, particularly through the lens of the always developing Open Public Records Act and will provide some tools that municipal attorneys can use to fight back against self-inflicted wounds or AI overreach.
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.
The legal landscape around AI and copyright remains unsettled. Forward-looking businesses will not wait for definitive case law on every issue. Instead, they will treat AI as a catalyst to modernize copyright governance: tightening practices around online content, revisiting license strategies, and building internal literacy about how copyright really works in an AI-saturated environment.
During a recent lecture, Morrison & Foerster partner Joseph Gratz noted the potential of harnessing AI as a tool to further “human expression” and dissected the snarl of novel copyright challenges that AI song generators present to the music industry.
