LEADERS Conversation with Greenberg Traurig’s Leaders

Firm Brief

Greenberg Traurig, LLP (gtlaw.com) has more than 3,100 attorneys in 51 locations in the United States, Europe and the Middle East, Latin America, and Asia. The firm is a 2024 BTI “Leading Edge Law Firm” for delivering on client expectations for the future and is consistently among the top firms on the Am Law Global 100 and NLJ 500.

Richard A. Rosenbaum,
Greenberg Traurig’s Executive Chairman

We’ve all seen how AI has reshaped virtually every facet of society. It has moved beyond the emergence phase and is now a reality that directly influences the global economy. AI considerations drive strategic planning, workforce decisions, customer engagement, risk management, and regulatory compliance.

Clients are increasingly faced with a growing set of interconnected legal and business considerations that span industries, jurisdictions, borders, and practice areas. Questions surrounding governance, liability, intellectual property, data usage, cybersecurity, regulatory oversight, and contractual risk often arise simultaneously rather than sequentially.

Businesses feel pressure to adopt AI-enabled tools and capabilities to remain competitive, while also navigating a fast-developing legal and regulatory landscape. Legislators, regulators, insurers, courts, and consumers are responding in varied ways, and in many cases uniform standards or established precedent have yet to emerge. The gap between the rapid pace of innovation and the time it takes for regulation to adapt appears to be growing.

This is where depth of experience and cross-disciplinary alignment can be especially valuable. Addressing AI legal issues requires the ability to bring together global teams across practices capable of advising clients in matters of litigation, regulatory, transactional, labor and employment, privacy, intellectual property, and industry-specific issues – sometimes at the same time. At Greenberg Traurig, we have invested in building an integrated capability of this nature. We recognized AI’s potential early on and began planning how to help clients navigate the forthcoming evolution. While this transformation has impacted virtually every area of law, we can look at a few examples to gain a sense of the bigger picture. The perspectives that follow from our Insurance, Retail, and Innovation teams illustrate how coordinated, pragmatic guidance can support organizations seeking to move forward with confidence.

Matthew N. Beekhuizen,
Greenberg Traurig’s Chief Pricing and Innovation Officer

Innovation & AI

Artificial intelligence did not arrive in a single moment. It crept in as an efficiency tool, then evolved to an accelerant, and increasingly operates as a decision-making force embedded in critical business and societal systems. The law has had to keep pace with rapidly moving technology, often responding in real time new innovations that challenge traditional legal frameworks. Legislatures are beginning to address concerns around transparency, bias, accountability, and intellectual property. States across the country have begun enacting AI-specific statutes, while regulators are increasingly looking to existing consumer protection, employment, antitrust, and privacy laws to establish meaningful guardrails. Accordingly, organizations should understand how their AI systems work, how they are trained, and how their outputs affect people.

Courts, meanwhile, are grappling with questions that traditional legal doctrines were not originally designed to answer. Who bears responsibility when an algorithm yields a flawed decision? How might liability be assessed when outcomes are shaped by complex models trained on large, and potentially imperfect, datasets? Whether long-standing principles of authorship, causation, and duty can adapt to systems that learn and evolve over time is an open question. Various stakeholders are seeking to influence the direction that legislation may take and how it is interpreted.

But one thing appears clear: AI does not eliminate accountability; rather, it reshapes it and, in some cases, may increase the focus on responsibility. Using an algorithm does not excuse bias, absolve responsibility, or automatically shield decision-makers from scrutiny. AI can amplify risk when governance is weak, but it can also reward strong foresight and robust oversight. Organizations that treat AI not as a standalone technology project, but as an enterprise-wide consideration requiring legal, technical, and ethical alignment from the outset, may be best positioned to succeed.

The evolution of AI law reflects a broader truth about innovation itself: progress and responsibility ought to move together. As AI transforms how decisions are made and value is created, the role of counsel goes beyond reacting; it involves helping clients adopt systems that earn trust, withstand scrutiny, and are designed to evolve over time.

John R. Richards,
Co-Chair of Greenberg Traurig’s Global Labor & Employment Practice and Global Chair of the firm’s Retail Industry Practice

Few industries illustrate the practical impact of technology more clearly than the retail space. A sector once defined by physical storefronts and seasonal rhythms has become a sophisticated ecosystem powered by data, automation, and continuous consumer engagement. AI has significantly changed how retailers hire and schedule workers, market and price products, and serve consumers. With that transformation comes a new concentration of legal risk.

On the workforce side, retailers are increasingly turning to automated hiring and screening tools to manage volume and speed. These tools can deliver measurable efficiency gains. However, they may also raise exposure under employment and anti-discrimination laws, particularly where algorithms unintentionally replicate or amplify historical bias. Algorithmic scheduling and productivity tools could raise additional concerns under wage and hour laws, especially when automated decisions affect breaks, overtime calculations, or employee classification. In addition, the expanding use of AI-enabled workplace monitoring – such as tracking productivity, movement, or engagement – may require retailers to navigate privacy, notice, and consent obligations that differ across states.

Nationwide and global retailers also face inconsistent disclosure requirements, governance expectations, and enforcement priorities. Relying on third-party vendors to deploy AI tools does not automatically shift that responsibility. Employers may remain accountable for outcomes, highlighting the importance of human oversight, clear internal governance, thoughtful policies, employee training, and well-drafted contractual protections.

On the consumer side, technology has fundamentally reshaped how retail brands connect with their customers. It has also personalized the shopping experience by collecting data on each consumer. Omnichannel commerce has blurred the boundaries between physical and digital marketplaces, while AI-powered marketing influences everything from product recommendations to pricing strategies. Subscription models, automated fulfillment, and experiential retail concepts offer convenience and engagement. They may also attract heightened regulatory scrutiny regarding transparency, fairness, and potential deceptive practices.

Legal considerations now extend beyond traditional consumer protection and supply-chain compliance and may include:

•AI-generated marketing content that tests advertising standards and intellectual property rules

•Platform accountability as retailers integrate marketplaces, social commerce, and third-party sellers into their brand experience.

What often distinguishes the most resilient retailers is not merely the speed of AI adoption, but the thoughtfulness with which they implement it. Retailers that embed governance, accountability, and trust into their operations may be better positioned to withstand regulatory scrutiny and legal challenges. In an industry built on brand loyalty, how technology is used may matter as much as what it delivers. The legal framework surrounding such use is increasingly a core consideration.

Fred E. Karlinsky,
Chair of Greenberg Traurig’s Global Insurance Regulatory and Transactions Practice Group

Insurance law is being reshaped by climate volatility, cyber risk, and the rapid integration of artificial intelligence into core insurance operations. A growing number of carriers use machine learning models to price risk, evaluate submissions, detect fraud, and support claims decisions. These tools promise meaningful efficiency gains, but they also raise concerns about accuracy, fairness, and accountability. At the same time, emerging technologies and new business models are generating risks that existing coverage frameworks did not contemplate.

Regulators have been proactive. The NAIC’s Model Bulletin on the Use of Artificial Intelligence Systems by Insurers has been adopted in some form by more than half of the states. It requires insurers to maintain written governance frameworks, validate third-party data and models, and document the testing of automated decisions for bias and reliability. Colorado has issued algorithmic discrimination rules for insurers. The New York Department of Financial Services has issued guidance on AI in underwriting and pricing. Additional state activity continues, with consistent emphasis on transparency, model governance, and consumer protection.

These developments coincide with significant pressure on traditional insurance markets. Climate-driven losses have prompted carrier withdrawals from segments of the homeowners market in states such as Florida, California, and Louisiana. Technological change is dovetailing with structural shifts in the economics of insurance. Risk is migrating to the surplus lines market and to alternative risk transfer structures while autonomous vehicles, transportation network companies, and delivery network platforms are prompting legislatures to revisit longstanding assumptions about coverage allocation and the point at which insurance attaches. Cyber insurance, once a specialty line, has become a central component of enterprise risk management and is increasingly tied to obligations under recent SEC disclosure rules.

The practical questions for insurers, agents, and policyholders are recurring ones. Will a pricing or underwriting model withstand regulatory review? Will a new product clear filing requirements in each relevant jurisdiction? Will a data-sharing arrangement satisfy applicable privacy and unfair trade practices standards? And as new industries emerge, how will the insurance practice meet their needs? Answering these questions requires dedicated attention to a relentless pace of change and an informed view of how regulators, courts, and consumer advocates are likely to respond.

Broadly, the next phases of insurance law may be shaped less by any single technology than by how the industry and its regulators address the legal and operational issues that follow from disruptive innovation.