Category Archives: Technology

Board and C-Suite Lessons for Getting AI Right: What 25 Years of Internet Adoption Can Teach Us

by Charu A. Chandrasekhar, Avi Gesser, Gordon Moodie and Karen Levy

Left to right: Charu A. Chandrasekhar, Avi Gesser, Gordon Moodie and Karen Levy (photos courtesy of Debevoise & Plimpton LLP)

As boards and executives look for guidance on how best to adopt AI, comparisons to previous innovations are often used. But catchphrases like “AI is the new fire” or “it’s the new electricity” are not very helpful for people who have to make decisions about AI adoption. None of us were around to experience the impact of the steam engine, and even if we had been, the business world then was so different from what it is today that any lessons cannot be readily translated into concrete, actionable advice. Continue reading →

AI’s Biggest Enterprise Challenge in 2026: Contractual Use Limitations on Data

by Charu A. Chandrasekhar, Avi Gesser, and Adam Shankman 

Left to right: Charu A. Chandrasekhar, Avi Gesser, and Adam Shankman (photos courtesy of Debevoise & Plimpton LLP)

We recognize it’s a little early to make the call for the biggest AI challenge for 2026, but we’re pretty confident that NDAs and other contractual use limitations are about to become a significant problem for enterprise AI adoption.

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Agentic AI in Retail Investing: Navigating Regulatory and Operational Risk

by Charu Chandrasekhar, Avi Gesser, Jeff Robins, Kristin Snyder and Achutha Raman

Left to Right: Charu Chandrasekhar, Avi Gesser, Jeff Robins, Kristin Snyder and Achutha Raman (Photos courtesy of Debevoise & Plimpton LLP)

The Rise of AI-Driven Investing in Retail Finance

Generative artificial intelligence (“GenAI”) innovations are rapidly transforming the formulation, analysis, and delivery of investment advice. Many broker-dealers and investment advisers are embracing GenAI to support one or more parts of the investment lifecycle—synthesizing investment research; undertaking trend analysis, anomaly detection, and pattern recognition for risk modeling and market surveillance; and performing large-scale data extraction and analysis.

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Do the Enforcement Choices Match the “America First” Antitrust Rhetoric?

by Bilal Sayyed

Bilal Sayyed (photo courtesy of Cadwalader, Wickersham & Taft LLP)

Gail Slater, the Assistant Attorney General for the Antitrust Division, Department of Justice, suggests that the antitrust leadership of both political parties “underenforced our century-old antitrust laws for several decades,” accepting “false economic theories of self-correction” of markets negatively impacted by anticompetitive conduct and dominant firms.  Gail Slater, The Conservative Roots of America First Enforcement (Apr. 28, 2025).  Federal Trade Commission Commissioner Mark Meador recently criticized “the monstrously swollen firms who’ve hollowed out communities, raised prices, distorted labor markets, corrupted the public square, or otherwise degraded quality across [the] economy.” “Antitrust enforcement is,” according to Meador, “one of the most powerful, economy-wide tools available for addressing” a “dehumanization of economic life” associated with “the size and power of the largest companies” that have “ballooned to unprecedented levels.” Mark Meador, Antitrust’s Populist Soul (Sept. 15, 2025). “Big is bad.” Mark Meador, Antitrust Policy for the Conservative (May 1, 2025).

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Which OpenAI Model for Legal Work? Update for GPT-5

by Avi Gesser, Diane Bernabei, and William J. Sadd

photos of authors

From left to right: Avi Gesser, Diane Bernabei, and William J. Sadd (photos courtesy of Debevoise & Plimpton LLP)

We recently provided a quick guide on the comparative capabilities of the various models currently available through GPT Enterprise based on our experience as lawyers using these models and OpenAI’s own recommendations. Below is an update to that guide based on our use of the new GPT-5 models since they became available to us on August 7, 2025. Again, this blog post is not a review or endorsement of any particular GenAI model.

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AI Use Cases for Lawyers, Part 2—From Audio of a Hearing to Transcript, Summary, PowerPoint and Podcast in Nine Minutes

by Avi Gesser and Michael Pizzi

Photos of authors

From left to right: Avi Gesser and Michael Pizzi (photos courtesy of Debevoise & Plimpton LLP)

In Part 1 of this series, we “vibe coded” a game designed to help train lawyers and professional staff on the firm’s new AI policy using Generative AI. In Part 2, we demonstrate how lawyers can use AI tools to rapidly transcribe and summarize audio recordings from congressional hearings, oral arguments, or depositions, and transform them into a variety of easy-to-digest formats. Specifically, we used NotebookLM and Gamma to transcribe a recent 30-minute Second Circuit oral argument and then create a two-page written summary, a “podcast”-style audio summary, and a PowerPoint presentation—all in under nine minutes.

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Future-Proofing Private Equity and Venture Capital: Leveraging AI for Strategic Advantage and Higher Returns

by Sabrina Hannam, Ibe Imo, Shana Sharan, and Ash Buonasera

Left to right: Sabrina Hannam, Ibe Imo, Shana Sharan and Ash Buonasera (photos courtesy of Boardswell)

In the high-stakes world of private equity, venture capital, and technology, a silent revolution is underway, transforming the very essence of how firms operate and compete. It’s a story not of human titans clashing in boardrooms, but of a new collaborator—Artificial Intelligence (AI)—that is rewriting the rules of engagement for human capital management. Once a tool for streamlining simple tasks, AI has evolved into a “digital colleague,” capable of autonomous decision-making and strategic support that extends far beyond the traditional confines of talent acquisition. This shift is challenging long-held practices and heralding an era where success is no longer solely defined by human intuition but by a symbiotic relationship between bold leadership and intelligent machines. Continue reading →

California Adopts New Employment Al Regulations Effective October 1, 2025

by Arsen Kourinian, Ruth Zadikany, and Remy N. Merritt

Left to right: Arsen Kourinian, Ruth Zadikany, and Remy N. Merritt (photos courtesy of Mayer Brown)

The California Civil Rights Council (CRC) recently announced that it has finalized regulations that clarify how California’s anti-discrimination laws apply to the use of artificial intelligence (Al) and automated decision systems (ADSs) in employment decision-making (the “Regulations”). The Regulations provide that the use of an ADS (including Al) in making employment decisions can violate California law if such tools discriminate against employees or applicants — either directly or due to disparate impact — on the basis of protected characteristics (including race, age, religious creed, national origin, gender, and disability).

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White House’s AI Action Plan: Winning the Race in a Patchwork Regulatory Era

By Joshua Ashley Klayman, Ieuan Jolly, Jeffrey Cohen, and Caitlin Potratz Metcalf

Left to right: Joshua Ashley Klayman, Ieuan Jolly, Jeffrey Cohen, and Caitlin Potratz Metcalf (photos courtesy of Linklaters)

On July 23, 2025, the White House published Winning the AI Race: America’s AI Action Plan (the AI Action Plan), a comprehensive effort aimed to solidify United States leadership in artificial intelligence. The AI Action Plan acknowledges the U.S.’ uniquely complex—and, at times, conflicting—regulatory landscape, including the patchwork of state-level laws that impact innovation, compliance, and policy predictability. The Action Plan calls for national leadership and seeks a unified, pro-innovation regulatory approach, with an understanding that states will continue to develop their own laws. Businesses should prepare for both the opportunities and the compliance challenges that will arise as the Action Plan is implemented.

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Antitrust Insights from the Administration’s First Six Months

by Ilene Knable Gotts, Nelson O. Fitts, Damian G. Didden, Christina C. Ma, and Emily E. Samra

Left to right: Ilene Knable Gotts, Nelson O. Fitts, Damian G. Didden, Christina C. Ma, and Emily E. Samra (photos courtesy of Wachtell, Lipton, Rosen & Katz)

As predicted, antitrust merger enforcement under the second Trump Administration exhibits a return to a more restrained approach at both the Federal Trade Commission and the Antitrust Division of the Department of Justice.  Most refreshingly, the agencies appear committed to good faith engagement with merging parties.  The FTC lifted its four-year “temporary” suspension of early terminations of the HSR waiting period, and a senior Division official recently stated that the DOJ will “not send ‘scarlet’ letters warning parties that they ‘close at their own risk’”—a practice adopted under the prior administration.  In recent orders, the FTC highlighted the importance of Commission staff and merging parties working together in “good faith” during merger reviews.  In public statements, both the FTC and DOJ have eschewed “turning the HSR review into an extortion racket.” These commitments reflect a welcome return to established patterns of antitrust practice, where proactive engagement with regulators can lead to efficient outcomes for lawful transactions.  

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