Earlier this month Hogan Lovells completed what it described as one of the largest transactions in the legal industry: a merger with Cadwalader, Wickersham & Taft. The combined firm ranks among the top five global law firms, with about 3,000 lawyers and roughly $3.6 billion in annual revenue.
The deal was driven by Miguel Zaldivar, Chief Executive Officer of Hogan Lovells. Zaldivar had identified a missing presence in New York for his firm; Hogan Lovells itself had been formed earlier by merging the regulation-focused Washington firm Hogan & Hartson and Lovells, which has served the City of London since the 1890s.
Why Cadwalader?
According to Zaldivar, the merged firm creates a market proposition that previously didn’t exist: combining Washington heritage and London strength with a meaningful New York platform. When he interviewed for the CEO role in 2019, he told the board they needed to "live in New York," and that simply building a practice there was not sufficient.
Zaldivar initially targeted Shearman & Sterling, which ultimately merged with Allen & Overy, and then approached Pat Quinn, managing partner of Cadwalader, the oldest firm on Wall Street. Quinn initially rejected the merger proposal at a 2024 meeting, but Zaldivar asked him to study the materials with his strategy team, believing they would conclude a global platform would be advantageous.
The role of AI in the decision
Zaldivar says artificial intelligence (AI) was a meaningful factor behind the decision to seek scale. After taking the CEO role in 2020 he became focused on AI; although he does not claim to be a technical expert, he believes AI will transform the profession and firms must prepare.
He summarized a traditional cost structure as: people first, real estate second, technology third, operations fourth. He expects technology to move up that list and possibly displace people. From that perspective, smaller firms—Zaldivar cites firms around $600 million in revenue—may lack the resources to invest in the necessary technology, while Hogan Lovells at nearly $3 billion provides a different base to compete.
Zaldivar pointed to Kirkland & Ellis’s announcement that it will invest $500 million in AI as an example of the scale of resources now being deployed, arguing that without similar resources a smaller firm cannot realistically compete.
Which tasks might move in-house and which remain with firms?
Zaldivar acknowledges that simpler, less sophisticated tasks are more likely to be handled in-house by clients using AI tools. However, he believes external firms can retain work if they maintain an elite proposition and become more efficient than in-house teams, because law firms have more data and repeat exposure to issues: "we will look at an issue ten times, they will look at it once."
Workforce shape and recruitment practices
Asked about prospective changes to law firm staffing structures—some envision a shift away from the traditional pyramid to alternatives such as a cylinder or inverted pyramid—Zaldivar said he cannot predict the exact shape. He expects segmentation: firms that effectively train large recruiting classes and make efficient use of junior lawyers will win more work; those that fail to do so risk being displaced.
Zaldivar also emphasized that Hogan Lovells will continue hiring in ways consistent with its culture. He referenced the firm’s response to the Lehman crisis, when management avoided layoffs and instead found solutions for young professionals (some moved in-house, some were sent home), and said he feels a moral obligation to continue that legacy.
Conclusion: further consolidation likely
Zaldivar’s view is that AI-driven change and the resource needs of serving the world’s largest companies will push more law firms toward consolidation. Larger firms with greater capacity to invest in technology are likely to have an advantage over smaller competitors that cannot marshal the same resources.
As an aside, Cooley CEO Rachel Proffitt has noted that AI could help big law firms more quickly identify outstanding junior lawyers, further changing workforce and training dynamics.
