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Law firms Hogan Lovells and Cadwalader set to merge in record $3.6bn deal

Combination that would deliver 3,000-lawyer behemoth is latest transatlantic merger

Hogan Lovells and Cadwalader, Wickersham & Taft are set to merge in the largest-ever law firm tie-up, creating a behemoth with combined revenues of more than $3.6bn.

The new firm, which will be known as Hogan Lovells Cadwalader, will become the world’s fifth-largest law firm by revenue and house more than 3,000 lawyers globally.

Hogan Lovells — which itself was created from the transatlantic merger of US firm Hogan & Hartson with the UK’s Lovells in 2010 — is by far the dominant party, with more than six times the number of lawyers and offices than New York-headquartered Cadwalader. Hogan Lovells chief executive officer, Miguel Zaldivar, will be CEO of the combined firm.

Partners will vote on the combination in the spring with the merger expected to go live as soon as June 2026, according to Zaldivar.

“This is history in the making,” Zaldivar told the Financial Times on Thursday. “We’re doing this in part to address our client needs . . . the days of smaller firms teaming up and multiple relationships [for each client with different firms], we see them as passing.”

“When you have a strong balance sheet — $3bn plus — when you have no debt, when you have a very well capitalised firm, when your brand has consistently improved . . . then the icing on the cake is getting New York right.”

Equity partners at Hogan Lovells earn an average of $3.07mn. Cadwalader’s profit per equity partner — a key metric to compare in any law firm merger — is $3.7mn.

Hogan Lovells will account for a greater proportion of the equity partners and a larger amount of the income of the combined firm, according to a person familiar with the deal’s terms.

The deal comes after Cadwalader, one of Wall Street’s oldest law firms and a pre-eminent name in finance, has lost tens of partners this year, including from senior management. 

The firm has also faced scrutiny over its decision to do a deal with US President Donald Trump in April, committing at least $100mn in pro bono legal services to the administration to avoid being targeted in a White House crackdown on Big Law earlier this year.

Pat Quinn, Cadwalader’s co-managing partner, told the FT that the firm was coming to the end of its second-ever strongest year by revenue and had hired more than 95 lawyers, including 10 partners, in the past 12 months. The firm predicts it will finish the year with revenues of $625mn.

The firms started talking about a possible deal in November 2024 before pausing conversations in March, Zaldivar said. Discussions restarted in autumn this year.

Zaldivar said the firms did not envisage major lay-offs from the combination, despite duplicate offices in London, New York and Washington DC.

The tie-up marks the latest in a run of large mergers in the legal industry as firms look to get a stronger foothold on both sides of the Atlantic and scale up in the face of pressure to make heavy investments in technology and artificial intelligence. 

UK law firm Ashurst and the US’s Perkins Coie agreed a merger last month, which will create one of the top 20 law firms globally by revenue, while America’s Winston & Strawn announced a tie-up with Britain’s Taylor Wessing this week for a 1,400-lawyer firm that will be known as Winston Taylor.

UK “magic circle” firm Allen & Overy and New York’s Shearman & Sterling also merged in 2024 to create A&O Shearman. The combined firm posted revenues of $3.7bn for the last financial year.

In this story that Sri, Amir and I published this morning, we revealed that over the past year OpenAI staffers had noticed that improvements to the company’s models weren’t necessarily lifting ChatGPT usage. Their quandary is that focusing too much on increasing the chatbot’s appeal could draw away resources from the company’s stated goal of developing artificial general intelligence, or AI that meets or surpasses human abilities.

Nevertheless, there are growing signs that the company is shifting its research strategy to be more aligned with its products. For instance, OpenAI hopes to release updates to its models for ChatGPT more frequently than in the past, as often as once a month, a current employee told me. Already, we’ve seen this trend with GPT-5.1 released in November and GPT-5.2 released this month.

This seems like a smart way to avoid building up too much hype around any particular model release—that can end up being a letdown (as we saw with GPT-5). But some current and former employees told me that they’re worried that OpenAI could become too focused on incremental updates to its models at the expense of the longer-term vision of what its AI should look like.

Other issues could arise if researchers focus too much on users’ initial reactions to changes in ChatGPT.

For instance, if a user is shown two versions of a ChatGPT response where one version is longer, they might choose the longer answer because people tend to assume longer responses are more accurate, a former employee said. In the long run, though, overly wordy responses can become annoying to users, the former employee said.

“Product and research are deeply interconnected, not oppositional,” an OpenAI spokesperson said in a statement. “Research breakthroughs shape our products, and product feedback shapes research. This is a single, unified strategy for building and safely deploying increasingly capable models, not a division between competing sides.”

For what it’s worth, a secretive new model from OpenAI, codenamed Garlic (whose existence we first reported here), could give the company an opportunity to realign its research and product teams. That’s because Garlic was created through improvements in pretraining, the first step of model training in which a model is shown lots of data from the internet and other sources so it can learn to make connections between them.

Pretraining is the part of the model development process that OpenAI has lately struggled to show improvements in. But getting better results in pretraining matters, because they flow through to the model’s performance in a variety of areas, from coding to creative writing to a model’s personality.

So theoretically once Garlic is incorporated into ChatGPT, it should improve the chatbot’s performance on a variety of areas users might ask questions about. It should also improve the chatbot’s personality, while also helping the model’s general intelligence, an area that researchers would care more about.

(Importantly, OpenAI’s recently-released GPT-5.2 isn’t based on the full-blown Garlic model, but rather, an early checkpoint of the model, according to a person with knowledge of the model, so we’ll likely see more improvement there still.)

One last note: somewhat counterintuitively, some of the information we’ve learned about ChatGPT usage has made me more optimistic that it still has a lot of room to grow. We learned during the reporting process for today’s article that many ChatGPT users simply don’t understand the full range of things they can do with the chatbot. That’s partly because the chatbot is so text-based that users might not realize ChatGPT can do things like analyze a picture of your houseplant to understand why it’s dying or look at a picture of your hand in mahjong and tell you whether you’re making an illegal move or not (both of which I’ve done in the last week).

If OpenAI can make ChatGPT’s interface more intuitive and visual, as leaders have promised, more users could discover these under-the-radar applications over time.

How OpenAI’s Organizational Problems Hurt ChatGPT

Over the past year, some OpenAI staffers noticed a concerning change in the way people who used ChatGPT were reacting to improvements in the chatbot.

In prior years, every time OpenAI made a big upgrade to the artificial intelligence that powers the chatbot, usage surged as people easily found ways to get useful responses out of it, one employee said.

But even as ChatGPT attracted more users this year, improvements to the underlying AI model’s intelligence—and the in-depth research or calculations it could suddenly handle—didn’t seem to matter to most people using the chatbot, several employees said.

The trend left employees scratching their heads. The company’s research team had spent months working on reasoning models that spent more time computing answers to complex questions about math, science and other topics than ChatGPT’s previous models. OpenAI bragged over the summer about how its AI had achieved gold-medal–level performance at the 2025 International Mathematical Olympiad, and in the fall it aced the 2025 International Collegiate Programming Contest.

Most of the questions users asked ChatGPT, though, didn’t take advantage of those types of improvements, according to some OpenAI employees.

OpenAI’s focus on “science, math benchmarks, frontier math, coding competitions…doesn’t seem to match who the typical ChatGPT user would be,” said Peter Gostev, AI capability lead at LMArena, a startup that evaluates AI performance and publishes widely cited results. Much of the time, ChatGPT users are “probably asking about pretty simple things, like movie ratings, where you wouldn’t need a model to think for half an hour.”

Data OpenAI published in September about ChatGPT queries seem to back up Gostev’s view.

That issue and other disconnects between OpenAI’s underlying technology and its products created an opening this year for OpenAI competitors such as Google to make gains against ChatGPT. As a result, OpenAI CEO Sam Altman earlier this month issued a “code red” warning to refocus the company on improving its chatbot so it can appeal to more people.

The change in the way ChatGPT users have reacted to new models powering the chatbot shows how the goals of OpenAI’s core AI research division, which develops its technology, don’t always serve the needs of ChatGPT, which drives most of the company’s revenue. It also shows how OpenAI’s reliance on the chatbot for revenue could become a weakness as Google and other competitors find various ways to add AI features to a wide range of consumer products, including search, mobile devices and productivity apps.

The idea that ChatGPT might not crater Google Search is a shift from a year or two ago, when executives at both OpenAI and Google believed ChatGPT could effectively replace the popular search engine. Google Search has since added AI-powered answers at the top of search results, and the company reported in October that the feature was driving “meaningful” search query growth and revenue as “users continue to learn that Google can answer more of their questions.”

OpenAI’s renewed ChatGPT push comes as the company is at risk of falling short of its ambitious user growth goals. At the start of the year, when it had 350 million weekly active users, OpenAI said it aimed to hit 1 billion this year. With less than 900 million weekly active users as of earlier this month, that goal will be tough to meet.

But OpenAI has done an impressive job of convincing more individual workers and businesses to subscribe to ChatGPT for extra features and unlimited usage. The company is now generating more than $19 billion in annualized revenue, largely from such subscriptions, up from $6 billion in annualized revenue in January. That suggests it will hit its goal, set in August, of reaching $20 billion in annualized revenue by the end of this year. The company is also on track to beat its 2025 revenue goal of $13 billion, up from around $4 billion last year, and is looking to raise funds at a $750 billion valuation, 50% higher than its valuation two months ago during a share sale.

These are big and enviable numbers by most standards. But to generate $200 billion in revenue in 2030, as OpenAI has projected, it will likely need to convince weekly users to use the chatbot daily. That way it will have more opportunities to sell ads that it has planned to run in the chatbot or to take a cut from the sale of products users find through the chatbot, employees and investors say. (ChatGPT has roughly 70% of assistant usage globally while also ranking as Apple’s most downloaded free app of the year and capturing 10% of search share in less than three years, a spokesperson said in a statement.)

That will require ironing out its organizational and product challenges. This year, OpenAI’s research group, which has more than 1,000 people and is mostly cordoned off from the rest of the company, has largely focused on developing reasoning models rather than improving AI specifically for the company’s chatbot, according to several employees.

But reasoning models don’t do much for ChatGPT, whose users generally want answers fast, according to a person who worked on them. Typically, reasoning models can take anywhere from several seconds to several minutes to answer a question—which can feel like an eternity to people accustomed to Google’s snappy search results. OpenAI says reasoning models are best suited for completing complex, multistep tasks, reviewing large amounts of code or finding specific information across a trove of company documents.

ChatGPT faces an even bigger problem than the issue with reasoning models: Consumers don’t appear to understand the full range of topics the chatbot can answer questions about, even when it’s using nonreasoning models that give faster answers. That limits how much time they spend using it, several employees said.

In particular, ChatGPT’s text-based design has made it harder for people to discover its other features, such as its ability to analyze images of mechanical or computer errors and provide advice on how to fix them. The current look and feel is somewhat akin to MS-DOS, the text-only Microsoft operating system for PCs used in the 1980s, said ChatGPT product chief Nick Turley. The PC revolution didn’t take off until Microsoft launched Windows, a more visually appealing and intuitive operating system, he added.

Other OpenAI leaders have echoed this sentiment, saying that ChatGPT’s interface will have to change to gain mass appeal. OpenAI’s head of applications, Fidji Simo, said in a blog post this week that ChatGPT is moving “from being primarily text-based and conversational, toward a fully generative UI that brings in the right components based on what [users] want to do.” On Tuesday, the company launched a new image-generation model for ChatGPT users and said it would incorporate more imagery in ChatGPT responses.

But Simo, who joined OpenAI from Instacart several months ago to oversee ChatGPT and other applications, seems aware of the limitations on her side of the company. She recently wrote on her blog that at its core, OpenAI remains a research-focused company and “products aren’t the goal themselves.”

Some rivals to OpenAI, whose main product primarily caters to consumers, don’t seem to be experiencing the same disconnect between their research and product efforts. Anthropic, for example, mostly focuses its research efforts on an application programming interface aimed at businesses. So far, the smarter Anthropic’s models get—especially in generating computer code—the more API sales it makes to other businesses and application developers. At OpenAI, improvements to its models also boost API sales, but they are a small fraction of its current and projected revenue.

For much of the year, Altman seemed to be running OpenAI as if it had already conquered the chatbot market, according to some employees. He embarked on countless other product efforts, including the Sora video app, music-generating AI, a web browser, specialized AI agents, a consumer hardware device, robots and more.

There’s a growing sense among OpenAI executives that ChatGPT could be vulnerable, which has rattled many of them, according to a person who recently spoke with leaders at the company. Altman, as part of his code red declaration, said he wants to move some employees back to working on ChatGPT.

“Product and research are deeply interconnected, not oppositional. Research breakthroughs shape our products, and product feedback shapes research. This is a single, unified strategy for building and safely deploying increasingly capable models, not a division between competing sides,” an OpenAI spokesperson said.

The divergence between OpenAI’s research and ChatGPT product groups emerged over the past year as the company struggled to improve its large language models through traditional training methods that had previously worked. So it focused its energies on reasoning models to eventually reach artificial general intelligence—AI that meets or surpasses human abilities.

Initially, the researchers thought reasoning models could also improve ChatGPT. But at the start of the year, when OpenAI converted its most advanced reasoning model to a version that users could use in ChatGPT, the model’s performance got worse. It turns out that creating a chat-based version of the model unintentionally dumbed the model down.

OpenAI still found ways to bring reasoning models into ChatGPT, where they currently power its Thinking mode and Deep Research agent—launched in February—that generates reports. (Reasoning models also help power Codex, OpenAI’s coding assistant app.) But relatively few of the chatbot’s nearly 900 million weekly active users regularly access those features, several employees have said.

It’s also far from clear that reasoning models will lead to AGI, according to some researchers at OpenAI.

A change OpenAI recently made to ChatGPT implied its reasoning models were becoming a liability for the chatbot. Earlier this month, the company quietly rolled back a feature in its free and lowest-priced ChatGPT subscription tier that automatically routed people’s questions to reasoning models.

OpenAI faces other hurdles in bringing improved models to ChatGPT: Even traditional, nonreasoning AI models can clash with ChatGPT features, such as efforts to personalize the chatbot so it provides different answers based on what it already knows about the person using it.

For instance, in the weeks leading up to its August release of GPT-5, a flagship LLM model powering OpenAI’s products, researchers found that the model’s performance on certain tasks such as coding questions declined after it was integrated into the chatbot, the current employee said. That’s because when users sent a query to ChatGPT, the chatbot would also use information it had about them, such as their occupation, to personalize the answer, the employee said.

But that personal information at times interfered with the model’s understanding of what the user was asking, leading to incorrect answers, the employee said. The company fixed the issue before it released GPT-5, but employees believe they’ll continue to face interference between new models and ChatGPT features.

There are other signs of schisms between research and product at OpenAI. Earlier this year, the company deprioritized the development of its image-generation model, which had temporarily boosted usage and user growth of ChatGPT in March, according to two employees.

It couldn’t be learned why it made that decision, but when Google in August released its own image-generating AI, Nano Banana, to much acclaim from consumers, leaders at OpenAI rushed to improve its image technology, one of the employees said. That prompted a disagreement between Altman, who felt image-generation capabilities were important to ChatGPT’s growth, and Mark Chen, the company’s research chief, who wanted to prioritize other initiatives, they said.

Earlier this month, Altman said in his “code red” alert that image generation would be a key priority in the push to improve ChatGPT. This week OpenAI released a new image-generating model for the chatbot.

In Google, OpenAI faces a competitor that has long held advantages in getting its AI in front of people, including through search, Chrome and its workplace apps such as Gmail. And in recent weeks, Google’s AI models have improved to be roughly on par with ChatGPT in terms of the questions or tasks they can handle adeptly, including generating images and computer code. That makes Google’s chatbot and other AI products more appealing.

Inside OpenAI, leaders are concerned the average chatbot user won’t see much of a difference between ChatGPT and Google’s Gemini, according to a person who has spoken to them. And unlike social apps like Facebook and Instagram, which had staying power because the products got better as the number of people that used them grew, such network effects generally don’t exist in chatbots.

OpenAI is at another disadvantage: its finances. It is burning through billions of dollars a year in cash as it rents more and more servers to train and run its AI, including ChatGPT. While OpenAI is endeavoring to develop its own data centers and server chips to lower those costs over time, Google today can operate more efficiently because a decade ago it began developing specialized servers for AI.

TAE Technologies has already agreed joint venture with UK government’s atomic laboratory

US President Donald Trump’s family has gone into business with the British government, adding a fresh dimension to an already complicated relationship. 

Trump Media & Technology Group, the Trump family media business, said on Thursday that it had agreed to combine with fusion energy company TAE Technologies in a $6bn merger to build “the world’s first utility-scale fusion power plant”.

The twist in the deal is that TAE Technologies, which is backed by US tech group Google and oil major Chevron, this month struck a joint venture with the UK government’s atomic laboratory. 

The state-owned UK Atomic Energy Authority would contribute £5.6mn in equity to the new venture, based in Oxfordshire, the government said.

It touted the partnership as evidence of the “technology prosperity deal” that was signed by London and Washington in September but has since been suspended, amid US concerns over progress on trade talks. 

Now it is also a business link between the Starmer administration and the Trump dynasty.

The Department for Business and Trade said the joint venture was “going through the usual regulatory and due diligence processes”.

One official said the government had not been aware of discussions between TMTG and TAE Technologies at the time the decision was made.

The way the Trumps have enriched themselves rapidly since Donald Trump returned to the White House this year is in contrast to his predecessors, who have tended to make modest financial sacrifices for the duration of their term of office.

In Britain politicians have to divest or manage any potential business or financial interests when they become ministers.

Rishi Sunak, the last prime minister and the wealthiest MP in British history, put his investments in a blind trust while he was in government, meaning they were managed by a third party. 

“This could bring all manner of headaches, as spending government money on a firm associated with Trump will be unpopular with British voters,” said Robert Ford, professor of political science at the University of Manchester.

“But attempts to back out of the deal may provoke anger and even lawsuits from the notoriously litigious Trump,” he added.

According to a Financial Times investigation, the family’s business has already reaped more than $1bn in pre-tax profits over the past year, in part thanks to a cryptocurrency boom fuelled by the administration’s industry-friendly policies.

Trump set up TMTG to run his Truth Social app after being banned from major social networks after the Capitol Hill attack of January 6 2021. Its board includes FBI director Kash Patel and his son, Donald Trump Jr, who will also serve on the board of the new entity announced on Tuesday.

Built on right-leaning online politics, earlier this year TMTG pivoted towards crypto, raising billions of dollars to buy tokens, and is launching several bitcoin funds. 

Just as Trump’s digital currency ventures have netted gains, so he has had no compunction in leaning on Prime Minister Sir Keir Starmer to try to benefit his family’s sprawling golf business. 

During Starmer’s visit to the White House in February, Trump raised the possibility of the Turnberry golf resort in Scotland — which the US president owns — returning as a venue for the Open Championship.

The R&A, the body that runs the Open, the oldest golf championship in the world, in 2021 said it would not host the tournament at Trump’s Turnberry resort in the wake of the January 6 attack. 

Trump has repeatedly asked Starmer to try to overturn that block. “He did go on about Turnberry,” said one person involved in the February visit. 

In July the president took part of his summer holiday at Turnberry, mixing business with pleasure as Starmer flew in to meet him at his hotel with near-full media access.

The two leaders later flew together on Air Force One, the president’s official plane, to view Trump’s new golf course in Aberdeenshire.

Starmer said this year that he “likes and respects” the US president, despite their differences in policy on areas ranging from immigration to wind farms.

By maintaining a friendly approach to Trump, Starmer has been able to secure financial and diplomatic wins for the UK, he has maintained.

In May, for example, London stressed the benefits of a trade pact aimed at cushioning the impact of Trump’s “liberation day” tariffs, which granted lower-tariff quotas for British car and steel exports.

But Washington’s decision this month to suspend implementation of the tech prosperity deal, signed during Trump’s second state visit to Britain in September, is evidence of the unpredictability of the “special relationship” under him.

“Any government dealing with Trump is at risk of finding itself complicit in his moneymaking activities,” said one Labour figure. “But it would be a brave prime minister who decided to snub him or elevated ethical principles above a much-needed investment in the UK economy.”

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The professor, Nuno F.G. Loureiro, was pronounced dead at a hospital on Tuesday morning. The authorities said they had opened a homicide investigation.

The authorities said on Tuesday that they had opened a homicide investigation after a professor at the Massachusetts Institute of Technology was fatally shot at his home in Brookline, Mass.

The professor, Nuno F.G. Loureiro, 47, was a member of the departments of nuclear science and engineering and physics, as well as the director of M.I.T.’s Plasma Science and Fusion Center, the school said.

The Norfolk County District Attorney’s Office said the police responded on Monday night after receiving a report of a man shot at his home. The office said that Dr. Loureiro was brought to a hospital with gunshot wounds, and that he was pronounced dead on Tuesday morning. An office spokesman, David Linton, said on Tuesday that there had not been any arrests in the case.

The Brookline police chief, Jennifer Paster, said that she had deployed patrol cars and officers to Dr. Loureiro’s neighborhood.

“This remains an active and ongoing homicide investigation,” she said in a statement. “In order to protect the integrity of the investigation, we are limited in the information we can share at this time and ask for the community’s understanding and patience.”

Ted Docks, the special agent in charge of the F.B.I. in Boston, said there “seems to be no connection” between the fatal shooting of Dr. Loureiro and a shooting at Brown University on Saturday that killed two students.

M.I.T. said it was encouraging members of the campus community who may be affected by Dr. Loureiro’s death to reach out for support.

“This shocking loss for our community comes in a period of disturbing violence in many other places,” the president of M.IT., Sally Kornbluth, said in a statement. “It’s entirely natural to feel the need for comfort and support.”

M.I.T. named Dr. Loureiro director of the Plasma Science and Fusion Center in May 2024, putting him in charge of one of the school’s largest labs, where more than 250 researchers, staff members and students work in seven buildings with 250,000 square feet of lab space.

In January, President Joseph R. Biden Jr. announced that Dr. Loureiro was one of nearly 400 scientists who had been awarded the Presidential Early Career Award for Scientists and Engineers. The administration called it the highest honor bestowed by the U.S. government on outstanding scientists and engineers at the start of their careers.

M.I.T. said the National Science Foundation had nominated Dr. Loureiro for the award because of his work on the generation and amplification of magnetic fields in the universe.

Dr. Loureiro, who was born and raised in Portugal, received an undergraduate degree in physics from the Instituto Superior Técnico in Lisbon and a doctorate in physics from Imperial College London in 2005. After postdoctoral work at the Princeton Plasma Physics Laboratory in New Jersey and the Culham Center for Fusion Energy, Britain’s national laboratory for fusion research, he returned to Portugal to become a principal investigator at the Instituto Superior Técnico’s Institute for Plasmas and Nuclear Fusion, Ms. Kornbluth said.

He joined M.I.T.’s faculty in 2016, and he was appointed deputy director of the Plasma Science and Fusion Center in 2022. He was an expert on a fundamental plasma process called magnetic reconnection, among other areas of research.

“Nuno was not only a brilliant scientist, he was a brilliant person,” Dennis Whyte, a former director of the Plasma Science and Fusion Center, said in an obituary published by M.I.T. “He shone a bright light as a mentor, friend, teacher, colleague and leader, and was universally admired for his articulate, compassionate manner.”

CNN Portugal reported that Portugal’s minister of foreign affairs had announced Dr. Loureiro’s death in Parliament. On Tuesday, the U.S. ambassador to Portugal, John J. Arrigo, released a statement expressing his condolences to Dr. Loureiro’s family, friends and colleagues.

“We honor his life, his leadership in science, and his enduring contributions,” Mr. Arrigo said.