The numbers tell a compelling story. Global M&A deals involving AI and machine learning rocketed from 717 deals worth $44 billion in 2023 to 904 deals valued at $78 billion in 2024, according to data provided by PitchBook for this article.
As AI continues to captivate the public's imagination and attract significant investment, both public and private companies are expected to boost their M&A ambitions in this area.
"There are certainly many early indicators of continued bullishness and aggressive activity," said Mark M. Bekheit, global vice chair of Latham & Watkins LLP's M&A practice.
"What I simply say is, follow the money. ... Pick your flavor of AI, but that is effectively where all the VC money is going, and historically that's an indicator of where the M&A activity will pick up from there," Bekheit said.
The New AI-Fueled M&A 'Ecosystem'
What's driving the AI acquisition frenzy is more than just FOMO, or fear of missing out, though that's certainly part of it.
Dario De Martino, a transactional partner at A&O Shearman and co-head of the firm's fintech and blockchain group, said AI acquisitions have become a core element to competitiveness, with both strategic and private equity firms actively seeking AI companies.
"Quite frankly, every deal that I've touched over the past couple of months has had an AI component, or is being entirely driven by AI," De Martino said. "Companies are realizing that AI isn't just nice to have. It's more like the core to their competitiveness."
Activity is ramping up in areas such as cloud computing, data analytics and generative AI — which has become a buzz phrase for good reason — and the infrastructure needed to support these models, attorneys said.
Demand for faster processing "and more scalable cloud services is driving the bulk of M&A," said Derek Liu, an M&A partner in Baker McKenzie's Silicon Valley office specializing in tech transactions.
Liu said the proliferation of AI is fundamentally changing how software companies innovate, compete and grow. He described two critical layers of AI: foundational large language models, or LLMs, from companies like OpenAI and Anthropic, and vertical application development.
"The promise of AI is not having a little chatbot you can have a conversation with," Liu said. "It's about integrating that intelligent functionality into virtually every industry's software."
Small companies can now develop sophisticated AI applications without enormous upfront costs. This has fueled a surge of "AI-native" startups in legal tech, healthcare and customer relationship management — making them attractive acquisition targets, Liu said.
"The beauty of this ecosystem is that all the startup has to do is pay for an [LLM] subscription, and boom, they get access to all of that and just build their product on top of that," he said.
Private Players Pour Money Into AI
Private equity deals involving AI companies grew from 272 deals worth $21 billion in 2023 to 332 deals valued at $26 billion in 2024, according to the PitchBook data.
Venture capital saw even more dramatic growth, with deals increasing from 8,748 to 8,909, and total value jumping from $89.2 billion to $134.1 billion.
"PE sat on the sidelines for a bit, but they're now hunting for AI companies to roll up in their larger platforms, or sometimes merge an AI company within other tech companies they have in their portfolio," said De Martino of A&O Shearman.
Builders of generative platforms are generating heaps of funding despite fierce competition both in the U.S. and from their Chinese counterparts.
For example, Amazon-backed Anthropic, the startup behind a new generative AI model guided by Claude, was reported to have recently finalized a $3.5 billion funding round that pushed the startup's valuation to $61.5 billion.
The funding includes investments from Lightspeed Venture Partners, General Catalyst and Bessemer Venture Partners, and Abu Dhabi-based investment firm MGX is also in talks to participate, the report said.
That came as competitor OpenAI was also said to be in discussions to raise up to $40 billion at a $260 billion valuation.
Among other deals in the PE space, Blackstone recently invested $300 million in AI and data intelligence solutions platform DDN, and New Mountain Capital acquired Machinify Inc., a healthcare payments software provider.
Navigating the AI M&A Minefield
M&A attorneys are facing a complex new legal and regulatory landscape, De Martino said, noting that "regulators don't treat AI acquisitions the same way that they would a factory merger."
Considerations include antitrust regulations, national security matters, IP and data privacy issues, as well as intellectual property challenges and potential copyright infringements, attorneys said.
Kenton J. King, a Skadden Arps Slate Meagher & Flom LLP M&A partner and tech industry veteran, said he hasn't seen anything like the current AI boom since the dawn of the internet, adding that a "tremendous amount" of legal issues have cropped up.
"When there are big shifts in the industry, it means that everybody has to rethink where they are on the chessboard. Do they have the right strategic focus, do they have the right skills, the right assets to play into the future?" King said. "[AI] is something that's pervasive and foundational, meaning that it touches every company, every enterprise, so everybody's having to think about where they are."
Generative AI platforms are "just the surface," King noted, pointing out the extensive infrastructure required: "a massive need for computing power, massive need for engineering talent, massive need for energy."
Utility companies are repositioning themselves to provide energy for huge data centers. But the potential applications of AI span industries, from legal work to medical diagnostics. For example, King spoke about AI providing a second opinion for clinicians.
"We have trained clinicians that look at X-rays ... but you can imagine a second opinion easily from an AI tool that has a body of knowledge that is far larger than any one clinician or doctor," he said.
Preparing for the AI M&A Future
King said Skadden has an AI practice made up of a tightly coordinated group of attorneys across disciplines — litigation, corporate, IP, privacy, security — that stays on top of the technology and the related legal issues.
"There's a tremendous amount of pure legal issues that are going on in this area," he said. "Everybody as a base case is trying to keep up with what the industry is doing, what tools are being created and evolving, and what clients or potential clients are doing."
De Martino emphasized that regulators both in the U.S. and in Europe are looking to prevent large market players from gaining dominance through the consolidation of data, technology or industry talent.
"We see AI as a sort of subcategory of the tech industry group, and we are staffing deals with partners and associates that have specific expertise," he said.
Bekheit, the Latham global vice chair of M&A, stressed the importance of ensuring that the firm has at least one AI subject-matter expert on teams handling AI-related deals.
His Latham colleague, Michael Rubin, a regulatory partner and global chair of the artificial intelligence practice, said that broader training across the firm is ongoing and crucial as the sector continues to grow.
The firm hosts academies, learning modules and other in-house programs with curriculum on not just AI technology but the entire AI ecosystem, as well as the many laws and regulations — from Europe's AI Act to various state laws in the U.S. — that can impact due diligence on M&A, Rubin said.
"Understanding the full range of the AI ecosystem helps people understand our client base, because that ecosystem is our client base, whether it's an energy producer, whether it's a data center provider, whether it's an LLM developer, or whether it's one of the thousands of companies integrating these products into their daily operations," he said.
--Editing by Marygrace Anderson and Rich Mills.
For a reprint of this article, please contact reprints@law360.com.
