Question of the Week: What is the next frontier for AI M&A and how will it shape the future landscape of the industry?

Chris Ahn

Partner, Mergers and Acquisitions

“We are currently seeing a lot of follow-on investments in AI. For example, sponsors are making additional investments in portfolio companies or using cash and/or equity from the portfolio balance sheet to fund acquisitions of minority investments or joint ventures with AI-focused companies. In minority/JV deals, this has often been combined with related licensing/partnership agreements so that the portfolio gains (i) access to the technology, (ii) participation in the AI company’s team, and (iii) a stake in the AI company’s future growth (and, if possible, opportunities for future investments and/or acquisitions of the company). In the short term, I think we will continue to see smaller deals that are more opportunistic and synergistic with existing platforms. I don’t expect all of these companies to start selling at very high valuations in the near future, in part because macro factors (lower interest rates, etc.) are not yet large enough to drive many high valuations, and also because the market is evolving so quickly and it is not yet clear which companies will have lasting power.”

Wai Choi

Partner, Technology, Media and Telecommunications

“It’s a very fragmented space, especially when you consider the full range of AI types that extends far beyond the headlines focused on generative AI tools. In the GenAI arena, as the rapid arms race in model development continues, we’re seeing a wide range of industry-specific or use-case-specific offerings coming online based on a model offered by one of the leading developers (often with the flexibility, by design, to substitute an alternative model if needed). I expect this trend to continue. At the portfolio company level, we’re also helping companies of all types grapple with whether and how to incorporate AI to remain competitive and drive high valuations in the sales process, while remaining agile enough to adapt to further technological advances. “On the due diligence side, we have seen increased scrutiny over whether companies are practicing good GenAI hygiene and implementing appropriate policies and safeguards around confidentiality, intellectual property rights, privacy, cybersecurity, bias and legal compliance, including as private equity and strategic acquirers continue to rely heavily on reassurance and insurers are increasingly sensitive to the potential implications of AI use.”

Oliver Howley

Partner, Technology, Media and Telecommunications

“Foundation model developers have understandably attracted the attention of investment professionals. However, in the medium to long term, I expect there to be only a handful of significant players in the Foundation model market, and only a small number of companies will have the opportunity to invest in them. That’s why I see attention shifting to three other types of targets. First, we have intermediaries who add valuable proprietary content, such as industry knowledge, to the Foundation model through fine-tuning or search-augmented generation. Second, we have non-GenAI developers, such as those offering discriminative AI models that can categorize expenses and bills. These models can be more cost-effective than generative models for some tasks, and can still be plugged into generative models to produce complex results. Third, we have “pickaxes and shovels” and “complementary targets”—such as data center providers, data labeling, and GenAI inversion and model poisoning defenses. Goals like these will ultimately keep the AI industry expanding, offering stable and meaningful value beyond the spotlight of the latest breakthroughs in foundational models.

Andrew Wingfield

Partner, Mergers and Acquisitions

“Proof of concept in AI is high risk compared to established technology platforms. While AI M&A discussions are increasing, they tend to be in niche areas. Companies are more focused on adopting AI for portfolio use than acquiring the technology itself. I think we may see activity in AI-adjacent areas. We’re seeing a noticeable increase in data center investments to support front-end AI engines. Large cap sponsors see this as a growth area that requires more infrastructure due to the growth in machine learning and AI adoption. While technology investments are facing scrutiny and valuation gaps, large corporations are leading the market, potentially driving more direct investment in AI platforms—a kind of vicious cycle.”

(See source.)