AI trends for 2025: M&A and investments

Advancing AI capabilities through M&A

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AI trends for 2025: M&A and investments

AI trends for 2025: M&A and investments

Advancing AI capabilities through M&A

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January 10, 2025

The surge in AI adoption has significantly influenced corporate strategies, including in the realm of mergers and acquisitions (M&A). The growing M&A activity is focused on companies acquiring related technology and technical talent to rapidly prepare for the disruption that AI is creating. Companies are increasingly leveraging M&A to enhance their AI capabilities, aiming to stay competitive in a rapidly evolving technological landscape.

The role of AI in M&A

AI's integration into M&A transactions is multifaceted, encompassing the acquisition of AI technologies, skills and processes. According to our study, nearly two-thirds (64%) of business leaders plan to use M&A to bolster their AI capabilities within the next 12 months, with this figure rising to 70% over the next three years. Acquiring businesses with existing AI capabilities offers a relatively efficient way to onboard advanced technology and expertise, potentially leading to market expansion, enhanced agility and cost reductions.

However, the decision to pursue M&A for AI capabilities is not without challenges. The fast-paced and ever-changing AI landscape means there are significant gaps in the market and the uncertainty regarding which companies will ultimately rise to the top may compel organizations to consider alternative approaches. These alternatives include strategic partnerships with AI vendors and tech firms, taking minority stakes in AI organizations or purchasing third-party AI solutions as a service.

AI use also requires a number of inputs that are seeing dramatic increases in demand including increased computing power to run AI models. Major chip manufacturers have seen significant increases in demand for the components required to run AI models. AI also requires increased power, which is forcing governments and companies to consider how AI development growth can be supported by adding to existing power sources and energy grids, including renewed interest in nuclear power.

Regulatory considerations: the EU AI Act

The regulatory environment surrounding AI is becoming increasingly stringent, particularly with the introduction of the EU Artificial Intelligence Act (AI Act). This legislation, which recently came into force, imposes comprehensive compliance requirements on providers, deployers, importers and distributors of AI systems. The AI Act categorizes AI systems based on their perceived risk, with certain high-risk AI systems subject to rigorous regulations, including human oversight, technical documentation and post-market monitoring.

In the context of M&A, identifying and categorizing AI systems and General-Purpose AI models within the target company is crucial. The AI Act's tiered approach to regulation means that AI systems employing manipulative techniques or exploiting vulnerabilities are entirely prohibited, with non-compliance resulting in substantial fines. High-risk AI systems, such as those used in employment or education, are subject to stringent rules, while other AI systems posing limited, or no risks may fall outside the AI Act's scope.

Legal and compliance risks

Governments and regulatory organizations around the world have started developing legal principles and frameworks relating to the regulation of AI, with new regulations coming into effect on a regular basis. These regulations have the potential to impact AI transactions in two ways: (i) new opportunities to develop technology to adhere to the regulations, and (ii) new regulations that might negatively impact an AI company's service or strategy. Key themes of these regulations include human rights and equality, human oversight, transparency of AI use, sustainability and security.

The use of AI in M&A transactions also entails significant legal and compliance risks, particularly concerning copyright law. The ownership and licensing of the input, training data and output of AI systems are critical issues. The input and training data, which enable AI systems to learn and perform tasks, can be subject to copyright protection. The target company may have obtained these materials from various sources and, depending on the terms and conditions, may have limited rights to use, modify, share or transfer them.

The output of AI systems, which may be similar or identical to the input or training data, can also be protected by copyright or other statutory provisions. If the target company lacks the necessary rights or licenses to use, exploit, distribute or transfer the output, it may face liability risks, including claims for infringement, damages and injunctions. These risks could extend to the buyer, who may assume the target company's liabilities post-acquisition.

Due diligence and mitigation strategies

As executives and professional advisors improve their understanding of value generators and risks of AI-related companies, the due diligence process and purchase agreement negotiations are expanding to capture AI-related concepts of data use and ownership, copyright development and forthcoming regulatory risk. This underscores the importance for AI-related companies to evaluate their advisors' expertise in a rapidly developing specialized transactional marketplace. We also anticipate that there will be a significant increase in data owners enforcing their copyrights in data sets used without the owner's consent or a license to do so.

Private equity's increasing involvement in AI M&A

Over the past three years, it was estimated that 30% of AI-related M&A transactions were completed by a financial acquiror.¹ There are a number of factors that we see supporting this level of private equity (PE) involvement. Artificial intelligence is poised to impact many traditional industries where PE funds hold ownership positions. The transformational possibilities of AI adoption in those industries can create significant efficiencies in operations, and operational efficiency improvement is a fundamental lever for PE funds to deliver returns to investors, and which can also result in significant value creation for the AI companies in which these PE funds invest. Although there are some indications that the available dry powder held by PE funds has decreased slightly in 2024, available cash for investments also remains at or near all-time historical highs.

In conclusion, while M&A offers a strategic avenue for enhancing AI capabilities, it requires careful consideration of regulatory, legal and compliance risks. Companies must conduct comprehensive due diligence and consider alternative strategies to ensure a successful and compliant integration of AI technologies.

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