Navigating the AI investment landscape: strategic considerations in AI business acquisitions

Artificial intelligence, although still in its infancy, is continuing to evolve rapidly and proving to be one of the most dynamic and transformative technologies of our time. As AI technologies continue to develop, so too does the number of number of AI businesses. The number of new AI companies created in the U.S. alone has grown 75% each year between 2014 and 2017, with a huge spike in 2023 ^[1]. With the investment of billions of dollars by Big Tech in AI, more investors and acquirers are increasingly turning their attention to AI businesses.

While both the UK and US are aggressively pursuing AI leadership, their approaches diverge in emphasis. The US continues to dominate in scale, with $109.1 billion in private AI investment in 2024 (exceeding the combined total of China, the European Union, and the UK by $25.4 billion) ^[2], and a strong focus on frontier technologies and national security. The UK, by contrast, is leveraging strategic partnerships and public sector transformation to drive adoption, with a regulatory environment that prioritises ethical standards and societal benefit (namely, much of the UK's AI investment is in life sciences, healthcare, and wellness ^[3]). This divergence presents unique opportunities for firms with transatlantic capabilities to navigate both ecosystems effectively, by balancing scale and innovation in the US with strategic integration and compliance in the UK.

Market momentum, investment flows and increased acquisitions

The AI investment landscape has experienced unprecedented growth. According to Stanford University's AI Index Report 2025, U.S. private investment in AI reached $109.1 billion in 2024 ^[4]. This growth reflects continued confidence in AI's commercial viability. AI business usage is also showing increased growth with 78% of businesses reporting using AI in 2024, an increase of 55% from the prior year ^[5]. Such growth has increased competition among investors and acquirers, driving up valuations for both investors and acquirers. With valuations still at high, especially when compared other industries, concerns of an AI bubble are increasing. If valuations start to decline, companies may look to strategic acquisitions to acquire AI technologies and talent instead of building from the ground up.

Over the Atlantic, the UK is rapidly positioning itself as a global AI hub, with over £31 billion in foreign direct investment committed by major US tech firms in 2025 alone ^[6]. This surge is supported by government initiatives such as AI Growth Zones, the National Data Library, and targeted infrastructure investment in supercomputing and quantum capabilities. As outlined above, UK investors and acquirers are increasingly focused on AI-native companies that align with domestic priorities from which societal benefit can be derived, including NHS integration and professional standards.

What does all this mean for the AI investment landscape? Increased competition among investors and acquirers and a renewed focus on diligence. It is also leading investors and acquirers to re-emphasise business fundamentals and sharpen their focus on AI companies that demonstrate clear revenue models and practical applications rather than purely research-oriented ventures.

Key investment considerations

However, investing in or acquiring AI businesses requires an understanding of unique risks, opportunities, and valuation considerations that distinguish this sector from other technology investments.

Technology differentiation and moats

AI businesses often face the challenge of demonstrating sustainable competitive advantages. Unlike traditional software companies that may rely on network effects or switching costs, AI companies must establish defensible positions through proprietary data, specialised algorithms, or domain expertise. Besides the renewed focus on business fundamentals, investors are also evaluating whether target companies possess unique datasets, specialised talent, or technological approaches that create meaningful barriers to entry. There is also increasingly more interest in AI-native companies rather than AI-based companies where AI is added as a bolt-on feature or selectively embedded in certain products.

Talent and human capital

AI companies are particularly dependent on specialised talent, with data scientists and machine learning engineers commanding premium compensation. The scarcity of AI expertise creates both opportunity and risk. According to the World Economic Forum's Future of Jobs Report 2023, demand for AI specialists is expected to grow by 40% through 2027. Acquirers must assess not only the target company's current talent but also its ability to attract and retain key personnel post-acquisition.

Regulatory landscape

The regulatory environment for AI is also rapidly evolving. The EU's AI Act, which came into force on 1 August 2024, establishes comprehensive regulations for AI systems based on risk levels, the first of which took effect on 2 February 2025. Similarly, the U.S. is developing AI governance frameworks. So far this year, all 50 states, Puerto Rico, the Virgin Islands, and Washington, D.C., have introduced AI legislation and 38 states have already adopted or enacted approximately 100 measures relating to AI ^[7]. As we have seen with the proliferation of data privacy laws and regulations, we are seeing an increase in new laws and regulation around AI. As noted throughout our commentary in our white paper on AI, "The View from the Top"., it remains impossible for legislation to keep pace with the technology and use cases and striking the right balance between regulation/legislation to ensure a safe and ethical environment that still encourages creativity, innovation and efficiency is critical for both the UK and US to be seen as leaders in AI.

With this ever moving regulatory environment, there is a need to ensure that investment in and development of AI is in a manner that conforms to the legislative guide-rails. Significant equity value can be preserved if businesses get this right and executives, shareholders and founders need to be aware that this will form an important part of the diligence process for investors and acquirers - evaluating the target’s regulatory compliance to assess potential risk of non-compliance.

Due diligence imperatives

AI investments and acquisitions require due diligence beyond traditional financial and legal review and require particular focus on technical due diligence, data rights and privacy and intellectual property rights.

• Technical due diligence: Independent assessment of algorithms, data quality, model development, model performance, and scalability. This often requires engaging AI specialists who can evaluate the technical merit and commercial potential of the underlying technology. Part of this technical diligence should include an understanding of who was involved in the development of the technology and the stages of its development.
• Data rights and privacy: Comprehensive review of data sources, usage rights, and privacy compliance, particularly given increasing global data protection regulations.
• Patent analysis: Given the rapid pace of AI innovation, to the extent there are patents covering the technology, careful review of the patent landscape is important to identify potential infringement risks.

Strategic integration considerations

For corporate acquirers, successful AI integration requires careful planning. AI capabilities often need to be embedded throughout an organisation rather than operating as standalone units. This integration challenge is compounded by cultural differences between traditional enterprises and AI-native companies.

Research by Boston Consulting Group indicates that companies successfully integrating AI capabilities see 6-10% revenue increases, but only 10% of companies achieve significant financial impact from their AI initiatives. This disparity underscores the importance of thoughtful integration planning.

Looking forward

The AI investment landscape will likely continue evolving rapidly. Investors and acquirers should focus on companies with clear paths to profitability, defensible competitive positions, and experienced management teams capable of navigating regulatory and technical challenges. As the market matures, we expect to see increased consolidation, with larger technology companies continuing to acquire specialised AI capabilities and traditional enterprises seeking to build AI competencies through strategic acquisitions. We also expect the number of new AI companies being formed each year to continue to grow as more and more founders look at the promise of AI as their next gambit.

Success in AI investing requires balancing the significant potential rewards with careful risk assessment and specialised expertise throughout the investment and acquisition process.

Womble Bond Dickinson's transatlantic team of Digital lawyers understands how to deliver Artificial Intelligence services across a global footprint. This article in one in a series comparing the US, UK and EU legal regimes around Artificial Intelligence – find them all on our AI hub here.

Sources

[1] Center for Security and Emerging Technology Issue Brief, “Acquiring AI Companies: Tracking U.S. AI Mergers and Acquisitions,” November 2024, page 9.

[2] Stanford University, "Artificial Intelligence Index Report 2025", Chapter 4 (Economy), page 4.

[3] Department for Science, Innovation and Technology, UK Government, "Artificial Intelligence Sector Study 2024".

[4] Ibid, page 3.

[5] Id.

[6] Department for Science, Innovation and Technology, UK Government, "Press release on the US-UK tech agreement".

[7] The National Conference of State Legislatures, “Summary of Artificial Intelligence Legislation,” July 10, 2025 available at Artificial Intelligence 2025 Legislation.