The Flow of Capital into Gen AI: Implications for Your Business

By: Kevin McClelland, Head of Citizens Technology Investment Banking | February 2025

A flurry of investment activity continues in the emerging field of generative AI. Both strategic and financial investors are racing to secure a foothold in the biggest technological wave since cloud computing. For corporate decision-makers, understanding the scope and focus of these investments can help guide their approach to leveraging AI most effectively.

A capital wave continues to roll across generative AI companies — here’s what it means for midsize businesses.

Intense flow of capital, especially from VC

As the technology for large language models (LLM) has matured in recent years, a competitive capital race has defined the landscape for companies developing generative AI and related applications.

Specific investments range widely, but the cumulative total of capital invested in generative AI over 2023 and 2024 is more than $85 billion, according to TechCrunch¹. Many generative AI companies now have post-deal valuations over $5 billion, with some valued as high as $157 billion. The sector’s high valuations reflect how competitive the technology has become – and how competition for equity stakes in these companies has intensified.

Some of the largest investments from financial investors and strategic firms, such as Google, Microsoft, and Amazon, have been made into companies developing foundation models, including OpenAI, Anthropic, and xAI. These substantial funding rounds have not only propelled the development of more reliable and versatile foundation models; they have also fueled an ecosystem of innovation. By providing the capital for extensive research and development, they enable faster iteration cycles, attract top-tier AI talent, and support the infrastructure required to train and deploy large-scale models. In turn, accelerating mainstream adoption of generative AI as a new wave of applications leverage enhanced capabilities.

Many more investments are being made in AI applications. AI-application companies are building the tools needed to apply generative AI to specific use cases – such as ones that help developers create software.

A familiar investment pattern

The flow of capital in these specific patterns – major investments into foundation models by strategics and VC, alongside a flurry of application-level investments – has similarities to the capital race in cloud computing 20 years ago. For cloud computing, strategic companies like Amazon, Google, and Microsoft raced to establish leadership in the core technology. In the years since, VC investments have continued to flow into the sector, supporting the development of derivative and related applications.

If generative AI follows a similar pattern, a capital surge could continue for years as the technology matures. A “long tail” of investments could persist as entrepreneurs find new ways to apply generative AI to industry-specific uses.

What it means for business leaders

Companies have embraced generative AI. In Citizens’ 2025 AI Trends survey of midsize-company CFOs and private equity firms, three-quarters of respondents said they plan to increase their budget for AI tools in the next five years. Customer service functions are a popular use case for generative AI technology at midsize companies, as are predictive analytics and cybersecurity.

Corporate CFOs also point to AI’s value in payment processes. In fact, 63% of midsize-company CFOs said AI has made payment automation significantly easier. Fraud detection and cash-flow forecasting were other popular financial use cases noted by CFOs.

PE firms also use AI in their financial functions. More than half of private equity sponsors use AI for portfolio monitoring. PE firms also said they use AI in exit strategies, due diligence, and investment analysis.

Given the vast capital needs of AI foundation models, few midsize companies will have the resources to develop standalone in-house LLMs. As with cloud computing, the landscape of vendors has proliferated and could continue to grow. Midsize companies may have more and better options for off-the-shelf AI services that improve processes and/or lower operational costs as the AI-application landscape matures.

Actions to consider

• Stay informed about investment trends in AI to track the maturity of application technology. Monitoring investment trends can also help expand your team’s awareness of new applications that could be useful to your industry or business model.
• Track peers for indications about their approach to AI to benchmark your company’s options and potential opportunities.
• Establish an internal cross-functional working group to share ideas and information about the evolution of AI and its business application.