As the landscape of artificial intelligence continues to evolve, financial experts from leading institutions predict a surge in mergers and acquisitions (M&A) that will heavily focus on data and infrastructure-related companies. This shift is driven by the industry’s imperative to develop robust AI capabilities and enhance data management practices.
In 2025, industry leaders from firms such as Goldman Sachs, Bank of America, and Axom Partners foresee an expectation that the AI sector will amplify its M&A activities. This trend is partly influenced by macroeconomic indicators like declining interest rates and political factors that provide a conducive environment for corporate transactions. According to Neil Kell from Bank of America, success in deploying AI applications heavily relies on effective data management and integrity, positioning these functions as primary areas of interest for acquisitive companies.
Brandon Hightower of Axom Partners points out the ongoing ‘arms race’ in AI, particularly around infrastructure and talent acquisition, which is expected to maintain its momentum. Tech firms centered on critical data operations are anticipated to lead the way in the AI M&A landscape, with a focus on developer tools and resource optimization enterprises providing essential ‘pickaxes and shovels’ for AI development. Notably, Scott Denne from S&P Global Market Intelligence highlights that while generative AI firms have seen limited deal activity, significant investments continue in companies fortifying AI infrastructure, including storage and cloud solutions.
In the previous year, the M&A spending on AI and related technologies soared to $82 billion from $55 billion the year before, as reported by 451 Research. This increase encompasses purchases of AI-driven products, as well as supporting technologies like software and hardware crucial for AI progression. A favorable borrowing environment due to lower interest rates and narrowing price expectation gaps between buyers and sellers, including AI companies, are critical reasons for the uptick in M&A activities. Moreover, the appointment of Andrew Ferguson to the Federal Trade Commission is perceived positively by market analysts, suggesting further strengthening of large tech corporations.
The anticipation of intensified AI M&A activities has bankers emphasizing the importance of core components necessary for AI success. Jung Min of Goldman Sachs stresses the significance of data infrastructure and analytics, along with developer tools that play a crucial role after AI models are trained. The quest to optimize data quality and flow has been a focal point for major AI players, as illustrated by recent transactions like OpenAI’s acquisition of Rockset, aimed at improving data retrieval and pipeline efficiency.
Significant acquisitions this year by big data companies like Databricks and Snowflake underscore the strategic focus on data. By controlling data and AI models, these companies position themselves for future prominence in the AI sector, according to industry expert Alan Bressers. Furthermore, the drive for scalability prompts acquisitions of infrastructure firms, with Nvidia’s purchase of OctoAI and its pending acquisition of Run:ai showcasing this trend.
Aside from the tech-centric M&A, cross-sector movements are likely, with AI’s potential extending into areas like industrial automation, customer service, and customer relationship management. Companies involved in automating the supply chain and machine interactions present promising opportunities for AI applications. Salesforce’s aggressive push into AI for customer engagement exemplifies this, suggesting potential moves by competitors such as ServiceNow, Braze, and HubSpot to enhance their offerings.
The prediction of an upcoming wave of M&A activity within the AI sector underscores the critical need for improved infrastructure and data management. As companies strive to harness the power of AI, strategic acquisitions in these areas could provide a significant competitive edge, driving innovation and efficiency across various industries.
Source: Businessinsider
