Analysis-Unglamorous world of 'data infrastructure' driving hot tech M&A market in AI race

Amidst a general slowdown in M&A, deals involving data infrastructure companies are surging, driven by the critical role of data in AI development; these deals account for approximately 25% of global M&A activity. Legacy tech companies like Meta, Salesforce, and ServiceNow are acquiring data specialists, such as Salesforce's $8 billion acquisition of Informatica, to enhance their AI capabilities and remain competitive against firms like OpenAI and Google. Investment bankers note that the urgency to deploy effective AI is making data management firms increasingly valuable, with potential targets including Confluent, Collibra, and Dataiku.

Analysis

The M&A landscape is experiencing a significant divergence, with dealmaking slowing across most industries but surging within the data infrastructure sector, primarily fueled by the imperative for advanced AI development. Tech deals constituted $421 billion, or approximately 25% of the $1.67 trillion in global M&A in the first five months of the year, an increase from 20% in the previous year and 17% in 2023, with AI software makers representing nearly three-quarters of this tech deal value. Legacy technology giants, including Meta (NASDAQ:META), Salesforce (NYSE:CRM), and ServiceNow (NYSE:NOW), are aggressively acquiring data specialists to bolster their AI capabilities and maintain competitiveness against AI leaders like OpenAI and Google (NASDAQ:GOOGL). Recent notable transactions underscore this trend: Meta's $14.8 billion investment for a 49% stake in data-labeling company Scale AI, Salesforce's planned $8 billion acquisition of data integration company Informatica, ServiceNow's purchase of data catalogue platform Data.world, and IBM's (NYSE:IBM) acquisition of data management provider DataStax. Investment bankers identify enterprise data infrastructure and analytics firms such as Confluent (NASDAQ:CFLT), Collibra, Sigma Computing, Matillion, Dataiku, Fivetran, Boomi, and Qlik as potential near-term acquisition targets, given their crucial role in helping businesses integrate, analyze, and store information. This M&A urgency is further contextualized by Gartner's forecast of worldwide generative AI spending reaching $644 billion in 2025, a 76.4% increase from 2024. However, the pursuit of data assets is not without peril, as highlighted by the necessity of high-quality, well-organized data to avoid erroneous AI outputs, exemplified by Air Canada's chatbot providing incorrect information.

Key Decisions for Investors

• Investors should closely monitor companies specializing in enterprise data infrastructure, data integration, and AI-enablement, as they are prime M&A targets and beneficiaries of the secular growth in AI, potentially offering significant upside.
• Consider the strategic implications for legacy tech companies (e.g., META, CRM, NOW, IBM) making these acquisitions; successful integration of data assets could enhance their competitive moat and AI-driven revenue streams, while integration challenges or overpayment could pose risks.
• Evaluate the quality of underlying data strategies and management capabilities within AI-focused investments, as the effectiveness of AI models and the ultimate return on investment heavily depend on the ingestion of well-curated, relevant data, mitigating risks associated with flawed AI outputs.