Goldman Sachs M&A Head Gene Sykes: AI Drives Record Deal Year as Funding Shifts from VC to Tech Giants
In an Odd Lots podcast interview, Goldman Sachs co-head of global M&A Gene Sykes explains that 2026 is the largest M&A year in history, driven primarily by AI infrastructure demand. He notes that unlike the dot-com era, current AI buildouts are funded by major tech platforms with massive free cash flows rather than venture capital. Sykes also reveals that only 2% of companies report a positive EPS impact from AI, indicating that enterprise integration is still in its early stages.
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Gene Sykes, co-head of global mergers and acquisitions at Goldman Sachs, stated in an Odd Lots podcast episode that 2026 represents the largest M&A year in history, surpassing even the peak volumes seen in 2021. This surge is not driven by traditional industry consolidation but by urgent corporate demand for artificial intelligence capabilities. Sykes observed that nearly every sector—from natural resources to power generation—is allocating capital and adjusting strategies to support AI infrastructure development.
Unlike the TMT construction wave during the early 2000s internet bubble, the primary investors in today's AI infrastructure have shifted fundamentally. Sykes emphasized that while early internet buildouts were financed largely by venture capital, the current AI expansion is being funded by the world's most successful large technology platforms. These companies have accumulated hundreds of billions of dollars in free cash flow, allowing them to finance massive infrastructure projects without relying on external funding or IPOs. This change in capital structure suggests greater financial resilience for the current AI expansion but also alters the dynamics of the M&A market.
Despite the hot M&A market, Sykes provided data revealing that actual progress in enterprise-level AI integration remains limited. According to internal Goldman Sachs analysis, only 2% of companies currently cite a positive impact on earnings per share from their use of AI in their financial reports. While perhaps 20% to 30% of firms claim to have implemented AI strategies, very few have deeply embedded AI into workflows to generate quantifiable financial results. This indicates that current M&A activity is driven more by expectations of future potential and competitive pressure than by realized profit growth.