Inside the data center financing boom — and the teams Wall Street is building to win it

Wall Street is experiencing a significant transformation as banks rush to finance AI-driven data centers, with deal values soaring into the tens of billions. The landscape has shifted so dramatically that $100 million financings now seem trivial compared to the billion-dollar benchmarks that have become the new standard. Adam Lewis, a managing director at Citizens Bank, notes, "If you can't invest a billion dollars, we don't even want to talk to you," highlighting the substantial financial commitment required in this rapidly evolving sector. The rising costs associated with land and energy have pushed these projects beyond traditional commercial real estate loans, necessitating a shift towards large-scale infrastructure financing. Major banks like Morgan Stanley, Goldman Sachs, and JPMorgan are forming integrated teams across various disciplines to better understand the complexities of data center construction, aiming to capitalize on what could be Wall Street's largest-ever financing opportunity. Citigroup's internal memo suggests that the buildout of AI infrastructure could demand upwards of $3 trillion by 2030. In response, Citi is establishing a dedicated AI infrastructure group to streamline funding processes and coordinate across different banking sectors as projects become larger and more intricate. The immense scale of this buildout is beginning to stretch the financial resources of some of the world's leading tech companies, which face pressures to keep pace with infrastructure developments without overloading their own balance sheets. Fred Turpin, global chair of investment banking at JPMorgan, describes this moment as the "largest investment cycle in the history of capitalism." To bridge the financial gaps, Turpin has organized a cross-disciplinary working group that connects technology and energy specialists with bankers experienced in private capital markets. This collaboration enables the bank to initiate projects using its own funds before tapping into long-term investments from sovereign wealth funds and pension plans, which seek stable, long-term returns. As the demand for AI infrastructure continues to grow, bankers are leveraging various sources of capital, including loans, bonds, and private investments, often packaged into singular financing structures from the outset. Goldman Sachs has adapted to this shift through its Capital Solutions Group, created to unify origination, structuring, and capital distribution as deal complexity escalates. Notably, at Morgan Stanley, a dedicated task force focused on data centers has been formed, spearheaded by investment bankers Richard Myers and William Graham. They have successfully arranged significant financing deals, including a $2.6 billion agreement for CoreWeave and a groundbreaking $27 billion bond for a collaboration between Meta and Blue Owl. This evolving landscape necessitates collaboration among specialists across various sectors to secure the necessary capital. Understanding the intricacies of data center financing is critical, as these projects intersect real estate, energy, and technology. Bankers now need to be adept at interpreting technical documents and assessing potential risks associated with project execution. Lewis emphasizes the importance of being knowledgeable about the physical realities of these operations, stating, "We can read electrical diagrams and mechanical diagrams and understand land use permits and power configurations." As demand for these projects persists amid constraints on power and resources, questions arise about the sustainability of this growth. Goldman Sachs' Greenwood points out that discussions are evolving, with clients now considering concepts like "terrestrial data centers" and even ventures into underwater or space-based facilities. The future of AI infrastructure financing is poised to be as innovative as the technologies it supports.