Morgan Stanley Tops Goldman in AI Debt Underwriting

Morgan Stanley has overtaken Goldman Sachs as the leading Wall Street bank for artificial intelligence-related debt deals. The firm and JPMorgan are arranging roughly $13 billion to finance a Meta Platforms data center in El Paso, Texas, as Morgan Stanley projects global AI-related debt issuance near $570 billion for 2026.

Banks and technology companies are using borrowed capital to fund gigawatt-scale data centers instead of relying only on cash. Lenders are assembling financing packages that combine leveraged loans, investment-grade bonds and structured credit to spread costs and preserve corporate liquidity for other investments.

Morgan Stanley Chief Executive Ted Pick has said data center capital expenditure for 2026, which was forecast at $575 billion in November 2025, is now running near $850 billion. That upward revision has increased demand for large, syndicated financing packages and prompted banks to expand their debt underwriting teams.

Morgan Stanley has been active in other AI infrastructure deals. The bank provided up to $1 billion in financing to miner-turned-AI-infrastructure company Core Scientific to support data center growth. JPMorgan later increased that facility by $500 million. Core Scientific’s assets were acquired in an all-stock transaction valued at about $9 billion by CoreWeave, with the merged company planning roughly $5.5 billion in data center development across six centers by the first half of 2027. Morgan Stanley co-led a $2.6 billion facility for CoreWeave alongside Goldman Sachs on a separate package.

Analysts and banks tracking the financing wave identify Morgan Stanley, Goldman Sachs and JPMorgan among the main beneficiaries. Bank of America reports it has helped raise nearly $500 billion for AI-related companies since 2025. Some bond investors have pushed back as issuance climbs, and coverage ratios on hyperscaler bonds have declined, prompting signs that investors may require higher yields to offset risk. Goldman Sachs Chief Executive David Solomon described the period as the middle of an “AI capex super cycle,” noting broad use of loans, debt and equity to meet demand.

Banks arranging large AI financings earn underwriting fees and deepen client ties while taking on direct credit exposure to infrastructure spending. Lenders continue to compete for mandates tied to data center build-outs and sector listings as companies scale AI infrastructure.