Goldman CEO: AI Deal Demand Robust as $15T Spending Looms

Wall Street's largest investment banks are positioning themselves at the center of what could become the largest infrastructure buildout in modern history. Speaking at the Hong Kong Monetary Authority's Global Financial Leaders' Investment Summit on November 3, 2026, executives from Goldman Sachs and Morgan Stanley outlined a vision of sustained, multi-trillion-dollar capital deployment into artificial intelligence infrastructure over the coming decade.

$15 Trillion Over Ten Years

Morgan Stanley CEO Ted Pick delivered the headline projection: cumulative AI infrastructure spending could reach $15 trillion over the next decade. He estimated that the largest technology hyperscalers, including companies like Meta Platforms and major cloud providers, could deploy between $800 billion and $1 trillion annually over a seven to twelve year horizon.

"We're somewhere in the second inning of a nine-inning game," Pick said. "Ten to fifteen trillion, that's a very large range, but that's not an unreasonable sum to be thinking about to build that, which will push the product forward."

Capital Markets Ready to Finance

Goldman Sachs CEO David Solomon confirmed that capital markets remain highly receptive to AI-related financing opportunities. Wall Street firms are already capitalizing on a wave of AI-driven advisory and financing mandates, structuring debt and equity transactions for market leaders including Meta Platforms Inc. and Anthropic PBC.

Solomon emphasized that the primary constraint on deal size is the cost of capital rather than its availability. "There will be robust financing to meet the demand," he stated. However, Solomon injected a note of caution, warning that technological supercycles rarely advance in a straight line and investors should prepare for volatility.

Availability and Timeline

Officially launched on November 3, 2026, these projections represent Wall Street's most comprehensive public assessment of AI infrastructure financing to date. The statements come as investment banks compete to capture advisory fees and underwriting mandates from technology companies racing to build out data center capacity, custom silicon, and energy infrastructure.

Productivity Gains and Economic Impact

Beyond the immediate financing opportunity, Pick outlined the long-term economic rationale for the investment wave. He projected that returns on AI infrastructure spending will prove durable, with productivity gains potentially lifting real US gross domestic product by 50 to 70 basis points annually. This would represent a significant boost to economic growth rates over an extended period.

• Hyperscalers could deploy $800 billion to $1 trillion annually
• Spending horizon extends seven to twelve years
• Real GDP could gain 50 to 70 basis points annually from AI productivity
• Investment banks structuring deals for Meta, Anthropic, and other leaders

Governance and Accountability

Addressing concerns about AI governance, Solomon drew on Goldman's two decades of experience operating automated trading platforms. He emphasized that accountability must ultimately reside with individuals rather than systems, regardless of how sophisticated the technology becomes.

"The people that make the technology need to take responsibility for what they are doing, and the people that deploy it have to take responsibility for how it is deployed," Solomon said. This framing positions human judgment and oversight as the critical control mechanism even as AI systems become more autonomous.

What This Means

Wall Street's most powerful financial institutions are betting that AI infrastructure represents a generational investment opportunity. With capital markets signaling readiness to finance the buildout and productivity gains justifying the economics, the stage is set for sustained deployment. However, Solomon's caution about non-linear progress suggests investors should prepare for periods of reassessment and volatility even within a broader upward trend. The nine-inning game has eight innings left to play.