SKN | Goldman Sachs and the AI Capital Cycle: What HNW Families Should Read Beyond the Boom

Key Takeaways:

• Goldman Sachs is increasingly positioned across the AI capital cycle, from investment banking and credit markets to infrastructure financing and private markets.
• Goldman Sachs Research estimates that US hyperscalers could spend roughly $800 billion on AI-related capital expenditure in 2026, while broader global AI investment is expected to exceed $1 trillion.
• The financing structure matters as much as the technology: AI investment is increasingly moving through corporate bonds, private credit and infrastructure funds, creating new layers of leverage and counterparty exposure.
• For HNW families, the strategic issue is not simply exposure to AI growth but understanding where AI-related financing enters the banking, custody and private-markets architecture of the family balance sheet.

Goldman Sachs is becoming an important financial intermediary in the US artificial-intelligence buildout, not because it develops AI models, but because it sits close to the capital required to build them. Its investment-banking, markets, credit and private-markets businesses increasingly connect technology companies with the debt, equity and infrastructure financing required for the next phase of the AI cycle. For HNW families, this makes Goldman’s role worth examining as a window into how the AI boom is migrating from a technology story into a multi-layered financial cycle.

Read AI as a Capital-Allocation Cycle

The scale is already substantial. Goldman Sachs Research estimates that global AI investment could exceed $1 trillion in 2026, while US hyperscalers are expected to spend roughly $800 billion on capital expenditure. US data-center electricity demand alone is forecast by Goldman to more than double from 31 gigawatts in 2025 to 66 gigawatts in 2027.

The implication is important: AI is no longer confined to technology-company balance sheets. It increasingly affects infrastructure, energy, real estate, telecommunications, semiconductors and financial markets.

Watch the Debt Behind the Data Centers

The next phase of the AI boom is increasingly being financed through credit. Goldman estimates that almost $500 billion of AI-related debt had been issued by August 2026, as technology companies and infrastructure developers seek additional funding beyond their existing cash flows.

This changes the risk equation. Equity investors absorb changes in valuation, but lenders face a different question: whether future cash flows will be sufficient to service increasingly large capital commitments. Recent market activity suggests investors are becoming more selective as AI-related borrowing expands.

For HNW clients participating in private credit, infrastructure funds or structured financing, the distinction between AI exposure and AI financing exposure therefore becomes critical.

Goldman’s Role Shows Why Private Markets Matter

Goldman Sachs expects private infrastructure financing to play an increasingly important role as hyperscalers confront the limits of traditional liquid credit markets. Infrastructure funds already held more than $1.7 trillion in assets and approximately $400 billion of available capital as of September 2025, according to Goldman research.

For private-bank clients, this creates a potentially important intersection between technology and alternative assets. A family may have no direct investment in an AI company while still gaining indirect exposure through a private infrastructure fund, data-center financing vehicle or private-credit strategy.

Use Swiss Banking to Separate Exposure From Liquidity

Zurich and Geneva private banks can play an important governance role in this environment. The objective should not be to eliminate exposure to the AI capital cycle, but to prevent illiquid or highly correlated positions from becoming entangled with the family’s core liquidity.

Strategic custody, emergency liquidity and Lombard financing should be assessed separately from allocations to private credit, infrastructure and other long-duration assets. A portfolio that appears diversified by investment label can still carry substantial concentration if multiple holdings ultimately depend on the same AI infrastructure spending cycle.

Stress-Test the AI Financing Chain, Not Just the Equity Market

HNW families should examine the full chain: technology companies, data centers, power infrastructure, lenders, private funds and banks providing financing or custody. The key questions are where leverage sits, who bears construction and refinancing risk, what collateral supports the exposure and how quickly liquidity can actually be realised.

The deeper lesson is that Goldman Sachs’ growing role in AI finance illustrates the maturity of the AI boom. It is becoming a financial infrastructure story as much as a technology story. For globally mobile families, preserving flexibility means understanding that exposure can enter the balance sheet indirectly — through credit, infrastructure and private markets — even when there is no obvious AI stock allocation.

For a confidential discussion regarding your private-markets exposure, Swiss banking structure, liquidity reserves and counterparty diversification, contact our senior advisory team.