TL;DR · 30-second read
The Short Version
The biggest technology companies are expected to spend about $5.3 trillion on artificial intelligence and the huge computer buildings behind it by 2030. That forecast jumped by $800 billion after just one round of quarterly results.
Goldman Sachs says a practical problem is coming: big lenders can only hold so much debt from the same few companies. So more of the money is likely to come from private investment funds.
Why it matters: who pays for the AI boom, and at what price, could shape how fast it gets built.
Goldman Sachs Research said on June 12, 2026 that private markets are likely to play a growing role in financing data centers, as hyperscalers (the largest technology companies leading the AI buildout) are expected to make a combined $5.3 trillion in capital expenditures from 2025 through 2030. That estimate stood at $4.5 trillion before first-quarter earnings reports.
Private infrastructure funds raised a record $221 billion in 2025 and could exceed $3 trillion in assets under management by 2030, according to the analysis by Amanda Lynam, the firm’s chief credit strategist in Goldman Sachs Research.
Executive Summary
The central argument concerns the capacity of public debt markets more than the appetite for AI. Hyperscalers already account for a large share of new corporate borrowing. As the same few issuers sell ever-larger amounts of debt, they gain weight in widely tracked bond indices and can run into the limits investors set on exposure to any one company.
Lynam expects those constraints to become “somewhat more binding in coming years,” while acknowledging that their magnitude is “still heavily debated.” At a minimum, she argues, they will affect decisions about exposure and pricing. Private infrastructure and real estate funds, which together held about $1 trillion in uninvested capital, are the natural complement.
The forecast also carries its own caution: hyperscaler capex estimates are growing meaningfully faster than actual data center construction. The size and timing of long-term financing needs therefore remain open, even as the direction of travel toward a broader capital base looks clear.
Why Bond Buyers’ Limits Will Matter
A corporate bond index is a benchmark many investors track. When a handful of companies issue large amounts of debt, their weight in that benchmark rises, and portfolios tracking it can end up holding more of those names than their managers may want. Some investors also operate under formal concentration limits, which cap exposure to a single borrower. Once those limits come into play, a borrower may still find buyers, but the pool of willing buyers can narrow and the price of the debt can change.
The numbers explain why this has moved up the agenda. Goldman’s estimate of hyperscaler capital spending from 2025 through 2030 rose from $4.5 trillion to $5.3 trillion around a single earnings season, an increase of $800 billion. Lynam’s team has already noted borrowers tapping investment-grade debt and private asset markets, across a variety of structures and currencies. That diversification is consistent with companies widening their funding base before any single market becomes a constraint.
The claim has limits. The $5.3 trillion figure measures spending, not borrowing, so it does not by itself show how much must be raised externally. Goldman also stops short of predicting a hard ceiling, describing constraints that affect “nuanced decisions around exposure and pricing” at the very least. The practical takeaway for hyperscaler treasurers and bond investors is a likely negotiation over terms, not a sudden shortage of credit.
Private Capital Is Large, but It Is Not All for Data Centers
Private infrastructure funds held just over $1.7 trillion in assets as of September 2025, including almost $400 billion in dry powder, meaning capital committed by investors but not yet deployed. Private real estate funds held $2.1 trillion, including $600 billion of dry powder. Combined, that uninvested capital comes to about $1 trillion, or less than a fifth of the projected $5.3 trillion in spending.
Even that comparison flatters the available capacity, because neither pool is reserved for AI. Infrastructure funds also invest in energy security and other themes, and real estate funds have their own wider mandates. The projected rise above $3 trillion in infrastructure assets is also conditional: it assumes growth returns close to the 16% to 17% annual pace seen for much of 2012 to 2021, up from roughly 11.5% a year from 2021 to 2024.
The more defensible reading is that private markets can complement public debt markets rather than replace them. Fundraising data support the momentum: as of May 2026, 695 infrastructure funds were seeking an aggregate $555 billion, about two and a half times 2025’s record total. Those are targets rather than closed commitments, however, and fundraising has been concentrated among experienced managers, which suggests the benefits may not be evenly shared.
A Capital Stack Split by Asset
A capital stack is the mix of debt and equity that pays for a project. In data centers, Goldman’s analysis points to a stack that crosses traditional categories because land, operational networks, power, buildings, and equipment touch different asset classifications. Digital infrastructure funds have increasingly been classed as infrastructure rather than real estate over the past decade, and the line between the two fund types continues to blur.
Lynam argues that combined long-term financing capacity matters more than category names. For developers and operators, that suggests a wider set of potential capital partners. For allocators, it raises a practical question: an investor holding both infrastructure and real estate funds could accumulate more data center exposure than either label implies.
Investor demand has its own logic. Institutions cite diversification, income, and inflation protection as top reasons for allocating to infrastructure, and the category returned 12.8% last year, behind only private equity and venture capital among private market categories. Largest-fund fundraising periods have also shortened, from 13 to 18 months on average in 2018 to 2021 to 7 to 12 months from 2022 through the third quarter of 2025.
Estimates Are Moving Faster Than Concrete
The most useful caution sits near the end of the analysis. “For now, the growth in hyperscaler capex estimates is meaningfully outpacing the growth in actual data center construction,” Lynam writes, adding that the metric “warrants close monitoring for an estimate on the long-term financing needs.”
Private data center construction has accelerated, and a significant backlog of projects has not yet entered construction. For lenders and fund managers, that gap affects timing. Capital raised against a forecast still has to find projects that are ready to build, while a backlog that converts quickly could bring financing needs forward. Construction starts may therefore be a more grounded signal of real funding demand than the headline capex estimate.
Background
Data centers are the specialized buildings that house the servers, networking gear, and power and cooling systems behind cloud services and AI. Financing them has become more complex as their scale has grown, because a single campus can involve land, buildings, power, networks, and equipment, each of which may appeal to different kinds of investors.
Private infrastructure funds pool money from institutional investors to buy and finance long-lived assets. The market grew roughly 11.5% a year from 2021 to 2024, after annual growth of about 16% to 17% for much of 2012 to 2021, based on Preqin data. Over the past decade, digital infrastructure funds have increasingly been categorized as infrastructure rather than real estate. Source: Private Markets Are Expected to Have a Growing Role in Data Center Financing, Goldman Sachs Research’s analysis of private capital’s role in the AI and data center buildout.Sources