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In September 2024, Goldman Sachs stock researcher Jim Covello warned that AI investment could end badly if companies build costly infrastructure faster than useful applications and financial returns emerge. That was a warning about the economics of AI spending—not proof that a market bubble was about to burst, or a prediction of when one might.
What did the Goldman Sachs researcher warn?
In a September 25, 2024, report, Futurism attributed the following argument to Jim Covello, identified in the story as a senior Goldman Sachs stock researcher: AI technology might not yet be useful enough to justify its high cost, while investment in infrastructure could exceed what businesses and customers need. The report quoted Covello saying, “Despite its expensive price tag, the technology is nowhere near where it needs to be in order to be useful,” and, “Overbuilding things the world doesn’t have use for, or is not ready for, typically ends badly.” Read the September 2024 report.
Those are Covello’s reported views, not a finding that an AI bubble exists. “Explode” was headline language, not a verified forecast of a crash or its timing.
Does heavy AI spending mean there is a bubble?
Not by itself. Spending can signal strong expected demand, but it does not establish that customers will get enough value to cover the cost, or that companies building AI infrastructure will keep earning today’s profits. A bubble question is ultimately about the gap, if any, between what investors pay for future earnings and what businesses can sustainably deliver.
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- Spending and earnings: Are large investments translating into durable revenue and profits, or is spending growing faster than returns?
- Costs and customer value: Do businesses and consumers gain enough productivity or other measurable value to justify the expense?
- Supplier profits and future demand: Are infrastructure providers earning from the current investment boom, and will customers keep buying at the same pace?
- Valuations and demonstrated returns: Do share prices depend on earnings that have already emerged, or on optimistic assumptions about future growth and its longevity?
How large is the investment boom?
Goldman Sachs Research forecast that global AI investment would exceed $1 trillion in 2026. That is a forecast, not a final tally of money spent. The firm also modeled AI investment as a share of GDP; the figures below are estimates, not measured outcomes.
| Measure | 2026 | 2027 | 2028 |
|---|---|---|---|
| U.S. AI investment as a share of GDP | 1.8% | 2.5% | 2.8% |
| Global AI investment as a share of GDP | 0.9% | 1.3% | 1.4% |
These are Goldman Sachs Research’s 2026 modeled estimates. The firm says they depend on estimation assumptions and flags possible capital-expenditure double counting for some companies, so they should not be read as exact realized investment totals. Goldman Sachs Research’s AI investment estimates.
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What has changed since the 2024 warning?
The debate has continued, rather than being settled. Goldman Sachs revisited concerns about a possible AI bubble in October 2025. In June 2026, Covello discussed whether the investment boom had begun to produce returns and said AI economics looked more questionable than they had two years earlier. These later discussions keep the question open; they do not establish that a crash is imminent. Goldman Sachs on renewed bubble concerns and Goldman Sachs’s 2026 discussion with Covello.
What is the counterargument to the bubble warning?
Goldman Sachs’s 2026 valuation analysis notes that AI-related investment is already generating profits that support some stock prices. That is a meaningful counterpoint to the view that spending has produced no economic benefit. The open issue is whether those profits will last: current earnings can support valuations while still proving temporary if customers reduce spending or the investment boom slows. Goldman Sachs’s 2026 valuation analysis.
For investors, the distinction matters. Infrastructure companies may benefit from current demand even while the long-term returns on AI adoption remain uncertain. The key question is not simply whether spending is high, but whether the earnings and customer value it produces endure long enough to justify the capital committed.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How should investors read the “about to explode” headline?
Read it as a dramatic framing of a risk argument made in 2024, not as evidence of an imminent market break. The later Goldman Sachs material shows persistent debate: investment is large, returns and productivity remain under scrutiny, and some profits already flow from the boom. None of those facts alone resolves whether AI stocks are overvalued or whether investment will pay off across the industry.
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