Goldman Sachs has forecast a 7 percentage point drop in Big Tech return on equity, directly attributing the decline to AI capital expenditure that has not yet produced measurable returns.1
The bank released this projection alongside its AI spending and profitability analysis — an explicit institutional signal that spending and return compression are connected.1
Big Tech companies across the United States have collectively committed hundreds of billions to AI infrastructure: data centers, custom silicon, and large-scale model development. Similar buildouts are accelerating in Asia and Europe. Goldman's analysis frames these outlays as front-loaded costs, not yet matched by revenue.1
Institutional investors globally are now weighing near-term derating of AI infrastructure stocks.1 Premium valuations built on AI growth narratives are difficult to sustain when a major bank attaches a specific number — 7 percentage points — to the drag on equity returns.
The pattern has precedent across markets. Broadband expansion in the late 1990s and cloud infrastructure in the 2010s both preceded returns by years. AI investment cycles are more compressed. Scrutiny is higher. The gap between capital deployment and output is now a focus for investors from Tokyo to Frankfurt to New York.
Analyst skepticism about AI return on investment has circulated since 2024.1 Goldman's forecast adds institutional weight to that skepticism — moving it from qualitative concern to a quantified sector-level projection.
Data centers and GPU clusters are depreciating assets. Without measurable output growth, they compress margins quarter by quarter. For companies in any market that have used AI investment to justify premium multiples, the pressure to show revenue is now acute.
Goldman's analysis points toward derating as the near-term outcome: investors pricing in margin compression rather than discounting future AI revenue.1 If that repricing takes hold globally, it marks the transition from the capital deployment phase of the AI cycle to an accountability phase — where spending requires justification in earnings, not roadmaps.
Sources:
1 Goldman Sachs AI Spending ROI Skepticism Report, June 17, 2026
