Moody’s Ratings raised its capital spending projections for the six largest US hyperscalers — Microsoft, Amazon, Meta, Alphabet, Oracle, and CoreWeave — to $785 billion for 2026 and near $1 trillion for 2027, an $85 billion upward revision from the agency’s March 2026 forecast. The revision followed a blowout Q1 2026 earnings cycle in which Google Cloud revenue grew 63% year on year, AWS posted its fastest growth in 15 quarters, and Microsoft’s AI revenue surpassed $37 billion at a 123% year-on-year run rate. Combined cloud revenue growth across AWS, Microsoft Azure, and Google Cloud in Q1 2026 was the fastest since Q2 2021, when their combined revenue was one-third of its current level. The upward revision reflects Moody’s assessment that revenue backlog growth, growing enterprise AI adoption, and compute shortages are indicating a multi-year growth trajectory that justifies continued aggressive infrastructure investment rather than the moderation that some analysts had predicted following Q4 2025 investor concerns.
The $85 billion revision is itself a significant data point. Moody’s had already revised its 2026 hyperscaler capex forecast upward multiple times before the Q1 2026 earnings cycle. The agency’s original 2026 forecast was approximately $600 billion, revised to $700 billion in March 2026 and now revised to $785 billion following Q1 results. Each revision reflects the same underlying dynamic: hyperscaler revenue growth and contracted backlog expansion are validating investment at rates that consistently exceed analyst expectations, and the companies are responding by increasing their infrastructure commitments rather than pausing to assess whether existing commitments are generating adequate returns. The three largest hyperscalers added approximately $700 billion in remaining performance obligations over just two quarters, with AI model companies including OpenAI and Anthropic so compute-constrained that they cannot meet existing demand. That contracted revenue backlog is the data that Moody’s is treating as justification for continued capex escalation.
The Credit Risk That Accompanies the Forecast
Moody’s framing of the $785 billion figure is not purely positive. The agency simultaneously raised its capex forecast and flagged that rising capital intensity and higher debt levels could lead to a reassessment of creditworthiness if strong profit growth from AI investments fails to materialise. The credit risk observation is significant coming from a ratings agency whose assessments directly influence borrowing costs for the companies it rates. Hyperscaler capex now approaches or exceeds 100% of operating cash flows for some operators, compared to a 10-year average of approximately 40%, creating debt service obligations that depend on AI revenue growth continuing at or above current rates to sustain investment-grade credit metrics. The $785 billion forecast is therefore a two-sided signal: strong enough near-term revenue validation to justify raising the forecast, and large enough capital commitment relative to cash generation to warrant ongoing monitoring of whether the payback timeline is developing as the investment thesis requires.
What the $1 Trillion 2027 Projection Means
The near-$1 trillion 2027 projection is the figure that most directly captures the trajectory of AI infrastructure investment. If the 2027 projection materialises, the six largest US hyperscalers will collectively spend more on AI infrastructure in a single year than the entire annual GDP of Saudi Arabia. The physical supply chain, grid interconnection, and permitting frameworks that govern data center development were not designed to absorb investment at this pace, and the gap between committed investment and the infrastructure delivery timeline is what our analysis of the AI infrastructure buildout creating a supply chain crisis nobody planned for documented in detail. The Moody’s revision confirms that the investment commitment is accelerating even as the delivery constraints that limit how quickly that investment can be converted into operational capacity are intensifying.
