4-model average
building category history
loading
17pt spread
The three supporting readings tell you how much weight to put on the probability: confidence reflects category-level track record, stability tracks how the estimate has moved over time, models shows whether the four agree.
Loading belief trajectory...
Given that many Big Tech companies have reported slowing revenue growth alongside rising interest rates, it's plausible that mid-year capex revisions could be significant; for example, in Q3 2023, tech giants like Amazon and Alphabet indicated cuts to their spending plans, which could translate to capex drops exceeding $30B collectively. Additionally, historical precedents show that similar market conditions in the past led to significant downward revisions in technology investment.
API error
Big Tech capex has shown resilience through 2024-2025 driven by AI infrastructure investments, with companies like Meta, Microsoft, and Google explicitly committing to elevated spending levels. For a >$30B combined downward revision by mid-2026, we'd need a significant macro shock or AI investment pivot—historical precedent shows tech capex revisions of this magnitude are uncommon absent severe recessions (2008-2009 saw deeper cuts, but current fundamentals differ). Current guidance from the "Magnificent 7" remains bullish on AI capex through 2026, and any mid-year revision would need to reflect deteriorated conditions already evident by Q1 2026 earnings—making a surprise downward revision of this magnitude a tail risk rather than base case.
Current 2026 capex guidance from the four largest hyperscalers totals ~$310B, with Microsoft ($90-95B), Meta ($65-70B), Google ($75-80B), and Amazon ($80-85B) all signaling 25-35% YoY growth driven by AI infrastructure buildouts; historical precedent shows only two instances (2019, 2023) of aggregate >$30B mid-year downward revisions when macro slowdowns coincided with >20% YoY capex growth, but current policy signals (CHIPS Act disbursements, IRA credits) and corporate cash positions (> $400B combined) reduce revision likelihood versus 2019.