JP Morgan says Q2 AI company revenues beat expectations and the economic sustainability of the AI capex cycle has improved versus six months ago. Its internal credit research projects $5.5 tln of AI-related capex in 2026–2030; external estimates reach up to $10 tln. At the midpoint (~$7.5 tln), JP Morgan models combined revenue for AI cloud, model providers and new neocloud services at $1.6 tln by end-2026; with 10–20% annual growth thereafter, 2030 revenue would be $2.5–3.0 tln. Demand is conce

JP Morgan says Q2 AI company revenues beat expectations and the economic sustainability of the AI capex cycle has improved versus six months ago. Its internal credit research projects $5.5 tln of AI-related capex in 2026–2030; external estimates reach up to $10 tln. At the midpoint (~$7.5 tln), JP Morgan models combined revenue for AI cloud, model providers and new neocloud services at $1.6 tln by end-2026; with 10–20% annual growth thereafter, 2030 revenue would be $2.5–3.0 tln. Demand is concentrated in enterprises: large firms’ AI spend as a share of total opex+capex is expected to rise from 4.5% over the past 12 months to 5.8% over the next 12 months — against roughly $30 tln of global large-enterprise opex+capex this implies about $1.7 tln of AI spend. JP Morgan says the bearish claim that AI infrastructure far exceeds monetization capacity has weakened, but margins, depreciation, utilization, pricing power and intra-supply-chain returns still require validation. (JP Morgan report, Aug. 20)