The AI cloud provider now expects capital expenditure of between $35 billion and $39 billion this year, compared with its previous forecast of $31 billion to $35 billion. The company also raised its 2026 revenue and adjusted operating-profit targets after reporting stronger-than-expected second-quarter results.
CoreWeave's second-quarter revenue more than doubled to $2.58 billion, narrowly exceeding analysts' expectations. Its revenue backlog reached $104.2 billion at the end of the quarter, up from $99.4 billion in the first quarter, while the company secured more than $25 billion in additional customer commitments during the current quarter.
The figures underline a central feature of the current AI investment cycle: demand for computing capacity is increasingly translating into large, multi-year infrastructure commitments.
CoreWeave operates data centres and provides computing capacity to technology companies developing and deploying AI systems. Its relationships with Nvidia, Microsoft, Meta, Anthropic and Caterpillar have positioned it within a supply chain increasingly dependent on advanced processors and high-capacity data centres.
The company's spending plans also demonstrate the capital intensity of the AI infrastructure economy. CoreWeave spent $9.4 billion on capital expenditure during the June quarter, compared with $6.8 billion in the preceding three months.
For investors, the larger question is whether strong demand can continue to justify the rapid expansion in infrastructure spending. A substantial backlog provides visibility, but delivery depends on CoreWeave bringing additional data-centre capacity online and meeting contractual obligations.
The development has implications beyond cloud computing. Demand for AI infrastructure is supporting investment in semiconductors, electricity generation, data-centre construction, cooling systems and network equipment.
The immediate market signal has been positive, with CoreWeave shares rising sharply after the results. But the longer-term test will be whether revenue growth and operating leverage keep pace with the capital required to build the infrastructure behind the AI economy.
