The Sequoia Capital partner said the industry would need $3 trillion in revenue to justify that level of investment, arguing a large revenue gap remains among leading AI companies.
Sequoia Capital partner David Cahn estimated global AI infrastructure investment will reach $1.5 trillion in 2026 and said the sector would need $3 trillion in revenue to cover those costs. He argued that a sizable revenue gap still separates current business performance from the level needed to support that spending, citing Anthropic ARR (annual recurring revenue) of $60 billion and mentioning OpenAI as part of the competitive landscape. The figures underscore a broader debate over whether rapid spending on AI computing capacity, chips, data centers and related infrastructure is running ahead of proven demand.