Bain & Company has warned that the artificial intelligence industry may need to generate nearly $6 trillion in annual revenue by 2031 to justify the unprecedented buildout of chips, data centres, networks and power systems. The consultancy estimates that annual AI infrastructure spending could reach $1.5 trillion by 2031, while capital expenditure by Microsoft, Google, Amazon, Meta and Oracle could collectively hit $780 billion in 2026—almost five times their combined level three years earlier.
Bain assumes capital expenditure will represent roughly 25% of industry revenue. Under that framework, even the upper end of current revenue projections leaves a major shortfall. Consumer AI products could generate $200 billion to $400 billion annually by 2031, and enterprise adoption could contribute another $1 trillion to $1.4 trillion. That combined range of $1.2 trillion to $1.8 trillion would still leave a gap of about $4.2 trillion relative to the nearly $6 trillion needed, according to Bain.
The report identifies possible new revenue sources, including advertising in chatbot products, autonomous vehicles and industrial automation, physical AI such as digital twins and humanoid robots, and entirely new AI-driven products in drug discovery, materials science and scientific research. Bain says the risk is that “the infrastructure is being built ahead of the demand curve,” and that sustainably funding the expansion could require adding roughly 1% to annual global GDP growth.
Separately, Axios reported that OpenAI’s annualized revenue run rate is nearing $70 billion, up more than 70% since the start of the third quarter, with enterprise sales more than doubling since July. Anthropic’s annualized revenue run rate reached about $65 billion in July, and its full-year 2025 revenue grew twelvefold to nearly $4.6 billion, though its operating loss exceeded $8 billion. Anthropic also disclosed $518 billion in future cloud, computing and infrastructure obligations. Both companies are preparing for potential public listings, which would provide investors with clearer views of AI revenue and spending.
While OpenAI’s top-line momentum is strong, Axios noted that company expense details remain unknown. Bain’s broader warning underscores the challenge: the next phase of the AI boom may depend less on building data centres and more on creating applications that generate enough economic value to pay for them.
