The AI industry must generate $6 trillion in annual revenue by 2031 to justify surging capital investment in data centre infrastructure. New product development, including innovations in search, advertising and physical AI, is projected to contribute $4.2 trillion — the largest revenue segment. Annual AI infrastructure spending could reach $1.5 trillion by 2031, covering new facilities, GPU upgrades, memory and networking equipment. Data centre sizes and costs are doubling roughly every 12 to 16 months, with Meta's Ohio facility projected to cost $200 billion by 2030. "The economics of AI infrastructure demand trillions in new revenue beyond productivity gains," said David Crawford, Bain's global technology practice chairman and lead report author.
The artificial intelligence：https://www.thenationalnews.com/opinion/comment/2026/09/27/ai-technology-regulation/ industry needs to become creative with new propositions to earn $6 trillion in annual revenue by 2031 and justify the capital being deployed for data centres, a new report from Bain and Company has shown.
Revenue from new product development is projected to become the biggest contributor to the industry, estimated to generate about $4.2 trillion to fund the booming technology's global market：https://www.thenationalnews.com/future/space/2026/09/25/google-data-center-space-launch-ai/ within the next half-decade, the US consultancy said in its latest technology report series on Tuesday.
That segment would include innovations in search, advertising, autonomy and physical AI, analysts at Boston-based Bain said.
Enterprise productivity would require $1 trillion to $1.4 trillion in revenue in order to support gains in areas such as software development, sales, marketing, customer service and IT operations, they said.
Absorption speed, defined as the pace at which companies can put AI to work, has become the “new competitive variable”, according to Bain, leading AI labs are investing upwards of $9.75 billion in engineering models to help companies assimilate faster, it said.
“The debate today is fixated on employee productivity. The economics of AI infrastructure demand trillions in new revenue beyond productivity gains. What the industry needs is a wave of innovation that will dwarf what mobile and cloud unlocked,” said David Crawford, chairman of Bain’s global technology practice and lead author of the report.
Consumer-focused services, which includes subscriptions and advertising revenue, is seen to contribute $200 billion to $400 billion. This particular segment is widely acknowledged to be crucial for the industry as service providers continue to push AI-powered products to billions of users globally.
“New products and uses that don’t exist today will enable new markets and opportunities from abundant intelligence – these may include drug discovery, mental health and energy generation,” Bain said.
Bain forecasts that annual spending on AI infrastructure might hit $1.5 trillion by 2031. Those expenses include new facilities, higher capacity and upgrades to the installed base of GPUs, memory and networking equipment.
If those capital expenditures amount to about a quarter of industry revenue – “an ambitious but reasonable percentage based on trends among cloud providers” – sustaining this level of investment would require an AI market approaching $6 trillion annually, Bain said.
“The unprecedented speed and scale of the AI buildout, with billions flowing into chips, data centres, networks and power systems, have focused attention on the challenge of building capacity,” the report said.
“But the more important question may be whether enough economic value can be created to justify it.”
The size and cost of AI data centres is consistently accelerating, doubling approximately every 12 to 16 months, Bain said. For instance, the Prometheus data centre of Facebook parent Meta Platforms in Ohio currently had a capacity of 600MW at an estimated cost of $24 billion in 2025; that is projected to jump to as much as 2GW and $80 billion by 2027, data from research firm Epoch AI.
By 2029, capacity at Prometheus is expected to jump to 5GW, at a cost of up to $175 billion, and by 2030, it would balloon to 9GW at $200 billion, San Francisco-based Epoch AI said.
Data centres would also need to address a number of challenges as more of them are built. These include adding grid capacity to power them, securing GPUs and other infrastructure components, a skilled workforce and retaining them “far above historical rates”, and issues on public opinion and regulations, such as pushback on resource use and noise pollution.
On the other hand, several governments are supporting the growth of the AI and data centres industries, including those in the UAE, Saudi Arabia, the EU, South Korea and the US, Bain said, noting that data centres are now central to technology innovation, economic growth and national sovereignty.
“Capital needs for data infrastructure will remain high … bottlenecks in power, semiconductors, and other inputs carry large capital needs of their own, opening additional entry points for investors,” Bain said.
“And as sovereign infrastructure becomes a bigger part of national strategies, partnerships offer both a way in and geographic diversification.”
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