$2 trillion in new revenue needed to meet AI demand globally by 2030: Report
A Bain & Company report warns that meeting global AI compute demand by 2030 will require $2 trillion in new revenue, with power and funding shortages threatening technology adoption worldwide.
New Delhi: At least $2 trillion in annual revenue will be required to fund the computing power needed to meet anticipated global AI demand by 2030, a new report revealed on Tuesday.
According to research by Bain & Company, even with AI-related savings, the world will still be short by $800 billion to keep pace with demand.
The report estimated that by 2030, global incremental AI compute requirements could reach 200 gigawatts, with the US accounting for half of the total power.
Even if US companies shifted all on-premise IT budgets to cloud and reinvested savings from applying AI in sales, marketing, customer support, and R&D into capital spending on new data centres, the funding would still fall short. This is because AI’s compute demand is growing at more than twice the rate of Moore’s Law, Bain noted.
“By 2030, technology executives will be faced with the challenge of deploying about $500 billion in capital expenditures and finding about $2 trillion in new revenue to profitably meet demand. Meanwhile, because AI compute demand is outpacing semiconductor efficiency, the trends call for dramatic increases in power supply on grids that have not added capacity for decades,” said David Crawford, chairman of Bain’s Global Technology Practice.
He added that the arms race dynamic between nations and leading providers makes the potential for overbuild and under-build harder to manage, requiring careful navigation of innovation, infrastructure, shortages, and algorithmic gains.
The report noted that while computational demand rises, leading companies have moved from piloting AI capabilities to profiting from them, delivering 10–25 per cent EBITDA gains over the last two years.
However, most organisations remain in the experimentation stage and are satisfied with modest productivity gains.
Bain also found that tariffs, export controls, and governments’ push for sovereign AI are accelerating the fragmentation of global technology supply chains.
“Cutting-edge domains such as AI are no longer just catalysts for economic growth but are conduits for countries’ political power and national security. Sovereign AI capabilities are increasingly seen as a strategic advantage on par with economic and military strength,” said Anne Hoecker, head of Bain’s Global Technology Practice.