The world needs at least $2 trillion annually to fund computing power needed to meet anticipated AI demand by 2030. However, even with AI-related savings, the US and other countries are still $800 billion short of meeting this need. Bain & Company’s latest Global Technology Report found that global incremental AI compute requirements could reach 200 gigawatts by 2030, with the US accounting for half of the power.
The report also highlights the rapid acceleration of agentic AI innovation, with companies investing in building foundational AI capabilities including agent platforms and real-time data access. However, most companies are still stuck in experimentation mode and need to navigate infrastructure, supply shortages, and algorithmic gains.
Meanwhile, quantum computing has the potential to unlock $250 billion in market value across industries such as pharmaceuticals, finance, logistics, and materials science. Humanoid robots also pose opportunities for growth, but commercial success will hinge on ecosystem readiness.
The report warns that technology executives will face a challenge of deploying $500 billion in capital expenditures while finding about $2 trillion in new revenue to profitably meet demand. The potential for overbuild and underbuild is also a concern due to the arms race dynamic between nations and leading providers.
To succeed, multinational firms will need to localize not just compliance but also their technology architecture, making decisions with optionality and prioritizing flexibility where uncertainty rules. The report concludes that global AI standards are unlikely to converge, and individual countries’ goals vary.
Source: https://www.bain.com/about/media-center/press-releases/20252/$2-trillion-in-new-revenue-needed-to-fund-ais-scaling-trend—bain–companys-6th-annual-global-technology-report