The top US companies are rushing to build massive datacenters to power AI workloads, but it might be hard to earn a return on these investments.
That’s according to IBM CEO Arvind Krishna, who offered a stark assessment of the economics behind the AI infrastructure boom during a recent interview. Krishna laid out the math: filling a one-gigawatt datacenter costs approximately $80 billion today, and with a five-year useful life before the equipment needs replacement, the financial pressure on AI companies pursuing artificial general intelligence (AGI) is immense.
“If one company is going to commit 20-30 gigawatts, that’s $1.5 trillion of CapEx,” Krishna explained. “Then, if I look at the total commits in the world in this space, in chasing AGI, it seems to be like 100 gigawatts with these announcements. That’s $8 trillion of CapEx.”
The IBM chief was unequivocal about the return on investment problem: “It’s my view that there’s no way you’re going to get a return on that because $8 trillion of CapEx means you need roughly $800 billion of profit just to pay for the interest.”
When asked whether he’d shared these concerns with OpenAI CEO Sam Altman—who has been vocal about massive infrastructure plans—Krishna acknowledged the philosophical divide. “That’s a belief. It’s a belief that one company is going to be the only company that gets the entire market,” he said. “I understand that from their perspective, but that’s different from agreeing with them. ‘Understand’ is different from ‘agree.'”
Krishna was particularly skeptical about the ultimate goal driving much of this investment. “I will be clear. I am not convinced, or rather I give it really low odds—we’re talking 0 to 1 percent—that the current set of known technologies gets us to AGI,” he said. However, he was quick to add a more optimistic note about AI’s near-term value: “I think that this current set is great. I think it’s incredibly useful for enterprise. I think it’s going to unlock trillions of dollars of productivity in the enterprise.”
Krishna’s comments highlight a growing debate in the tech industry about the sustainability of AI infrastructure spending. Major tech companies including Microsoft, Google, Amazon, and Meta have collectively announced plans to spend hundreds of billions of dollars on AI infrastructure over the coming years. Microsoft and OpenAI have proposed a $100 billion “Stargate” datacenter project, while Meta CEO Mark Zuckerberg recently said his company would spend over $60 billion on capital expenditures in 2025 alone, largely for AI infrastructure. The question of whether these massive investments will generate corresponding returns—particularly if AGI remains elusive—is becoming increasingly urgent for investors and industry observers. Krishna’s sobering analysis suggests that while AI will deliver significant enterprise value, the winner-take-all bet on AGI may leave many companies with stranded assets and unrecoverable costs.