Following recent reports on the capital spending of companies like Google, Microsoft, Meta Platforms, and Amazon — which in 2025 poured hundreds of billions of dollars into AI infrastructure, often with promises of transformative returns — critics caution that valuations may be drifting away from economic fundamentals. In his sharp critique, IBM CEO Arvind Krishna targeted both those numbers and the underlying logic behind the industry-wide race to build massive data centers.
According to his “back-of-the-napkin math,” constructing and launching a 1-gigawatt data center now costs roughly $80 billion. This means that the ambitious plans of major tech players — which aim for 20–30 gigawatts — translate into investments of about $1.5 trillion. Under the most aggressive visions, which assume 100 gigawatts, the total cost could reach $8 trillion.
What’s more, the hardware powering these facilities — primarily GPU accelerators and servers — becomes obsolete quickly. Krishna notes that after roughly five years, much of the equipment must be replaced. This means the investment isn’t a one-off expense — companies would need to reinvest cyclically just to maintain their capacity.
As a result, according to the IBM chief, given today’s costs and assuming the AI industry does not deliver fundamental breakthroughs, the probability of generating profits from this scale of expenditure is extremely low. He also cast doubt on optimistic forecasts about achieving artificial general intelligence (AGI), estimating the likelihood of reaching AGI with current technologies at only 0–1%.
At the same time, Krishna clarified that he is not dismissing the usefulness of current AI tools — he believes they can deliver significant productivity gains in the enterprise sector. However, he argued that for AGI or other deep breakthroughs to become feasible, the world will need “completely different technologies” from those driving today’s AI boom.
It appears that tech giants are increasingly splitting into two camps: enthusiastic believers in massive AI investment and those who warn of overreach. On one hand, AI clearly generates meaningful value today; on the other, there’s a growing sense that the sector may be inflating a bubble — one that could burst at the worst possible moment.