AI datacenter capex will far exceed forecast revenue through 2030
Investors are pouring more into AI data center infrastructure than they can hope to recoup by 2030, according to Gartner. “Enterprise and consumer AI revenue will be insufficient to support profitable returns on all planned AI capital expenditures during this period,” said Gartner Senior Director Analyst Will Sommer. AI data center owners would need to generate $8.5 trillion in revenue through…
Investors are funneling vast sums into AI data center infrastructure, but the returns may not materialize by 2030, according to Gartner. Analyst Will Sommer warned that enterprise and consumer AI revenue will fall short of supporting profitable returns on all planned capital expenditures during this period. To cover the $8.5 trillion in announced spending, AI data center owners would need to generate $3.6 trillion in revenue from enterprise and consumer AI.
However, analysts from Bain & Company predict that annual AI infrastructure spending could surge to $1.5 trillion by 2031, with the AI services market needing to exceed $6 trillion annually to cover the costs. This alarming forecast is particularly concerning for neocloud providers, as Gartner suggests that over 80% of them may cease independent operations due to the financial pressures.
While the hyperscalers may be large enough to absorb the financial strain, these cost pressures could force a significant portion of neocloud providers to wind down their operations. Both Bain and Gartner surveys paint a bleak picture of AI infrastructure investment, highlighting that a considerable amount of it will likely fail to generate a return and necessitate financial losses for companies.
Written by urgent.news from Computerworld's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
