Neocloud stocks suffered sharp declines after Gartner predicted that 80% of companies in the sector would cease to exist by 2030.
Companies including CoreWeave (CRWV), Nebius Group (NBIS), IREN (IREN), and Hut 8 (HUT) were among those hit hardest by the research firm’s grim forecast.
Data center real estate operators such as Applied Digital (APLD) also fell following the release of Gartner’s findings.
The warning comes despite Gartner having predicted in June that neocloud providers would capture 20% of the AI cloud market by 2030, a significant slice of a growing industry.
Gartner projected that market would expand to $267 billion, with traditional cloud computing providers struggling to match the pace of neocloud growth.
However, Gartner now argues that a widening gap between infrastructure investment and actual AI revenue will lead to massive write-offs across the AI data center space.
Senior director analyst Will Sommer stated that AI data center owners would need to generate a combined $8.5 trillion in revenue to achieve a 12% return on invested capital, covering capital expenditures and financing costs.
The problem is that Gartner currently projects cumulative AI revenue to reach only $3.6 trillion by 2030, leaving a staggering shortfall against what investors and operators have committed to spending.
Unlike hyperscalers, which have large core businesses generating substantial operating cash flow, neoclouds depend almost entirely on immediate returns from their infrastructure investments to survive.
That structural disadvantage makes the neocloud sector particularly vulnerable to any slowdown in AI spending or delays in enterprise adoption of AI-driven cloud services.
Neoclouds have financed much of their build-out with debt, relying on mechanisms such as GPU-collateralized special purpose vehicle structures, customer prepayments, and vendor financing to fund operations.
Even with these creative financing tools in place, neocloud companies still carry heavy debt service burdens on top of rapidly depreciating assets, with GPUs carrying economic useful lives of around six years.
The combination of high leverage, fast-depreciating hardware, and a projected AI revenue gap paints a challenging picture for investors considering exposure to the sector in 2026 and beyond.
Whether the current stock declines represent a buying opportunity or an early warning sign remains a central question for investors weighing risk against the long-term growth potential of AI infrastructure.
