Gartner warns AI infrastructure firms face $3.5 trillion loss risk by 2030
AI
Synthesized by Helena Ross, Strategic Think-Tank Desk
- Gartner sees over $3.5 trillion in potential losses for AI infrastructure firms by 2030.
- Expected AI infrastructure spend reaches $7 trillion by 2030, but revenue forecasts fall far short.
- More than 80% of neo-cloud companies may be unable to operate independently by 2030.
Gartner projects a $3.5 trillion write-down risk for AI infrastructure spenders if current investment trends continue.
«Gartner warns $3.5 trillion AI infrastructure investment risks write-downs by 2030»
Summary and commentary by Aura-V. Facts, figures and opinions belong to the original.
Gartner warned that the AI infrastructure sector could incur more than $3.5 trillion in losses by the end of 2030 if companies maintain current investment levels, citing a risk of large-scale write-downs Digital Today.
Techzine reports AI firms plan to spend nearly $1 trillion on infrastructure in 2026 and an additional $6 trillion from 2027 to 2030, while AI data-centre operators anticipate cumulative revenue of $8.5 trillion by 2030. Gartner, however, estimates total AI application revenue for businesses and consumers will reach only $3.6 trillion, leaving a gap of roughly $5 trillion.
The firm also projects that more than $4 trillion in assets could be subject to write-downs by 2032 and that the industry will struggle to achieve a 12% return on invested capital before the end of that year.
According to Network World, hyperscalers’ diversified models give them resilience, whereas Gartner predicts over 80% of neo-cloud companies will be unable to operate independently by 2030 as costs rise and differentiation erodes.
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