Investing.com -- JPMorgan believes the acceleration in revenue at artificial intelligence companies has strengthened the economic case behind the sector's enormous infrastructure spending.

"The recent acceleration in AI companies' revenues makes the AI capex cycle look more economically viable than it did six months ago," strategist Nikolaos Panigirtzoglou wrote in a note to clients, adding that faster revenue growth makes the sector's capital intensity look more sustainable, provided revenues eventually translate into durable margins and adequate returns on invested capital.

The bank noted estimates of cumulative AI data center capital expenditure through 2030 vary widely. Its credit research team has projected around $5.5 trillion, while some external estimates run as high as $10 trillion, giving a midpoint of roughly $7.5 trillion.

Against that, JPMorgan's equity analysts see AI cloud providers, model providers and neoclouds generating a combined revenue run-rate of about $1.6 trillion by the end of 2026, growing 10% to 20% annually to reach $2.5 trillion to $3 trillion by 2030.

Much of that demand is likely to come from large enterprises, according to the bank. A JPMorgan survey of Asia Pacific companies found average AI spend rising from 4.5% of expenses plus capex over the past 12 months to 5.8% over the next 12. Applied globally, that implies roughly $1.7 trillion of AI spending.

Reaching $2.5 trillion by 2030 would require that share to climb to around 6.5% to 7.%. “This is a meaningful increase from the expected 5.8% over the next 12 months, but not an implausible one if AI shifts from experimentation to scaled deployment and if enterprises can fund AI budgets through productivity savings, labour substitution, revenue uplift, or reduced spend on legacy technology,” wrote Panigirtzoglou.