New Delhi | September 23,2025 | SKY LINK TIMES
Meeting the skyrocketing global demand for artificial intelligence (AI) could require at least $2 trillion in new annual revenue by 2030, according to a new report by Bain & Company. Despite AI’s ability to boost productivity and generate savings, the research warns of an $800 billion shortfall that could disrupt the industry’s growth trajectory.
Global AI compute demand could hit 200 GW by 2030, requiring $2 trillion in revenue—yet an $800B funding gap remains, Bain & Company warns.
AI Compute Demand Surging Beyond Moore’s Law
The Bain report highlights that incremental global AI compute requirements could reach 200 gigawatts (GW) by 2030, with the United States expected to account for half of that demand. This surge far outpaces the efficiency improvements promised by Moore’s Law, which historically predicted that semiconductor performance would double every two years.
“By 2030, technology executives will be faced with the challenge of deploying about $500 billion in capital expenditures and finding about $2 trillion in new revenue to profitably meet demand,” said David Crawford, Chairman of Bain’s Global Technology Practice.
He added that power supply remains another critical bottleneck: “AI compute demand is outpacing semiconductor efficiency, calling for dramatic increases in power supply on grids that have not added capacity for decades.”
The Funding Gap: $800 Billion Short
Even if U.S. companies were to shift all on-premise IT budgets to cloud solutions and reinvest AI-driven savings from sales, marketing, customer service, and R&D, Bain estimates the funding would still fall short by $800 billion.
This gap raises concerns over whether nations and corporations can keep pace with AI’s exponential growth. The balance between overbuilding and underbuilding infrastructure has never been more complex, with the risk of wasted investments or crippling shortages looming large.
AI: From Experimentation to Profitability
While many firms remain in the “AI experimentation” phase, leading global companies have already scaled AI across key workflows. Over the last two years, these organizations reported 10% to 25% EBITDA (earnings before interest, taxes, depreciation, and amortization) gains, proving AI’s transformative potential.
However, Bain cautions that without robust infrastructure and funding, most companies will struggle to move beyond small-scale pilot projects into fully profitable deployments.
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The Geopolitical Dimension: Rise of Sovereign AI
The report also underscores the geopolitical implications of AI expansion. Tariffs, export controls, and government pushes for sovereign AI are fragmenting global technology supply chains.
Anne Hoecker, Head of Bain’s Global Technology Practice, noted:
“Sovereign AI capabilities are increasingly seen as a strategic advantage on par with economic and military strength.”
This shift highlights AI’s role not just as a driver of economic growth but also as a core component of national security and global power dynamics.
Outlook
As AI moves from promise to profit, the next five years will be crucial in determining whether the world can fund, power, and secure the infrastructure required. Without addressing the looming $800 billion gap, the future of AI could face severe constraints despite its vast potential.
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