Big Tech's $635 billion AI spending faces energy shock test, S&P Global says

• Planned AI infrastructure spending has surged from just $80 billion in 2019 to $635 billion projected for 2026, nearly an 8x increase in seven years
• S&P Global's Melissa Otto warns that if energy prices jump 30% as oil executives predict, it could force tech companies to revise capital expenditures in Q1-Q2, potentially triggering a 'really meaningful correction in all equity markets'
• Data centers require vast amounts of electricity, making AI growth heavily dependent on power prices and infrastructure capacity at a time when supply risks may not be fully reflected in current energy prices

Summary: Big Tech's $635B AI Spending Threatened by Energy Crisis

Key Findings:

S&P Global Visible Alpha warns that Big Tech's massive AI infrastructure investments face significant risks from Middle East conflict-driven energy price surges. Tech giants Microsoft, Amazon, Alphabet, and Meta planned $635 billion in AI-related capital expenditures for 2026, up sharply from $383 billion in the prior year and just $80 billion in 2019.

Main Concerns:

Melissa Otto, S&P Global's head of research, indicates that persistently high energy costs could force tech companies to revise capital spending plans in Q1-Q2, potentially triggering a "really meaningful correction in all equity markets." While no companies have announced cutbacks yet, the threat looms large.

Energy Constraints:

Data centers require vast electricity supplies, making AI infrastructure heavily dependent on power prices and capacity. Oil executives at CERAWeek in Houston warned that supply risks aren't fully reflected in current prices, raising concerns about further increases.

Market Implications:

• AI enthusiasm had driven global stock indexes beyond 2025 highs but has lost momentum since the Middle East crisis
• A 30% jump in energy prices would significantly impact consumers and corporate earnings
• Potential capex reductions could serve as a catalyst for broader equity market corrections
• Questions emerging around global economic growth prospects

Timeline:

The analysis suggests critical decisions on AI spending revisions may come in the first half of the year, making Q1-Q2 earnings reports particularly significant for market direction.