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Citigroup forecasts Big Tech's AI spending to cross $2.8 trillion by 2029

Published by Global Banking & Finance Review

Posted on September 30, 2025

2 min read

· Last updated: January 21, 2026

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Citigroup forecasts Big Tech's AI spending to cross $2.8 trillion by 2029
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By Rashika Singh and Joel Jose (Reuters) -Citigroup has raised its forecast for AI-related infrastructure spending by tech giants to surpass $2.8 trillion through 2029, from $2.3 trillion estimated

Citigroup Predicts Big Tech's AI Investments to Exceed $2.8 Trillion by 2029

By Rashika Singh and Joel Jose

(Reuters) -Citigroup has raised its forecast for AI-related infrastructure spending by tech giants to surpass $2.8 trillion through 2029, from $2.3 trillion estimated earlier, citing aggressive early investments by hyperscalers and growing enterprise appetite.

The AI boom ignited by ChatGPT's launch in late 2022 has continued to fuel staggering capital outlays and data center expansion despite a brief crisis of confidence sparked by China's cheaper DeepSeek model and lingering market concerns over U.S. President Donald Trump's tariff policies.

The Wall Street brokerage sees AI capex across hyperscalers to reach $490 billion by the end of 2026, up from its earlier estimate of $420 billion.

Data center operators - or hyperscalers - including Microsoft, Amazon and Alphabet have already spent billions of dollars in investments to ease capacity constraints that have hampered their ability to meet surging AI demand.

Citi analysts said hyperscalers were likely to reflect this incremental spend in their third-quarter earnings calls, with the guidance expected to be "building ahead of visible enterprise demand".

Citi estimates global AI compute demand would need 55 gigawatt of new power capacity by 2030, translating to $2.8 trillion in incremental spend, $1.4 trillion in the U.S. alone.

The brokerage said big tech firms are no longer relying only on profits to fund AI infrastructure. The costs are extremely high - about $50 billion for every 1 GW of compute capacity - and the companies are borrowing to keep up.

This shift is already showing up in their financials, with spending starting to eat into free cash flows. Investors are now asking how the tech companies will fund this scale of investment, especially as traditional models fall short.

"Enterprises have provided a clear external validation of value," Citi said, pointing to production deployments at companies such as Eli Lilly, Hitachi and Wolters Kluwer.

(Reporting by Rashika Singh and Joel Jose in Bengaluru; Editing by Pooja Desai)

Key Takeaways

  • Citigroup raises AI spending forecast to $2.8 trillion by 2029.
  • Hyperscalers like Microsoft, Amazon, and Alphabet lead investments.
  • AI capex expected to reach $490 billion by 2026.
  • Global AI compute demand requires 55 GW new power by 2030.
  • Tech firms increasingly borrow to fund AI infrastructure.

Frequently Asked Questions

What is Citigroup's revised forecast for AI infrastructure spending?
Citigroup has raised its forecast for AI-related infrastructure spending by tech giants to surpass $2.8 trillion through 2029, up from an earlier estimate of $2.3 trillion.
How much do hyperscalers expect to spend on AI capital expenditures?
Citi expects AI capital expenditures across hyperscalers to reach $490 billion by the end of 2026, an increase from the previous estimate of $420 billion.
What are the implications of AI spending on tech companies' financials?
The high costs of AI infrastructure are starting to impact free cash flows, raising concerns among investors about how tech companies will fund these substantial investments.
What is the expected global AI compute demand by 2030?
Citi estimates that global AI compute demand will require 55 gigawatts of new power capacity by 2030, translating to $2.8 trillion in incremental spending, with $1.4 trillion expected in the U.S. alone.
Which companies are mentioned as examples of enterprise AI deployments?
Citi points to production deployments at companies such as Eli Lilly, Hitachi, and Wolters Kluwer as examples of enterprises validating the value of AI.

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