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Press releaseGlobeNewswire· February 9, 2026

Hyperscale Data Centers Market Set to Reach US$ 177.58 Billion by 2032 | AI Workloads and Cloud Expansion Reshape Global Infrastructure Says Astute Analytica

View original at globenewswire.com
Hyperscale Data Centers Market Set to Reach US$ 177.58 Billion by 2032 | AI Workloads and Cloud Expansion Reshape Global Infrastructure Says Astute Analytica Chicago, Feb…
Opening lines of the source · GlobeNewswire · short snapshot — read the full document at the original

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  • Daily content creation is projected to reach 463 exabytes within the next five years

    80% confidence
  • The global hyperscale data center market is expected to reach US$ 177.58 billion by 2032

    80% confidence
  • Connected devices worldwide are expected to reach 14.4 billion globally

    80% confidence
  • CRAC and CRAH units are anticipated to generate revenues exceeding US$1.36 billion by 2032, growing at a CAGR of approximately 2.24%

    80% confidence
  • The global hyperscale data center market was valued at US$ 111.57 billion in 2023

    80% confidence
  • The hyperscale data center market will grow at a CAGR of 5.3% during the forecast period 2024-2032

    80% confidence
  • The air-based cooling segment's revenue is projected to exceed US$ 1.36 billion by 2032

    80% confidence
  • More than 60% of data centers worldwide still rely on air-based cooling systems as of 2023

    80% confidence
  • Approximately 45 new hyperscale facilities are under development in the United States, each boasting power capacities of around 15 megawatts

    80% confidence
  • Global data generation reached an estimated 175 zettabytes (ZB) by 2023

    80% confidence
  • North America is projected to command over 45% of the total hyperscale data center market revenue share by the end of the forecast period

    80% confidence

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Morgan Stanley & Co. LLC
Two significantly different EPS values (10.21 vs 2.68 USD_per_share) are reported for Morgan Stanley on the same observation date (2025-12-31). Fact A specifies FY 2025, while Fact B's 'N/A' fiscal period is ambiguous. If both represent FY 2025 annual EPS, these values directly conflict. The magnitude of the difference (3.8x) is too large to attribute to rounding or minor calculation variations. The missing fiscal period in Fact B raises data quality concerns, but same-date observation + same attribute should reference the same period.
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