Press release
United States AI data centers market is to reach USD 12.28 billion by 2030 - Driven by Explosive Growth in Generative AI, High-Density Compute, and Next-Gen Liquid Cooling Technologies | DataM Intelligence
Global AI Data Centers Market reached US$ 13.67 billion in 2024 and is expected to reach US$ 78.91 billion by 2032, growing with a CAGR of 24.50% during the forecast period 2025-2032, according to DataM Intelligence report.
This growth is driven by demand for generative AI surges, driving investments in GPU-powered infrastructure, high-performance computing, and energy-efficient data center upgrades across the U.S.
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Industry Latest News 2025:
✅ November 2025: The global AI data center investment reached $580 billion in 2025, with the U.S. expected to account for half of this surge in demand. Many new data centers are being built with capacities of 200 megawatts or more, mostly near existing centers. Renewable energy is projected to power most new facilities by 2035
✅ October 2025: Eight hyperscalers project a 44% year-over-year increase to $371 billion in 2025 for AI data centers and computing resources. The U.S. power demand from AI data centers could grow more than thirtyfold by 2035, reaching 123 gigawatts from 4 gigawatts in 2024
✅September 2025: AI data centers are driving power bills to record highs in several U.S. states. Nvidia announced it will invest up to $100 billion in OpenAI to support data centers, while Microsoft and Oracle are also making large investments.
✅ November 2025: Google announced a $40 billion investment in three new data centers in Texas to expand AI computing capacity.
✅ November 2025: Major tech companies Microsoft, Alphabet, Meta, and Amazon reported plans to spend roughly $370 billion in 2025 on AI data center capital expenditures, underscoring a massive growth phase.
Recent Mergers & Acquisitions
BlackRock, Nvidia, and Microsoft-led group agreed to acquire Aligned Data for $40 billion, expected closing in 1H 2026. Aligned has 5 GW data center capacity focused on AI workloads.
CoreWeave, backed by Nvidia, acquired crypto miner Core Scientific for $9 billion to expand AI data center capacity.
Google plans $32 billion acquisition of cloud security startup Wiz to enhance AI cloud infrastructure.
AMD completed $4.9 billion acquisition of ZT Systems, gaining rack-level expertise for AI data centers.
IBM closed $6.4 billion purchase of HashiCorp, boosting hybrid cloud and AI infrastructure management.
Salesforce announced $8 billion acquisition of Informatica to strengthen AI-ready data management capabilities.
Market Segmentation Analysis
By Component
- Hardware: Largest revenue segment with about 68% share in 2024, driven by demand for high-performance GPUs and AI-optimized servers.
- Software: Includes AI management, orchestration, and data analytics tools, a growing but smaller segment.
- Services: Fastest growing segment, covering consulting, deployment, integration, and maintenance services.
By Deployment Mode
- Cloud-Based: Over 50% market share in 2024, led by hyperscalers offering AI infrastructure as a service.
- On-Premises: Used by enterprises for security and customization needs.
- Hybrid: Growing rapidly as organizations blend cloud scalability with on-prem control.
By Data Center Type
- Hyperscale Data Center: Largest segment with about 64% share, driven by tech giants scaling AI workloads.
- Colocation Data Center: Moderate share, serving companies needing scalable space and connectivity.
- Edge Data Center: Fastest growing, supporting low-latency AI applications.
Others (Enterprise, Hybrid, etc.): Serve specific industry and distributed computing needs.
By End-User Industry
- IT and Telecom: Largest user segment (~48% share), fueling cloud and AI service demand.
- Healthcare: Rapid growth in AI-powered diagnostics and research.
- BFSI: Uses AI for fraud detection, customer analytics.
- Automotive: Supports AI in autonomous vehicles and manufacturing.
- Retail: AI for inventory, customer experience.
- Media & Entertainment: AI in content creation and delivery.
- Manufacturing: AI for automation and predictive maintenance.
- Others: Smaller shares from education, government, etc.
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TheU.S. AI data centers market report would provide approximately
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Growth Drivers:-
Surging demand for AI workloads requiring high-performance computing power.
Increasing investments by hyperscalers in large-scale AI-optimized data centers.
Rapid adoption of cloud and hybrid deployment models for flexibility and scalability.
Rising data explosion and big data analytics fueling infrastructure needs.
Government spending and policies encouraging AI infrastructure development.
Growing AI-as-a-Service adoption broadening enterprise usage.
Need for energy-efficient, sustainable data center solutions.
Expansion of generative AI and machine learning applications driving compute demand.
Regional Insights:-
North America dominates with over 40% global market share, U.S. being the largest contributor with $171.9 billion market size in 2025.
Key U.S. data center hubs: Northern Virginia, Dallas-Fort Worth, Silicon Valley, Chicago, Phoenix, New York Tri-State, Atlanta.
Northern Virginia: largest data center concentration globally with 250+ centers, highest absorption and rental rates.
Dallas-Fort Worth market expected to double in size by end-2026 with strong expansions.
Growth concentrated in strategic electricity market regions: PJM Interconnection (VA, OH), Midcontinent Independent System Operator (IL, IA), Northwest (OR), Southeast (GA).
Increasing investment in AI data center capacity via projects like OpenAI/Oracle's 4.5 GW Stargate program in Texas.
Demand outpaces supply with data center vacancy at record-low 1.6% nationally, elevating lease rates and accelerating expansions.
Emerging markets with access to affordable power like Atlanta, Charlotte-Raleigh, Austin and San Antonio are growing rapidly.
U.S. leads data center power demand growth driven by hyperscalers and AI infrastructure investment.
Key Trends and Technological Advancements
Software giants like Microsoft, Amazon, Google, and Meta plan massive investments ranging from $40 billion to over $100 billion in AI data center infrastructure in 2025.
Rack power density is increasing drastically from 40 kW to as high as 250 kW, necessitating advanced cooling technologies like liquid and immersion cooling.
AI workloads require immense continuous power; U.S. data center power demand may double from 35 GW to 78 GW by 2035.
Hyperscalers dominate AI infrastructure investments, expanding large hyperscale data centers in primary and secondary markets driven by power availability.
Integration of AI for operational efficiency, predictive maintenance, and AI-specific hardware development (custom chips like Google TPU, AWS Inferentia) is rapidly evolving.
Generative AI and large language models push high demand for GPU-heavy infrastructure and high-density racks.
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Key Players:
Amazon Web Services (AWS), Microsoft, Google, Meta, Equinix, Digital Realty, CyrusOne, QTS Data Centers, DataBank, Vantage Data Centers, CoreSite, Cologix, Switch Inc., Cyxtera Technologies, Sungard Availability Services, H5 Data Centers, Intel, Cisco Systems, Dell Technologies, Hewlett Packard Enterprise, AMD, Nvidia
Key Highlights
Amazon Web Services (AWS): Planned $100 billion investment in AI data centers in 2025, driving cloud & AI innovation; expanding facilities in Ohio and Georgia.
Microsoft: Committed $80 billion for AI-enabled data centers globally in 2025, half focused on U.S. infrastructure; advanced AI workloads on Azure.
Google: Estimated $75 billion capital expenditure in 2025, primarily for expanding AI data centers and server infrastructure.
Meta: Allocated $60-65 billion for AI data center growth, building ultra-large facilities requiring gigawatts of power, pushing AI product development.
Equinix: Leading colocation provider investing heavily to scale AI infrastructure with hyperscalers through expanded interconnection services.
Digital Realty: Focused on hyperscale AI-ready data center construction and sustainability initiatives for large enterprise and cloud customers.
CyrusOne: Accelerating AI data center projects with high-capacity, energy-efficient builds in key U.S. markets.
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