As per the study report “Future of Data Center / AI Data Center Market – Global Forecast to 2030″ released by MarketsandMarkets, the market for AI data centers is expected to develop at a compound annual growth rate (CAGR) of 30% and reach USD 100 billion by 2030.
The need for data centers that can handle AI workloads, such as training and inference for deep learning models, has increased due to the recent emergence of AI, or generative AI. AI has special requirements that traditional data center architecture, which was built for general-purpose computing, cannot provide. These requirements include parallel processing, high throughput, and low latency. Investments in dedicated AI data centers outfitted with cutting-edge IT gear, such as GPUs, TPUs, low-bandwidth memory, and ultra-high-speed interconnects, have increased as a result.
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Compute, cooling and power solutions are the most attractive segments within AI Data Center.
Among solution segments, Compute Solutions emerges as the most attractive, driven by demand for GPUs and accelerators to power Generative AI workloads. It holds the largest market size in 2025
Thermal Management ranks second, fuelled by innovations like direct-to-chip liquid cooling and digital twins for energy-efficient temperature control, boasting a 37% CAGR.
Power Management secures third place, integrating UPS systems with renewable energy and Li-ion battery energy storage (BESS) to improve sustainability and resilience, is estimated to be USD 7 billion in 2025.
These segments stand out as key enablers of high-performance, scalable, and eco-efficient AI data centers, positioning them at the forefront of market growth and investment priorities.
The future of AI Data Centers will be shaped by five key technological trends — Quantum Computing, D2C Cooling, 3D Stacking, Silicon Photonics, and Clean Energy Sources (Solar & Nuclear)
Quantum Computing stands as a game-changer, enabling data centers to tackle highly complex AI models, optimization problems, and simulations far beyond the reach of classical computing. This innovation holds the potential to dramatically accelerate AI training and inferencing capabilities.
Direct-to-Chip (D2C) Cooling is revolutionizing thermal management by enabling liquid cooling systems that are placed in direct contact with the processor, enhancing heat dissipation and allowing denser, more powerful AI workloads without overheating constraints.
3D Stacking transforms chip architecture by stacking multiple layers of processing units vertically, reducing latency, increasing bandwidth, and maximizing computational throughput — critical for AI’s demanding data processing needs.
Silicon Photonics advances networking infrastructure by using light instead of electrical signals, facilitating ultra-fast data transfer rates with lower power consumption, essential for handling massive AI datasets across distributed data centers.
Clean Energy Sources (Solar & Nuclear) are becoming vital to data center sustainability strategies, supporting carbon reduction goals while ensuring uninterrupted, reliable power for energy-intensive AI operations.
Together, these innovations will drive the next generation of AI data centers — faster, more efficient, and environmentally responsible.
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The US, India, UK, South Korea, and Italy are emerging as the most attractive countries for AI Data Centers
Driven by major announcements and large-scale projects, the US leads with massive initiatives from OpenAI, AWS, Meta, and Microsoft, and others including the multi-hundred-billion-dollar Stargate project. India follows with AdaniConneX, ST Telemedia planning a multi-billion-dollar investments. The UK and Italy see strong investments from Microsoft, focusing on energy-efficient infrastructure, while South Korea’s SK Telecom and LG U+ adopt cutting-edge GPUs and cooling technologies. Saudi Arabia (KSA) also stands out with a 1.5 GW AI Inferencing Data Center that is planned to be built by Saudi Aramco and Groq.
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