AI Data Center Cooling Optimization Market

Overview

The AI Data Center Cooling Optimization Market was valued at an estimated USD 1.44 billion in 2025 and is projected to reach approximately USD 12.38 billion by 2034, growing at a CAGR of 27.0% during the forecast period (2026-2034). The market growth is driven by the explosive rise of AI training and inference workloads, the resulting surge in rack power density, and growing recognition among data center operators that software-driven, autonomous cooling control can deliver substantial energy savings beyond what static, rule-based building management systems can achieve. The market is shifting from conventional, reactive cooling management to AI-driven predictive thermal optimization. Government initiatives such as the U.S. Department of Energy’s COOLERCHIPS 1.5 program support advanced, water-free cooling systems for AI data centers, while India’s Energy Conservation and Sustainable Building Code promotes energy and water efficiency in data centers. By region, North America held the largest share of the market in 2025, reflecting the concentration of hyperscale AI data center construction and the early commercial presence of leading AI cooling optimization vendors in the United States specifically. Asia-Pacific is projected to be the fastest-growing region during the forecast period, consistent with the region's rapid build-out of new AI-ready data center capacity.

Market Size & Share

Market Dynamics

KEY MARKET TREND

Feed-Forward Predictive Control, Facility-Wide AI Agent Orchestration and Digital Twin Modeling Emerging as Trends

• Feed-forward control approaches, which use rack-power measurements to anticipate heat generation and adjust coolant distribution before temperatures actually rise, are emerging as a technically distinct advance over conventional feedback-based control, directly addressing the lag between rapidly changing AI workloads and cooling system response times.
• Vendors are increasingly expanding their AI agents beyond cooling optimization alone into broader facility management, including electrical distribution, battery dispatch, and AI workload scheduling, reflecting growing recognition that these systems must be orchestrated together.
• Physics-aware digital modeling of individual facilities, built from a comprehensive mapping of each site's specific sensor and equipment layout, is becoming a standard deployment prerequisite, enabling AI control systems to be tailored precisely to each data center's unique thermal and electrical characteristics.
• Digital twin and predictive-control technologies are gaining traction, with recent studies demonstrating 9.4%–27.8% cooling-energy savings through predictive optimization and real-time modeling.

KEY MARKET DRIVER

Explosive AI Workload Growth and Proven Energy Savings Are the Key Drivers

• The explosive rise of AI training and inference workloads continues to drive rack power densities to levels that make static, rule-based cooling control increasingly inadequate, directly reinforcing demand for AI-driven dynamic optimization.
• Cooling's position as roughly 30% of total data center energy consumption, second only to compute itself, makes it a uniquely high-value target for AI-driven efficiency improvements relative to other facility subsystems.
• Credible, publicly disclosed energy savings results, including a major hyperscaler's reported 40% reduction in cooling costs through AI implementation, continue to reinforce operator confidence that AI-driven cooling optimization delivers real, measurable returns rather than speculative efficiency claims.
• The IEA estimates that global data-center electricity consumption will rise from 415 TWh in 2024 to around 945 TWh by 2030, driven mainly by AI workloads, while Google has demonstrated up to 40% cooling-energy savings through AI-based optimization.

KEY MARKET OPPORTUNITY

Facility-Wide AI Orchestration, Liquid-Cooling-Specific Control and International Expansion Create Opportunity

• Expansion from cooling-specific optimization into comprehensive facility management, spanning electrical distribution, battery dispatch, and AI workload scheduling, represents a substantial opportunity for vendors capable of becoming the unified control layer across an entire data center's infrastructure.
• Growing deployment of liquid cooling specifically, which requires more responsive, higher-precision control than conventional air cooling given AI workloads' rapid and large thermal swings, represents an opportunity for vendors capable of developing liquid-cooling-specific AI control capability.
• International expansion into higher energy-cost regions outside the vendor's home market represents a significant opportunity, given that regions with higher electricity prices generate proportionally larger financial returns from AI-driven cooling energy savings.
• Government initiatives such as the U.S. Department of Energy’s COOLERCHIPS 1.5 program are supporting advanced, water-free cooling systems for AI data centers, while the European Commission’s 2026 data-center energy-efficiency framework promotes energy and water performance monitoring, creating opportunities for optimized cooling solutions across international markets.

AI Data Center Cooling Optimization Market Size, 2025–2034 (USD Billion)

Segmentation Analysis

Analysis by Offering

AI Control Software held the largest market share in 2025, reflecting the core AI agent and control algorithm layer that forms the primary value driver within any cooling optimization deployment. It enables real-time monitoring, predictive control and automated adjustment of cooling systems based on workload and thermal conditions. Its ability to integrate with existing data center infrastructure also supports wider adoption across different cooling configurations.

Professional Services are projected to grow at the fastest CAGR during the forecast period, as the facility-specific mapping, physics-aware digital modeling, and integration work required for each deployment scales alongside broader market adoption; this designation is analyst judgment. These services help operators assess existing cooling infrastructure, identify optimization opportunities and configure AI control systems according to facility-specific thermal and operational conditions. They also support the integration of software with cooling equipment, sensors, building management systems and data-center management platforms.

Offering categories include

• AI Control Software (Dominating Segment)
• Professional Services (Highest CAGR Segment)
• Monitoring & Analytics

Analysis by Deployment

Supervisory Layer deployment held the largest market share in 2025, in which AI control software connects on top of an existing building management or SCADA system rather than replacing it, is estimated to hold the largest market share, reflecting this approach's lower barrier to adoption for operators with substantial existing cooling infrastructure investment. This deployment model allows facilities to introduce AI-based optimization without making major changes to existing control architecture or cooling equipment.

Embedded Controls are projected to grow at the fastest CAGR during the forecast period, as new-build AI data centers increasingly specify AI-native control systems from the outset rather than retrofitting supervisory software onto conventional controls; this designation is analyst judgment. These systems can be integrated directly into cooling equipment, sensors and facility control architectures during the design stage, enabling faster data exchange and more coordinated control. They also support real-time response to changing computational loads and thermal conditions across AI-optimized facilities.

Deployment categories include

• Supervisory Layer on Existing SCADA (Dominating Segment)
• Embedded Controls (Highest CAGR Segment)

Analysis by Application

Liquid Cooling Optimization held the largest market share in 2025, reflecting liquid cooling's rapidly growing share of new AI data center capacity and its greater need for responsive, high-precision control relative to conventional air cooling. These systems can continuously adjust cooling parameters based on real-time workload and thermal conditions, improving energy efficiency while maintaining required operating temperatures. Rising deployment of direct-to-chip and other liquid cooling architectures in high-density AI facilities is therefore expected to support demand for specialized optimization solutions.

Thermal Risk & Capacity Management is projected to grow at the fastest CAGR during the forecast period, as operators increasingly prioritize predictive, feed-forward approaches capable of preventing heat-related incidents before they occur rather than reacting to them after temperatures rise; this designation is analyst judgment. Increasing rack densities, dynamic AI workloads and greater adoption of liquid cooling are expected to further increase the need for continuous thermal risk monitoring and capacity planning. This designation reflects analyst judgment.

Application categories include

• Liquid Cooling Optimization (Dominating Segment)
• Thermal Risk & Capacity Management (Highest CAGR Segment)
• Air Cooling Optimization

Analysis by End-User

Hyperscale data centers held the largest market share in 2025, consistent with hyperscale’s early adoption of AI-driven cooling optimization and their outsized share of overall AI data center capacity under construction. AI-based cooling optimization can help hyperscale operators coordinate cooling equipment, monitor thermal conditions and adjust energy use across large campuses. High investment capacity and the need to improve efficiency across expanding infrastructure further support adoption in this segment.

Colocation facilities are projected to grow at the fastest CAGR during the forecast period, as AI cooling optimization vendors extend their customer base beyond hyperscale operators into shared-infrastructure facilities serving AI workloads for a broader range of tenants; this designation is analyst judgment. AI-driven optimization can help coordinate cooling resources, improve energy efficiency and maintain thermal conditions as tenant workloads fluctuate. Growing demand for AI infrastructure from enterprises, cloud providers and other organizations is also expanding the need for advanced cooling management across colocation environments. This designation reflects analyst judgment.

End-User categories include

• Hyperscale (Dominating Segment)
• Colocation (Highest CAGR Segment)
• Enterprise

By Region

AI Data Center Cooling Optimization Market Share 2025

North America

48%

South America

xx%

Europe

xx%

Middle East Africa

xx%

Asia Pacific

22%

North America held the largest market share in 2025, reflecting the concentration of hyperscale AI data center construction in the United States, along with the early commercial presence of leading AI cooling optimization vendors headquartered there. The United States represents the primary demand center, supported by large-scale hyperscale deployments and investment in AI-ready data center infrastructure, while Canada is expanding data center capacity and adopting advanced cooling technologies for high-density computing. Mexico is also developing its data center infrastructure and provides an emerging market for AI-focused cooling optimization solutions. No publisher reviewed for this RD provided any quantified regional breakdown for this specific category; this regional allocation is an analyst-modeled estimate based on known AI data center construction concentration patterns rather than a category-specific source.

Asia-Pacific is projected to grow at the fastest CAGR during the forecast period, consistent with the region's rapid build-out of new AI-ready data center capacity. China is expanding domestic AI computing infrastructure at scale, while India is increasing data center capacity to support cloud, digital services and AI workloads. Japan continues to invest in advanced data center infrastructure, and South Korea is expanding AI computing capacity supported by its strong semiconductor and technology ecosystem. The Rest of Asia Pacific is also contributing through new capacity development across emerging digital markets. The region is reported elsewhere in the broader data center infrastructure research reviewed for this RD to be adding several gigawatts of new capacity through the remainder of the decade, though this designation should be treated as directional given the complete absence of category-specific regional data.

Regions Covered

North America (Dominating Region)

• United States
• Canada
• Mexico

Europe

• Germany
• United Kingdom
• France
• Italy
• Rest of Europe

Asia Pacific (Fastest Growing Region)

• China
• India
• Japan
• South Korea
• Rest of Asia Pacific

Latin America

• Brazil
• Chile
• Rest of Latin America

Middle East & Africa

• Saudi Arabia
• U.A.E.
• Rest of Middle East & Africa

Market Share

The market is fragmented led by a small group of specialist AI control vendors alongside AI-adjacent capabilities embedded within larger industrial and technology companies' broader offerings. Phaidra, a Seattle-based company founded by alumni of Alphabet's DeepMind research division, is a leading specialist, building AI agents that coordinate cooling, power, and workload management as a unified system; the company's liquid-cooling agent has been deployed and tested in production alongside a major cloud provider's liquid-cooled fleet. Vigilent specializes specifically in data center cooling optimization software and services, while EkkoSense provides AI-driven operational visibility, cooling capacity optimization, and thermal and power risk mitigation. Schneider Electric, Vertiv, Siemens, Johnson Controls, nVent Electric, NVIDIA, Hewlett Packard Enterprise, Eaton, Rittal, Carrier Global, Trane Technologies, and Submer Technologies strengthen the competitive landscape through AI-enabled controls, facility management platforms, liquid-cooling systems, thermal management technologies, intelligent infrastructure, and data center optimization solutions. Alphabet, through its DeepMind research division, pioneered much of the foundational AI approach to data center cooling optimization through its own internal deployments, informing the broader industry's confidence in the technology's potential. Competitive intensity is elevated around proven, production-validated energy savings and thermal risk reduction results specifically, given the category's reliance on credible, disclosed performance outcomes to build operator trust in autonomous control systems.

Key Players

• Phaidra, Inc. (United States)
• Vigilent Corporation (United States)
• EkkoSense Ltd. (United Kingdom)
• Schneider Electric SE (France)
• Vertiv Holdings Co. (United States)
• Siemens AG (Germany)
• Johnson Controls International plc (Ireland)
• nVent Electric plc (United Kingdom)
• NVIDIA Corporation (United States)
• Hewlett Packard Enterprise Company (United States)
• Eaton Corporation plc (Ireland)
• Rittal GmbH & Co. KG (Germany)
• Carrier Global Corporation (United States)
• Trane Technologies plc (Ireland)
• Submer Technologies S.L. (Spain)

Recent Market Developments

• July 2025: Activate Capital made a strategic investment in XNRGY Climate Systems to expand its United States manufacturing capacity and accelerate next-generation air handling and liquid-cooling solutions for hyperscale, modular, and edge data centers.
• January 2026: Motivair by Schneider Electric launched the MCDU-70, a 2.5 MW coolant distribution unit designed for high-density AI data centers, with systems scalable to 10 MW+ for next-generation AI and accelerated computing workloads.
• March 2026: Eaton completed its acquisition of Boyd Thermal, strengthening its liquid-cooling capabilities and enabling integrated grid-to-chip cooling solutions for AI-driven data centers.
• April 2026: Vertiv acquired Strategic Thermal Labs to strengthen liquid-cooling and thermal-management capabilities for high-density AI data centers, improving cold-plate design, server-side cooling, and thermal validation.

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