Global Air-Cooled and Dry Heat Rejection Equipment for AI Training Clusters Market Strategic Research Report

Scope of the Report

The global Air-Cooled and Dry Heat Rejection Equipment for AI Training Clusters market size is predicted to grow from US$ 1,810 million in 2025 to US$ 7,433 million in 2032; it is expected to grow at a CAGR of 19.2% from 2026 to 2032.

Air-cooled and dry heat rejection equipment for AI training clusters refers to engineered facility-side cooling equipment and systems that reject heat from AI training clusters, HPC facilities and high-density data centres to the outdoor ambient air. The scope focuses on the primary heat rejection and cooling plant layer, including dry coolers, adiabatic dry coolers, air-cooled fluid coolers, air-cooled chillers with free-cooling functions, outdoor heat rejection modules for liquid-cooling loops, and equipment integrated with CDUs, CRAHs, direct-to-chip cold plates or immersion cooling systems. Key performance parameters include cooling capacity, thermal efficiency, fan power, acoustic performance, footprint, redundancy, free-cooling hours, water-use profile, reliability and modular deployability.

Air-cooled and dry heat rejection equipment for AI training clusters should be understood as a facility-side infrastructure category rather than as a conventional cooling-tower market. The category sits at the intersection of mature HVAC equipment, industrial heat exchangers, precision data-centre cooling and emerging liquid-cooling infrastructure. Its role is to reject heat from AI training workloads, high-density racks, CDUs, chilled-water loops and liquid-cooling circuits to the outdoor ambient environment. As AI clusters move towards higher rack densities and more concentrated thermal loads, the relevant buying criteria are shifting from unit-level cooling capacity alone to system reliability, modularity, water-use profile, free-cooling hours, redundancy, acoustic performance, footprint and speed of deployment.

The global supply structure is layered. Large thermal-management groups such as Johnson Controls, Carrier, Trane, Daikin and Vertiv are positioned around integrated cooling plants, air-cooled chillers, CRAHs, CDUs, controls and global service networks. Specialist heat-rejection manufacturers such as SPX/Marley, BAC, EVAPCO, Kelvion, Alfa Laval, ThermoKey and LU-VE compete through dry coolers, adiabatic coolers, air-fin coolers and industrial heat-exchange know-how. China and Taiwan add a fast-growing regional layer, represented by Envicool, Shenling, Canatal, Midea Building Technologies and Delta Electronics, where local AI computing projects, telecom operators and internet customers are accelerating demand for customised, rapidly deployable cooling systems.

Demand growth is driven by new AI factories, retrofits of existing data centres for liquid-cooled racks, and water-constrained regions seeking alternatives to conventional wet cooling. The rise of direct-to-chip and immersion cooling does not eliminate the need for outdoor heat rejection. Instead, liquid cooling moves heat more efficiently from chips and racks into fluid loops, which then require dry coolers, air-cooled chillers, adiabatic coolers, cooling towers or other external heat sinks. The most important industry transition is therefore not air cooling versus liquid cooling in isolation, but the integration of liquid-cooled IT with efficient, scalable and water-conscious facility-side heat rejection.

Key Questions Addressed in this Report

What is the 10-year outlook for the global Air-Cooled and Dry Heat Rejection Equipment for AI Training Clusters market?

What factors are driving Air-Cooled and Dry Heat Rejection Equipment for AI Training Clusters market growth, globally and by region?

Which technologies are poised for the fastest growth by market and region?

How do Air-Cooled and Dry Heat Rejection Equipment for AI Training Clusters market opportunities vary by end market size?

How does Air-Cooled and Dry Heat Rejection Equipment for AI Training Clusters break out by Heat Rejection Equipment, by Application?

This report presents a comprehensive overview of the global Air-Cooled and Dry Heat Rejection Equipment for AI Training Clusters market, covering market size and forecast, segmentation by product type and application, competitive landscape, leading players and regional and country-level outlook.

Segment by Heat Rejection Equipment

• Dry Cooler
• Adiabatic Dry Cooler
• Air-Cooled Chiller
• Integrated Outdoor Cooling Module

Segment by System Layer

• Primary Heat Rejection
• Cooling Plant
• Room / Row Interface
• Rack / IT Interface

Segment by Cooling Mechanism

• Sensible Dry Cooling
• Adiabatic-Assisted Cooling
• Mechanical Refrigeration
• Hybrid Free Cooling

Segment by Application

• AI Training Rack
• HPC / Supercomputing Rack
• Cloud Data-Centre Rack
• Telecom / Edge High-Power Rack
• Other

Who Can Use This Report?

This report is written for decision-makers who need a clear, data-backed view of the global Air-Cooled and Dry Heat Rejection Equipment for AI Training Clusters market:

• Manufacturers, suppliers and solution providers benchmarking their position and planning product, capacity and go-to-market strategy
• Distributors, channel partners and end users in AI Training Rack, HPC / Supercomputing Rack, Cloud Data-Centre Rack evaluating demand and sourcing options
• Investors, financial analysts and consultants assessing growth opportunities, competitive dynamics and M&A potential
• Government agencies, industry associations and research institutions tracking industry developments and policy impact