AI and Sustainability: Building a More Resilient Digital Future

Supporting AI requires energy, cooling and infrastructure

AI may be digital, but the systems that support it are physical. From data centers and computing equipment to cooling, power and water, AI depends on infrastructure that has a physical footprint and resource demands. By approaching AI and sustainability as two intertwined priorities, we can help improve how the next generation of digital infrastructure is designed and operated. 

A crucial energy management opportunity lies in data center cooling technology. AI requires significant amounts of computing power to operate, and that process generates heat. Improving the efficiency of data center cooling technologies can support the computing infrastructure needed for AI while minimizing environmental impact. Innovative technologies including advanced chillers, liquid cooling solutions and comprehensive thermal management are helping data centers support larger AI workloads while improving sustainability and overall performance.

For example, through our collaboration with NVIDIA, Trane Technologies has developed an integrated thermal management reference design that brings together cooling systems, controls and other technologies to meet the rapidly changing thermal needs of high-density computing. 

AI can also be used to optimize other infrastructure elements needed to support AI. Intelligent controls, digital solutions and energy management systems can continuously analyze and adjust energy use in real time, identifying inefficiencies while improving system performance. By making energy management in data centers more efficient, we can accommodate growing AI workloads while using energy more intelligently.

Bringing AI and sustainability together isn’t just about using less energy. It’s also about finding new uses for resources that might otherwise be wasted. For example, even the heat generated by AI operations can become a resource. At a data center operated by Swiss cloud provider Infomaniak, Trane Technologies’ heat pump technology captures waste heat and helps warm nearby homes, demonstrating how data centers can become part of a circular energy system through smarter energy management. 

These examples demonstrate how artificial intelligence and sustainability can advance together when energy and resource efficiency are integrated holistically across the AI ecosystem. Together, these approaches can help make the infrastructure supporting AI more efficient, helping build a more sustainable digital future.

Leveraging AI for sustainability

The other side of this equation is AI’s ability to reduce energy and resource use across a broad array of industries and applications. By turning data into actionable insights, AI can help organizations improve energy management, optimize building performance and reduce waste across existing systems. 

The built environment represents a particularly significant opportunity for AI and sustainability. Buildings account for almost 1/3 of global energy use, but up to 30% of the energy purchased for commercial buildings is wasted. AI-powered building technology can predict building energy needs and automatically optimize HVAC systems. For example, in the 52-story Meera Tower in Dubai, BrainBox AI, a Trane Technologies company, reduced HVAC energy consumption by over 40% in just four months.

Smart buildings can also use AI to predict energy needs, automate heating and cooling, identify equipment issues and optimize building performance. These advanced technologies show how AI for sustainability can improve efficiency within existing infrastructure while improving performance. 

The applications don’t stop with these real-world examples. AI can support a broad array of sustainability outcomes for the planet, from improving climate and weather modeling to monitoring ecosystems and habitats to help us better understand and preserve complex environmental ecosystems. 

The future of AI and sustainability

AI growth and sustainability do not need to be opposing forces. The relationship between them is increasingly dynamic: AI creates new demands on infrastructure, energy and cooling, but it also creates new opportunities to improve efficiency, reduce waste and optimize performance. 

Solutions such as advanced data center cooling, intelligent energy management, smart buildings and digital solutions show what is possible when AI and sustainability are approached together rather than separately.

Together, these approaches can help AI and sustainability advance in tandem, supporting the digital infrastructure needed to power the future while making that future more efficient, resilient and sustainable.