AI-enabled buildings can cut energy use by up to 22%, saving on annual utility costs and carbon, according to research from Schneider Electric.

Published at this month’s Climate Week show in New York, the research shows AI-enabled buildings can cut whole-building energy use by up to 22% compared with traditional controls. The research highlights annual utility savings as $13,600 to $49,300 per building at current commercial rates, helping organisations reduce operating costs every year with the potential to scale across larger portfolios.

The research also found the carbon avoided is more than 100 times greater than the AI system’s footprint.

As concerns grow over AI’s environmental impact, buildings remain one of the world’s largest sources of emissions, accounting for approximately 37% of global energy-related carbon emissions. Schneider’s research found that AI-driven HVAC optimisation deployed through a smart building management system can contribute 7.2 to 12.7% of additional building energy savings. This shows how AI manages energy more intelligently, easing pressure on building systems and the wider electric grid.

Up to 60 metric tons of carbon emissions can be avoided annually per building (59,869kg CO₂e), comparable with the environmental benefit of planting 2700 mature trees. More than 200MWh of annual energy savings is possible in some buildings, enough electricity to power dozens of average homes for a year.

AI can more than double the energy savings achieved by smart building controls alone. Both cloud and edge AI deployments can deliver significant energy and carbon benefits.

“The future of building management will be defined by how effectively organisations connect and contextualise data that were previously trapped in silos,” said Pankaj Sharma, executive vice president at Schneider Electric (www.se.com). “An AI layer on top of existing business systems can turn complexity into intelligence and intelligence into action, reducing emissions, lowering costs and improving performance simultaneously. As energy demand continues to rise, the ability to deliver these outcomes together, rather than forcing organisations to choose between them, will be critical to achieving both business and sustainability goals.”

The research uses building energy modelling validated against real-world pilot deployments to assess how AI-enabled HVAC control impacts energy consumption, carbon emissions and operating costs across Australia, India and the USA in differing building scenarios.

The study examined how an AI layer deployed on top of digital building management systems can connect previously siloed data sources, continuously analyse building conditions and automate HVAC optimisation in real time. By incorporating data from occupancy patterns, weather forecasts, equipment performance and other operational inputs, AI can enable buildings to operate more efficiently while reducing the burden on facility management teams.

The research also found that small and mid-sized buildings (less than 9300 square metres) stand to benefit significantly from AI-enabled optimisation. Historically, energy management systems have been considered too complex or costly for smaller facilities, where dedicated facilities expertise is often limited. By helping automate and simplify optimisation, AI can make sophisticated building management more accessible, enabling smaller buildings to reduce energy consumption, lower operating costs and cut emissions.

“AI is putting the power of energy intelligence into the hands of smaller building owners and operators,” said Sharma. “What once required significant expertise and investment can now be achieved more simply and at greater scale, helping organisations reduce energy waste, lower costs, improve performance and make smarter decisions with confidence.”

The report can be downloaded at  www.se.com/ww/en/download/document/Buildings_WP521_EN/.