Schneider Electric finds AI-enabled buildings can cut energy use by up to 22%, save on annual utility costs and carbon

NEW YORK, Sept. 21, 2026 (GLOBE NEWSWIRE) — Schneider Electric , a global energy technology leader, today published new research at Climate Week NYC 2026 finding that AI-enabled buildings can cut whole-building energy use by up to 22% against traditional controls. The research highlights annual utility savings as $13,600 to $49,300 per building at current commercial rates, helping organizations reduce operating costs every year with the potential to scale across larger portfolios. The research also finds 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 Electric’s new research, AI for Climate: Quantifying the Energy and Carbon Impact of Building Optimization , found that AI-driven HVAC optimization deployed through a smart building management system can contribute 7.2-12.7% of additional building energy savings. This shows how AI manages energy more intelligently, easing pressure on building systems and the wider electric grid.

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“The future of building management will be defined by how effectively organizations connect and contextualize data that was previously trapped in silos. 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,” said Pankaj Sharma, EVP, Software & Services at Schneider Electric . “As energy demand continues to rise, the ability to deliver these outcomes together, rather than forcing organizations to choose between them, will be critical to achieving both business and sustainability goals.”

The research uses building energy modeling 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 U.S 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 analyze building conditions, and automate HVAC optimization 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.