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

New Schneider Electric research quantifies how AI-based HVAC optimization can deliver recurring energy, cost and carbon savings, especially in smaller buildings.

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Schneider Electric (SBGSY) released research at Climate Week NYC 2026 showing AI-enabled buildings can cut whole-building energy use by up to 22% versus traditional controls.

The study estimates annual utility savings of $13,600–$49,300 per building at current commercial rates, with carbon avoided more than 100 times the AI system’s own footprint. AI-driven HVAC optimization deployed through smart building management systems delivers an additional 7.2–12.7% building energy savings, in some cases exceeding 200 MWh and avoiding up to 60 metric tons of CO₂e per year. Both cloud and edge AI deployments were modeled across building scenarios in Australia, India and the U.S, with small and mid-sized buildings under 100,000 sqft identified as major beneficiaries.

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• Research finds AI in buildings can cut whole-building energy use by up to 22% against traditional controls
• Annual utility savings of $13,600 to $49,300 per building at current commercial rates, with savings recurring year after year
• Carbon avoided is more than 100 times the AI system’s own footprint
  

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.

Other key findings include:

• Up to 60 metric tons of carbon emissions avoided annually per building (59,869kg CO₂e), comparable to the environmental benefit of planting 2,700 mature trees¹
• More than 200 MWh of annual energy savings in some building scenarios, 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 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.

The research also found that small and mid-sized buildings (less than 100,000 sqft) stand to benefit significantly from AI-enabled optimization. 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 optimization, 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. What once required significant expertise and investment can now be achieved more simply and at greater scale, helping organizations reduce energy waste, lower costs, improve performance, and make smarter decisions with confidence,” added Sharma.

Download the full report: LINK.

Press contact: mediarelations@se.com

About Schneider Electric
Schneider Electric is a global energy technology leader, driving efficiency and sustainability by electrifying, automating, and digitalizing industries, businesses, and homes. Its technologies enable buildings, data centers, factories, infrastructure, and grids to operate as open, interconnected ecosystems, enhancing performance, resilience, and sustainability. The portfolio includes intelligent devices, software-defined architectures, AI-powered systems, digital services, and expert advisory. With 160,000 employees and 1 million partners in over 100 countries, Schneider Electric is consistently ranked among the world’s most sustainable companies. 

www.se.com

Learn more about Advancing Energy Tech on Schneider Electric Insights.

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¹ USDA Forest Service (McPherson et al., 1994)

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FAQ

AI-generated questions and answers. How Rhea-AI works. Not financial advice.

What building types and regions did Schneider Electric’s AI energy study cover?

The research used building energy modeling, validated against pilot deployments, to assess AI-enabled HVAC control in different building scenarios across Australia, India and the U.S. It examined how an AI layer on top of digital building management systems affects energy consumption, carbon emissions and operating costs in these regions.

How does the AI layer optimize building HVAC performance?

The study describes an AI layer deployed on existing digital building management systems that connects previously siloed data sources, continuously analyzes building conditions and automates HVAC optimization in real time. By incorporating inputs such as occupancy patterns, weather forecasts, equipment performance and other operational data, the AI enables more efficient operation and reduces the burden on facility management teams.

Why are small and mid-sized buildings highlighted in the findings?

The research found that buildings under 100,000 sqft can benefit significantly from AI-enabled optimization. Historically, energy management systems have been seen as too complex or costly for smaller facilities with limited dedicated expertise. By automating and simplifying optimization, AI can make advanced building management more accessible, helping these smaller buildings cut energy use, lower operating costs and reduce emissions.