Schneider Electric published a new research 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 trees*
- 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 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,” Pankaj Sharma, EVP, Software & Services at Schneider Electric.