Study: AI-Enabled BMS Cuts HVAC Energy Use by Up to 27%

The research highlights annual utility savings of between $13,600 and $49,300 per building at current commercial rates, savings that would reduce operating costs every year and have the potential to scale across larger portfolios. The research also finds the carbon avoided with the use of AI is more than 100 times greater than that produced by the AI system.

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, also found that AI-driven optimization deployed through a smart BMS, rather than a traditional one, can result in additional whole-building energy savings of between 7.2% and 12.7%. This shows how AI manages energy more intelligently, easing pressure on building systems and the wider electric grid, a Schneider Electric press release said.

The research involved modeling energy use in a three-story office building prototype of about 53,800 square feet. Different building management configurations were deployed, via computer modeling, in Brisbane, Australia, Miami, Florida, and Mumbai, India, which are in similar climate zones and rely heavily on air conditioning.

Other key findings of the company’s research include:

• Up to 60 metric tons of carbon emissions were 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 were seen 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, executive vice president of software and 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 used building energy modeling validated against real-world pilot deployments to assess how AI-enabled HVAC control impacts energy consumption, carbon emissions, and operating costs 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 Schneider press release said.

The research found that small and mid-sized buildings (less than 100,000 square feet) 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.

 “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,” Sharma said.