This HVAC optimization enhancement is realized through deployment across various building scenarios, augmenting existing smart controls.

New research shows AI can substantially boost energy and carbon benefits in both cloud and edge deployments, with the smallest buildings under 100,000 square feet standing to gain the most from automated optimization.

The study models cloud and edge AI deployments across Australia, India, and the United States, identifying small and mid-sized buildings under 100,000 square feet as the primary beneficiaries.

It concludes that AI makes sophisticated building management accessible for smaller portfolios, helping reduce energy use, lower operating costs, and cut emissions.

At Climate Week NYC 2026, Schneider Electric released findings that AI-enabled buildings can cut whole-building energy use by as much as 22% versus traditional controls.

Schneider Electric’s Pankaj Sharma notes that layering AI over existing systems turns siloed data into actionable insights, driving emissions and cost reductions while improving performance.

The study projects annual utility savings per building in the range of $13,600 to $49,300 at current commercial electricity rates, with savings recurring annually.

Savings are presented as recurring each year and applicable to larger portfolios beyond individual buildings.

Some scenarios show more than 60 metric tons of CO2e avoided per building annually, with total avoided emissions vastly exceeding the AI system’s footprint.

Environmental and operational metrics include up to about 60 metric tons of CO2e avoided per building annually and over 200 MWh of yearly energy savings in certain cases.

Overall, the amount of carbon emissions avoided by AI-enabled optimization is more than 100 times the AI system’s own footprint.

AI-driven HVAC optimization, delivered via smart building management systems, can add 7.2% to 12.7% extra energy savings beyond baseline AI improvements, with some scenarios exceeding 200 MWh.