Net-zero goals by 2050 cannot be achieved without focusing on the decarbonization of commercial buildings, according to the Energy Transitions Commission’s (ETC) latest report, “Achieving Zero-Carbon Buildings: Electric, Efficient, and Flexible.” While national policies tend to target residential buildings, the ETC emphasizes that commercial buildings, which are responsible for 40% of total building operational energy consumption, should be the priority.
Commercial buildings, making up only 20% of global building stock by area, contribute significantly to energy use. In comparison, residential buildings, which account for 80% of the stock, are responsible for 60% of emissions. The ETC urges governments and stakeholders to shift their focus toward commercial properties and incorporate AI-driven solutions to help meet net-zero targets by 2050.
“Policymakers are often playing catch-up with technological progress. While laws promoting renewables and electrification exist, they are not enough, and bigger swings must be taken. We need a strategic approach, and it should be based on digitally retrofitting the commercial buildings first,” said Donatas Karčiauskas, CEO of Exergio, a company that implements AI-based energy efficiency tools in commercial buildings.
The report emphasizes how policymakers, asset owners, and technology providers can work together to address this challenge effectively. It claims that optimizing commercial buildings would cut more energy waste and carbon emissions because they consume nearly twice the energy per square meter compared to residential buildings.
Differences between residential and commercial buildings showcase decarbonization potential
Commercial buildings differ significantly from residential ones in various energy consumption patterns, and, according to energy experts, this is why they should be prioritized for decarbonization.
“Residential buildings have predictable energy usage patterns based on daily routines. Commercial buildings, on the other hand, operate on a much larger scale. Their occupancy rate fluctuates, and they have extended operating hours and intensive HVAC demands,” says Karčiauskas. “This means inefficiencies are magnified. Lighting, appliances, and cooling systems often run at full capacity even when not needed. Digital tools such as AI-powered energy management can solve that by adjusting ventilation, heating, and cooling in real-time.”
The report provides insights into the main areas that use energy and breaks down differences between residential and commercial buildings.
Due to their size, high occupancy, and dependency on energy-intensive equipment (e.g. computers), commercial buildings consume more electricity in the lightning and appliances area. In the US and EU, electricity supplies 35-50% of commercial building energy needs, compared to around 25% of residential buildings.
Space and water heating are less dominant in commercial buildings, accounting for 30-40% of total energy use (compared to over 60% in residential buildings). However, heating demand is significantly higher in sectors such as hotels and sports facilities.
Additionally, commercial buildings generally require more cooling, even in regions where residential air conditioning is uncommon. Space cooling accounts for approximately 15% of electricity consumption in commercial buildings, and about 6 % of energy use in residential buildings.
The role of AI in energy-efficient commercial buildings
While HVAC accounts for approximately 60% of commercial building energy use, the report emphasizes that energy efficiency potential levels vary among different kinds of buildings. Restaurants, healthcare, retail spaces, educational institutions, and offices are mentioned as high-impact areas.
The report recommends installing building management systems that integrate sensors, smart thermostats, and predictive AI to achieve real efficiency gains.
“For example, an office building with AI-powered sensors can preemptively reduce cooling loads before peak hours, and lower overall energy consumption without compromising comfort. It’s a triple-win situation: asset owners save money, there’s less emissions in the environments, and occupants have better working conditions,” continued Karčiauskas.
In Ozas Shopping Mall, located in Vilnius, Exergio previously implemented an advanced HVAC optimization system that helped save even more energy than ETC’s estimates–an AI-powered solution saved 29% of energy.
By optimizing heating and cooling strategies, the mall also saved €1 million and lowered carbon emissions without compromising visitor comfort.
“AI is no longer optional but a necessity. We have the technology to make commercial buildings more sustainable today. The challenge is to ensure widespread adoption before we run out of time,” concluded Karčiauskas.