In North America and Europe, radiators and boilers are gradually being switched on for the first time this season. Heating, in fact, is the largest single load for most commercial buildings, consuming approximately 32% of total energy.
As energy use will hit its peak in the coming winter months, experts say that in too many cases, instead of adapting, systems heat empty spaces and collide with cooling units, or overshoot by several degrees.
According to Exergio, a company that develops AI-driven optimisation tools for commercial buildings, this waste is predictable and could be prevented if we are aware of solutions other than deep renovations of technology overhaul.
“Many countries didn’t learn from their summer mistakes. When heatwaves hit, air conditioners exposed how poorly many systems were set up,” said Donatas Karčiauskas, CEO of Exergio. “This winter, heating will show the same flaws and we’re sure most businesses are still not prepared. We need systems that respond to occupancy and weather shifts, not ones that waste energy because they lag behind.”
That waste is visible in every sector. Heating, cooling and ventilation can take up to 60% of a commercial building’s energy use, yet most systems run inefficiently, wasting large amounts of power.
Karčiauskas argues that better control is already available for building managers: they need to cut heating in unused areas and connect HVAC to occupancy and door sensors.
“Winter energy waste isn’t hidden and absolutely predictable. AI finally gives building managers that ability,” he said. “The real barrier is acting on it minute by minute.”
Traditional retrofits, such as insulation projects, façade upgrades or boiler replacements, take years to plan and carry out, while digital optimisation avoids that delay.
It connects to the energy systems already running in a building and adjusts them daily to match occupancy and weather, preventing waste before it builds up.
“We call it a soft retrofit,” Karčiauskas said. “No extra construction, no disruption, no deep renovations are needed in this case. It’s all in optimisation.”
One example from Exergio’s projects in Europe shows how this works in reality. When a property services company connected over 2,000 heating stations to the Exergio analytics platform, instead of sending technicians on weekly rounds, the system could carry out checks around the clock.
“The platform detected faults in sensors, valves or control devices remotely and adjusted parameters accordingly in real time. Then, heating shifted with the weather, it lowered on sunny days, raised during cold winds and in some sites, room sensors automatically balanced the system to avoid overshooting,” Karčiauskas said.
Heating use fell by more than 15% without any insulation upgrades and maintenance teams completed their work 20% faster. For the operator, this meant fewer site visits, lower costs and buildings that kept occupants comfortable while wasting less energy. In other case studies, energy waste was reduced by up to 30%.
“As heating demand peaks, the businesses that adopt AI will see lower bill, and there will be fewer emissions,” Karčiauskas said.
