KPMG has recently released a report on “How AI is helping to improve energy efficiency and management in real estate.” It says that traditional retrofits are too slow and costly to deliver the scale of cuts required to reach net-zero goals of 2050, and instead points out that artificial intelligence is a faster route, but only together with the Strategic Energy Management (SEM) framework.
Exergio, a company that developed an AI-based tool for energy efficiency in commercial buildings, says that findings reflect what is already visible in real-world cases.
KPMG states that SEM should track how buildings use energy and assign clear responsibility for fixing problems. According to Karčiauskas, this usually means facility managers or energy officers are tasked with day-to-day oversight. However, certain tasks such as changing parameters in sensors should be automatically assigned to AI and machine learning models to adjust in real-time, with experts overseeing the process.
On its own, implementing a SEM mindset typically delivers 5-7% savings per year. But when used with AI, they rise to around 20%-30% state energy efficiency experts.
There are three tiers of SEM, according to the report. The first tier focuses on getting more out of what is already in place: engineers have to tune HVAC, lighting, and control systems so they run more efficiently day to day. This, according to Karčiauskas, is “a task of AI at the moment as we want to achieve faster savings”.
The second step is replacing worn or outdated equipment, for instance, boilers, chillers, or pumps, with models that use less energy. The third adds renewables or long-term power contracts, but only once the building’s basic energy consumption has been brought under control.
The authors of the paper stress that renewables should come last, since they deliver limited value if the building’s consumption has not already been optimised.
The study also indicates that efficiency depends less on new hardware and more on how existing systems are managed.
SEM has a five-step cycle. It includes assessment, planning, implementation, building capability, and monitoring. Within this setup, AI could regulate HVAC concurrently based on occupancy, weather, and usage, while managers define energy-saving goals, set comfort ranges, and review results.
Like this:
Like Loading...
Related
This entry was posted on September 15, 2025 at 12:26 pm and is filed under Commentary with tags KPMG. You can follow any responses to this entry through the RSS 2.0 feed.
You can leave a response, or trackback from your own site.
AI cuts energy waste by up to 30% in buildings says KPMG
KPMG has recently released a report on “How AI is helping to improve energy efficiency and management in real estate.” It says that traditional retrofits are too slow and costly to deliver the scale of cuts required to reach net-zero goals of 2050, and instead points out that artificial intelligence is a faster route, but only together with the Strategic Energy Management (SEM) framework.
Exergio, a company that developed an AI-based tool for energy efficiency in commercial buildings, says that findings reflect what is already visible in real-world cases.
KPMG states that SEM should track how buildings use energy and assign clear responsibility for fixing problems. According to Karčiauskas, this usually means facility managers or energy officers are tasked with day-to-day oversight. However, certain tasks such as changing parameters in sensors should be automatically assigned to AI and machine learning models to adjust in real-time, with experts overseeing the process.
On its own, implementing a SEM mindset typically delivers 5-7% savings per year. But when used with AI, they rise to around 20%-30% state energy efficiency experts.
There are three tiers of SEM, according to the report. The first tier focuses on getting more out of what is already in place: engineers have to tune HVAC, lighting, and control systems so they run more efficiently day to day. This, according to Karčiauskas, is “a task of AI at the moment as we want to achieve faster savings”.
The second step is replacing worn or outdated equipment, for instance, boilers, chillers, or pumps, with models that use less energy. The third adds renewables or long-term power contracts, but only once the building’s basic energy consumption has been brought under control.
The authors of the paper stress that renewables should come last, since they deliver limited value if the building’s consumption has not already been optimised.
The study also indicates that efficiency depends less on new hardware and more on how existing systems are managed.
SEM has a five-step cycle. It includes assessment, planning, implementation, building capability, and monitoring. Within this setup, AI could regulate HVAC concurrently based on occupancy, weather, and usage, while managers define energy-saving goals, set comfort ranges, and review results.
Share this:
Like this:
Related
This entry was posted on September 15, 2025 at 12:26 pm and is filed under Commentary with tags KPMG. You can follow any responses to this entry through the RSS 2.0 feed. You can leave a response, or trackback from your own site.