KPMG: How AI Systems can Cut Building Energy Waste by 30%
Achieving substantial carbon emission reductions involves two primary strategies: transitioning to renewable energy sources and decreasing overall energy consumption.
The latter method, which centres on enhancing the efficiency of buildings technologies and infrastructure, is often a more direct and cost-effective route as it prioritises the elimination of waste over expensive hardware upgrades.
Research from KPMG indicates that AI can play a key role in accelerating this efficiency-led approach particularly within the real estate sector.
The report suggests that traditional retrofitting projects like replacing boilers with heat pumps or upgrading insulation may not be sufficient to meet global 2050 net zero ambitions.
KPMG instead puts forward the case for Strategic Energy Management (SEM) frameworks that are augmented by AI systems.
These frameworks can be integrated with a building’s heating and electrical networks via the Internet of Things (IoT) to automatically manage energy usage.
AI in strategic management
Companies that implement AI-based energy management are already reporting substantial decreases in their energy consumption.
Donatas Karčiauskas, CEO of commercial building energy efficiency firm Exergio, confirms the findings align with field experience.
"AI is already helping buildings cut waste by 20-30% in our projects, no matter the climate or the age of the property," Donatas says.
"But those savings only last if there's smart energy management behind them."
The CEO emphasises that success depends on ongoing operational oversight rather than one-time system installations.
AI for energy efficiency
KPMG's research details a hierarchical model for implementing energy efficiency improvements.
The first tier concentrates on optimising the systems already in place with AI adjusting HVAC lighting and control settings automatically based on real-time data.
According to Donatas this is "a task of AI at the moment as we want to achieve faster savings".
The second tier involves upgrading outdated equipment such as boilers chillers and pumps to more efficient modern counterparts.
The third and final tier is the installation of renewable energy systems and the arrangement of long-term power contracts.
AI is already helping buildings cut waste by 20% to 30% in our projects, no matter the climate or the age of the property.
The report stresses this should only occur after baseline energy consumption has been minimised.
Human-centric AI
The research emphasises the importance of maintaining human oversight within AI-powered energy management systems.
Donatas notes that his company's platform "connects to the building's energy management systems and uses metrics such as sensor data and occupancy patterns to adjust HVAC simultaneously".
This approach ensures "efficiency becomes a continuous management task, not something postponed until the next renovation".
The study advocates for what KPMG terms "human-centric AI" that maintains transparency and builds user trust while delivering automated optimisation.
