KPMG Report: AI Combined with Strategic Energy Management Can Cut Building Energy Use by up to 30%
A report published by KPMG, titled "How AI is helping to improve energy efficiency and management in real estate," concludes that conventional renovation methods are insufficient to meet necessary energy consumption reduction targets in a timely or cost-effective manner. The report identifies the application of Artificial Intelligence (AI) within a Strategic Energy Management (SEM) framework as the most rapid and effective path to achieving significant efficiency gains in buildings.
The consultancy emphasizes that the primary value is derived not from the installation of new technologies, but from the intelligent management of existing building systems. This finding is corroborated by on-the-ground implementation data from PropTech firms such as Exergio, which develops AI tools for commercial properties. According to Exergio, its AI-driven projects are consistently reducing unnecessary energy consumption by 20-30% across diverse climates and building types.
The report underscores that such savings are only sustainable when supported by a continuous, active energy management process. The SEM framework provides the methodology for this, establishing the necessity of continuous energy measurement and assigning clear responsibilities for correcting performance deviations. Under this model, routine supervision is handled by facility or energy managers, while real-time operational adjustments, such as modifying sensor parameters, are executed automatically by AI and machine learning models under expert oversight.
KPMG and other industry specialists estimate that implementing the SEM methodology alone can generate annual energy savings of 5% to 7%. The combination of SEM with AI technology elevates this potential savings range to between 20% and 30%. The key differentiator is the system's capacity to make continuous, data-driven adjustments to building operations.
The report outlines a three-tiered approach within the SEM framework. The first and most immediate step is to optimize the daily operation of existing heating, ventilation, and air conditioning (HVAC), lighting, and control systems. This "fine-tuning" is identified as an ideal application for AI, capable of delivering rapid savings. The second step involves the replacement of obsolete equipment with more efficient alternatives. The third and final step is the incorporation of renewable energy sources, which the report's authors stress should only be undertaken after the building's baseline energy demand has been fully optimized.
Beyond the technology itself, the document highlights the importance of the organizational factor. A culture of active energy management is deemed essential. The SEM framework defines the operational rules, and AI ensures that equipment adheres to these rules continuously, while strategic decisions remain in human hands.
In practice, an AI system can regulate a building's climate control by simultaneously analyzing occupancy levels, weather forecasts, and historical usage patterns. Meanwhile, human managers are responsible for setting savings objectives, defining comfort parameters, and analyzing performance results. Exergio notes that its platform operates on this principle, connecting to a building's management systems to adjust HVAC operations based on real-time metrics.
This "people-centric" approach to AI aims to increase transparency and build trust in automated daily operations, positioning data-driven management as the new standard for efficient and sustainable real estate.
Stay updated on real estate technology trends at realestate-lisbon.com.
