In a recent study published in *Energy Reports*, researchers explore the readiness of buildings for AI-driven energy optimization, identifying major system-level challenges. Buildings comprise roughly 30% of the world’s energy consumption, yet the study stresses that the success of AI-based energy solutions largely depends on data quality and accessibility.
Despite advancements in technology, experts note that energy efficiency remains elusive without proper audits and system integration. The study introduces a six-layer model for Intelligent Building Management Systems (IBMS), advocating for real-time data sharing across systems like lighting, HVAC, and occupancy controls to optimize performance.
Donatas Karčiauskas, CEO of Exergio, emphasizes the core issue of fragmented data. “True efficiency begins with unified data,” he asserts, highlighting the disjointed nature of current building systems, especially in older infrastructures where integration wasn’t initially considered.
Even in new constructions, mechanical and electrical systems are often implemented separately, leading to inefficiencies. Karčiauskas argues that AI-based management can revolutionize building efficiency by connecting data streams and enabling real-time adjustments, as demonstrated by Exergio’s platform, which has significantly reduced energy costs in various real-world scenarios.
The study concludes that the future of energy efficiency will be defined by the integration and utilization of existing systems rather than new hardware, emphasizing the need for a foundational shift in how building systems are managed.
