Exergio Study: Smart Buildings Still Lack Critical Data
AI cuts energy use by up to 36%, but Exergio warns system disconnects hinder full efficiency.
exergio.com
A new study published in Energy Reports evaluates the readiness of buildings for AI-based energy optimization and identifies key system-level challenges. While buildings are responsible for about 30% of global final energy consumption, the study emphasizes that the full potential of AI-driven energy tools depends on one critical factor: data quality and accessibility.
Energy efficiency experts in commercial buildings note that without proper audits and integration, even advanced technologies can’t deliver reliable performance. Most systems simply aren’t built to work together, and as a result, efficiency remains more of a theory than a reality.
Instead of just focusing on better technology, the research proposes a smarter structure. It introduces a six-layer reference model for Intelligent Building Management Systems (IBMS) – a framework that spans everything from sensors and meters to AI-powered decision-making.
The concept proposed by researchers suggests that a building’s lighting, HVAC, occupancy, and other systems must share real-time data across layers to best optimize performance.
The study claims that the biggest roadblock isn’t missing hardware – it’s missing integration. Traditional setups often rely on fixed schedules and siloed platforms. This means that key areas like HVAC and lighting, which together account for over 50% of energy use in commercial buildings, continue to operate inefficiently, regardless of how advanced the equipment may be.
“Everyone’s talking about smart tech – sensors, automation, analytics – but few are addressing the root issue: how fragmented building data still is,” says Donatas Karčiauskas, CEO of Exergio, a company developing AI-based platforms for energy optimization. “We’ve seen this for years. Buildings often have all the right parts, so we decided to build a system that data-connects them. Efficiency only happens when buildings act as a whole – and that starts with unified data.”
Karčiauskas pointed out that this challenge is especially visible in older buildings, where outdated hardware and isolated systems were never designed to work together. For example, HVAC systems might be controlled by one vendor’s software, lighting by another, and occupancy sensors may not connect to either – meaning no system has the full picture.
The study notes that even in new developments, mechanical, electrical, and digital systems are frequently designed and implemented separately. It also warns that without real-time data exchange between these layers, the label “intelligent” is often just branding, not a reflection of actual building performance.
But AI-based energy management can make a difference, says Karčiauskas.
Instead of treating HVAC or lighting as isolated units, IBMS can connect data streams from across the building, adjusting systems in real time to meet actual demand.
“We didn’t build another device – we built a connective layer. It links what’s already there and turns scattered data into coordinated, real-time action. That’s what makes the system intelligent – not the tools, but how they work together,” explained Karčiauskas.
This connected-systems-first approach is already delivering measurable results in real-case scenarios, not just studies.
In a large commercial shopping mall, Exergio’s platform cut electricity use by 29% and heating demand by 36% – all without replacing core infrastructure. In a network of office buildings in Poland, the same solution helped slash energy bills by €88,000 in just nine months.
These improvements weren’t the result of expensive retrofits or large-scale equipment upgrades, argued Karčiauskas. They came from activating the potential of what was already installed, transforming fragmented building systems into a unified control layer that reacts to real-time conditions, demand, and performance.
“Everyone wants smarter buildings – but too often, we start by chasing the newest tech instead of fixing the foundations. The future of energy efficiency won’t be defined by hardware – it will be defined by how well we integrate, align, and unlock the systems we already have,” concluded Karčiauskas.
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