'AI's role in optimising building operations and energy performance is receiving continuous attention, and if you’re not using it, you might be already falling behind. It offers real-world solutions that are implementable here and how. Also, since the updated EU’s directive for buildings recently encouraged energy data sharing, we are sure that energy savings using AI will improve even more,” said Donatas Karciauskas, CEO of Exergio, a company that develops AI tools for building energy efficiency. “Current algorithms lead to the reduction of energy waste by up to 20%, but open-access for building’s data can increase these numbers. The fact that the  scientific community analyzes such solutions is usually the first step towards general acceptance, and seeing how aligned with latest tools it is, it is just a matter of time when it will become a standard in the industry.”

The study, titled 'Potential of Artificial Intelligence in Reducing Energy and Carbon Emissions of Commercial Buildings at Scale,' evaluates AI's impact on medium office buildings in the United States. It highlights several key areas where AI can make a substantial difference.

First of all, AI can enhance the efficiency of HVAC systems and lighting by learning and predicting optimal operating conditions. It can dynamically adjust heating, cooling, and lighting based on real-time occupancy data, reducing energy use during off-hours. Finally, research shows that the latest tech provides precise control over building systems, allowing for real-time adjustments 24/7.

“The study’s findings resonate with our projects,” Karciauskas noted. “For example, in office buildings we manage, there are 1000s of data points that can impact energy performance, and no human can oversee that. When we employ AI to help us, we know what to focus on. During off-hours, our system reduces energy usage in unoccupied areas, and ramps it up just before peak usage times, enhancing both comfort and efficiency.”

The study highlights the importance of integrated energy management as a critical strategy for achieving substantial emissions reductions and operational savings. 

It also highlights the economic potential of AI in building digitalization. It compares business-as-usual (BAU) and low-emission power generation (LEPG) scenarios, where the latter includes the use of AI. It is considered the best-case scenario that can collectively lead to energy savings reaching up to 40%.

“The integration of AI-for-energy in buildings, and especially commercial buildings, is also a great way to attract investors,” Karciauskas added. “It is setting new standards for sustainability. Even though research focused on commercial buildings in the US, regulations in the EU are already confirmed and businesses will have to shift towards sustainable solutions. It feels like we’re finally making it through in the commercial sector, which is still heavily responsible for greenhouse gas emissions.”

In Poznan, Poland, buildings equipped with Exergio’s AI platform achieved 20% reductions in energy waste, translating to financial savings of €80k in 9 months.