Across the Gulf region, many buildings are performing differently today than they were originally designed to, highlighting a significant gap between predicted and actual energy use. This disparity, often referred to as the performance gap, presents an opportunity for substantial energy savings, improved asset performance, and enhanced long-term value.
The world’s energy landscape is shifting as global demand evolves. With oil prices nearing $100 per barrel and the rise of artificial intelligence rapidly increasing electricity consumption—particularly in data centers—the International Energy Agency projects data center electricity use to grow approximately 15 percent annually through 2030. This rate outpaces overall global electricity demand by more than four times, offering energy producers a generational-scale opportunity.
A persistent challenge within the building sector is addressing the difference between a building’s designed performance, typically certified at completion, and its operational reality. This issue is global and affects various markets, including those with high-performance and certified buildings. Historically, closing this gap involved managing vast amounts of building data manually, an inefficient process that often left teams overwhelmed and unable to extract actionable insights.
Artificial intelligence (AI) is now emerging as a key tool in bridging this divide. In 2016, DeepMind applied AI technology to the cooling systems of Google’s data centers, utilizing sensor data to predict thermal conditions proactively. This approach initially reduced cooling energy consumption by up to 40 percent. By 2018, AI was directly managing parts of the cooling system under human oversight, achieving average energy savings of around 30 percent.
Beyond environmental considerations, energy efficiency is increasingly being recognized as a critical operating strategy. Efficiency measures enhance resilience by permanently lowering a building’s baseline energy use, thereby shielding owners from future energy price fluctuations. This positions efficiency not only as a sustainability initiative but also as a financial hedge against cost volatility.
Within this context, the Gulf’s energy-producing nations, particularly the Kingdom, possess significant potential to lead in efficiency technologies and asset performance. Leveraging energy more intelligently is not seen as competing with traditional energy sectors but rather as complementing them by reducing operating costs, boosting asset productivity, and strengthening economic infrastructure.
In summary, as energy demand patterns transform and technologies advance, improving building energy performance through AI-driven efficiency presents a valuable path forward for the region’s energy sector and broader economy.