IEA’s New Energy and AI Observatory to Monitor AI’s Impact on Global Energy Systems

As the rise of AI increases demand for data centres, it places significant pressure on energy systems while also enabling new efficiencies. The International Energy Agency (IEA) has launched a new Energy and AI Observatory, aiming to analyse the growing interconnections between the AI and energy systems and address the challenges. 

The platform is equipped with tools to understand datasets on data centre electricity consumption and digital infrastructure by region. 

“Building on our recent major report on this subject, this new Energy and AI Observatory, developed in consultation with a wide range of partners, underscores our commitment to supporting decision makers around the world as they plan for the future. Reliable data and analysis are the cornerstone of navigating this fast-moving space,” Fatih Birol, executive director of the IEA, said.

The observatory was initially announced in February at the AI Action Summit. In April, an IEA publication titled Energy and AI highlighted that electricity demand from AI-optimised data centres is projected to more than quadruple by 2030. Given the uncertainty around how this demand will evolve, the report calls for a scenario-based approach to guide timelines and decisions across the energy sector.

Currently, 20 case studies in the observatory feature how AI is deployed across the energy sector. They explore a wide spectrum of AI applications, from optimising heating and cooling systems to improving industrial gas use, increasing waste heat recovery, and enhancing grid and renewable energy efficiency.

One of them concerns the Infosys-owned and operated smart campus in Pune. Even before adopting AI, the campus had an energy performance index (EPI) of 70, far below the Indian benchmark of 180 for energy-efficient buildings. With AI and machine learning, Infosys further optimised operations by predicting demand and automating energy use. In six months, energy efficiency improved by 7%, on-site generation rose by 5%, and carbon emissions fell by 7,900 tonnes.

These case studies signal how AI can help balance rising energy demand with sustainability, making the observatory a key tool for future energy planning.