As artificial intelligence reshapes industries across the globe, its growing footprint in the energy sector is drawing serious attention. From supercharging smart grids to powering complex forecasting tools, AI is both a driver of energy innovation and ironically, a source of mounting energy consumption.
Now, the International Energy Agency (IEA) is stepping in with a bold new initiative: the Energy and AI Observatory. Launched to offer real-time data, analysis, and global insights, the Observatory aims to monitor how AI technologies are transforming and taxing the energy systems that support them.
AI’s relationship with energy is complex. On one hand, it’s enabling groundbreaking tools for sustainability, from predictive maintenance to climate modelling. On the other, the energy required to run AI models, particularly in sprawling data centres, is placing increasing strain on power grids around the world.
“There is no AI without energy,” the IEA notes. “At the same time, AI has the potential to transform the energy sector.”
The Observatory offers a data-rich lens into this dynamic interplay, tracking trends in data centre power use, AI application in energy systems, and emerging policy needs. Developed in collaboration with energy and technology partners, the platform provides a much-needed view into one of the fastest-evolving intersections in today’s economy.
The Observatory’s early findings paint a striking picture. Data centre capacity is growing at an unprecedented rate, with gigawatt-scale clusters emerging in North America, Europe, and the Asia-Pacific. These high-density installations, built to support increasingly powerful AI models, are now a key consideration in infrastructure and grid planning.
“AI is making data centres larger and more power-intensive,” the IEA warns. “Electricity generation capacity and grid strength are becoming pivotal factors in where these facilities are located.”
Despite the growing influence of data centres, reliable global statistics on their electricity consumption are still hard to come by. In response, the IEA has developed its own model to estimate regional energy demands, filling critical gaps in industry knowledge.
Beyond infrastructure challenges, the Observatory also highlights the positive potential of AI across 19 global case studies. These examples showcase AI’s role in optimising energy efficiency, improving price forecasts, and reducing operational costs.
One standout project comes from Hitachi Energy, where teams used advanced machine learning and probabilistic modelling to enhance energy market forecasting. The outcome: Nostradamus AI, a tool enabling users, even those without data science expertise, to generate precise energy pricing predictions.
The Observatory has drawn high-profile endorsements from some of the biggest names in tech and sustainability.
Christina Shim, Chief Sustainability Officer at IBM, applauded the initiative:
“I’m delighted that IBM contributed by sharing our work on the Electricity Access Forecasting AI model,” she said, referencing a collaborative project with the UNDP that uses IBM watsonx and IBM Cloud to predict electricity access across 102 Global South countries through 2030.
Kate Brandt, Google’s Chief Sustainability Officer, also praised the effort:
“The IEA’s Energy and AI Observatory creates a comprehensive reference, gathering crucial data and providing a global, informed vision on AI’s impact in the energy sector.”
As AI continues to expand its role in shaping the future of energy, the IEA’s Energy and AI Observatory is emerging as a crucial resource. By tracking how AI influences both demand and innovation, the Observatory helps policymakers, utilities, and tech companies alike navigate the challenges and opportunities of a rapidly transforming landscape.
In a world increasingly powered by data and algorithms, understanding the energy behind intelligence may be one of the most vital challenges of our time.