Surging Investments in Data Centres
Global investment in data centres has surged, nearly doubling since 2022. In 2024, these investments are expected to reach half a trillion dollars, raising concerns about escalating electricity demands. Data centres alone accounted for about 1.5% of global electricity consumption in 2024, totaling approximately 415 terawatt-hours (TWh). The growth of these facilities, which has been increasing by around 12% annually since 2017, far exceeds the growth of overall electricity demand.
The United States leads in data centre electricity consumption, accounting for 45%, followed by China with 25%, and Europe with 15%. A significant portion of the US’s data centre capacity is concentrated in just five regional clusters.
Looking ahead, the IEA predicts that global data centre electricity consumption will more than double by 2030, reaching roughly 945 TWh. To put this in perspective, this amount is slightly more than the total electricity consumption of Japan today.
AI: The Key Driver of Growth in Data Centres
AI is recognized as the “most important driver” behind the expected growth in data centre energy demands. The United States is projected to experience the largest increase, where data centres may account for nearly half of all electricity demand growth by 2030. By the end of the decade, US data centres are forecast to consume more electricity than the combined energy usage of industries like aluminium, steel, cement, and chemicals.
The IEA’s « Base Case » predicts around 1,200 TWh of global data centre electricity consumption by 2035, although there is considerable uncertainty regarding this projection. Depending on AI adoption, efficiency improvements, and energy bottlenecks, estimates range from 700 TWh (« Headwinds Case ») to 1,700 TWh (« Lift-Off Case »).
The Energy Demand of AI
Fatih Birol, Executive Director of the IEA, emphasized that AI is one of the biggest stories in the energy sector today, but until now, policymakers and markets have lacked the necessary tools to understand its far-reaching impacts. In the US, data centres are on track to account for nearly half of the growth in electricity demand, while in Japan, they are expected to surpass half of the total demand increase, and in Malaysia, as much as one-fifth.
Meeting the Global Energy Demand for AI
Meeting the growing energy demand generated by AI requires a diversified energy portfolio. The IEA suggests that renewable energy sources and natural gas will play leading roles, with emerging technologies like small modular nuclear reactors (SMRs) and advanced geothermal power also contributing. It is projected that renewable energy, supported by storage and grid infrastructure, will meet half of the global growth in data centre energy demand through 2035.
Natural gas will be essential, particularly in the US, where it is expected to expand by 175 TWh to meet the needs of data centres by 2035. Similarly, nuclear power will play a significant role, especially in China, Japan, and the US, with the first SMRs anticipated around 2030.
However, simply increasing generation capacity will not be enough. The IEA stresses the need for infrastructure upgrades, particularly in the grid. Existing grids are already under strain, which may delay up to 20% of planned data centre projects worldwide due to lengthy connection queues and long lead times for crucial components such as transformers.
The Potential of AI to Optimize Energy Systems
Beyond its energy demands, AI holds significant potential to transform the energy sector itself. The IEA highlights several key applications of AI:
- Energy Supply: AI is already being used in the oil and gas industry to optimize exploration, production, maintenance, and safety, including reducing methane emissions. It also assists in the exploration of critical minerals.
- Electricity Sector: AI can enhance forecasting for variable renewable energy sources, reduce curtailment, improve grid balancing, and enable fault detection, reducing outage durations by 30-50%. It also has the potential to unlock significant transmission capacity without the need for additional infrastructure—potentially up to 175 GW.
- End Uses: In industries, AI adoption for process optimization could result in energy savings equivalent to Mexico’s total energy consumption. AI could also help optimize transport, saving energy equivalent to 120 million cars, though monitoring for rebound effects in autonomous vehicles is necessary. In buildings, the potential is significant but hampered by slower digitalization.
- Innovation: AI could significantly accelerate the discovery of new energy technologies, such as advanced battery chemistries, synthetic fuel catalysts, and carbon capture materials. However, the energy sector is currently underutilizing AI for innovation compared to other sectors like biomedicine.
Collaboration and Overcoming Barriers
Despite the promising potential, the full integration of AI into the energy sector faces several barriers, including data access and quality issues, insufficient digital infrastructure, a lack of AI talent in the energy sector, regulatory challenges, and cybersecurity concerns. Cybersecurity, in particular, is a double-edged sword—while AI can improve defense capabilities, it also provides attackers with advanced tools. Cyberattacks on utilities have increased significantly in recent years.
Supply chain security is also a critical concern, especially regarding critical minerals like gallium, used in advanced chips, where supply is highly concentrated.
The IEA concludes that deeper dialogue and collaboration between the technology sector, the energy industry, and policymakers is essential. Addressing grid integration challenges requires better data centre siting, exploring operational flexibility, and streamlining permitting processes.
Although AI presents opportunities for substantial emissions reductions through optimization, these gains are not guaranteed and could be offset by rebound effects. As Dr. Birol stated, “AI is a tool, potentially an incredibly powerful one, but it is up to us – our societies, governments, and companies – how we use it.”
The IEA will continue to provide the data, analysis, and forums for dialogue to help policymakers and other stakeholders navigate the path ahead as the energy sector shapes the future of AI, and AI shapes the future of energy.
