AI and the global energy system: the new IEA report reveals the energy scenarios of the next decade

Image source: IEA

A new report from the International Energy Agency (IEA) sheds light on one of the most significant and under-recognized transformations in the global energy landscape: the growing impact of artificial intelligence.

While AI represents an extraordinary lever to optimize consumption, reduce emissions and innovate the supply chain, on the other hand it opens up complex scenarios linked to the increase in electricity demand, particularly from data centers. The study, the result of in-depth research based on up-to-date data, invites governments, companies and experts to a strategic reflection on how to address this epochal transition.

Data Centers and AI: An Unprecedented Acceleration in Electricity Consumption

The document “Energy and AI” , published by the IEA, offers a global analysis of the connections between the development of artificial intelligence and energy dynamics. According to the scenario outlined, by 2030 the global demand for electricity from data centers could more than double, exceeding 945 TWh – a volume comparable to the total consumption of an industrialized country like Japan.

This growth is largely fueled by AI-optimized processing systems , which are increasingly widespread in advanced economic sectors. In the United States, for example, it is estimated that almost half of the increase in electricity demand in the coming years will be linked to artificial intelligence, even exceeding the aggregate consumption of energy-intensive manufacturing sectors.

The phenomenon is not limited to the American market: countries such as Japan and Malaysia are also expected to see a significant impact from data centers on the increase in energy demand. This dynamic, according to the IEA, could put pressure on current electricity infrastructures and generate new needs in terms of energy production and distribution, making significant investments in production capacity, smart grids and low-emission sources indispensable.

Efficiency, safety and sustainability: strategic levers for an AI at the service of energy

In addition to outlining a realistic picture of the increase in consumption, the IEA report highlights the dual role of artificial intelligence in the energy context : on the one hand, a possible threat to the balance of networks and cybersecurity; on the other, a precious ally to improve operational efficiency, reduce costs and accelerate decarbonization.

Over the past four years, cyberattacks on energy utilities have tripled , often aided by advanced AI tools. At the same time, the same technology is now being used to identify vulnerabilities, optimize predictive maintenance of plants, and prevent blackouts.
Another key issue is the supply of raw materials , such as rare earth minerals needed to build servers and AI-related devices. The IEA provides detailed estimates of data center demand for these resources for the first time, highlighting how the concentration of supplies globally could become a critical factor for energy security.

While increased consumption may lead to higher emissions, the report suggests that these effects could be partly offset by the adoption of intelligent solutions that optimize resource use and accelerate the transition to renewables. In particular, AI is seen as a catalyst for innovation in key areas such as high-performance batteries and advanced photovoltaics.