The world is about to enter a new industrial period in which AI data will be the primary growth driver, surpassing oil. According to a recent analysis from the International Energy Agency (IEA), global investment in AI data centres is predicted to reach $580 billion in 2025, exceeding the $540 billion that would be spent on finding new oil supplies.
This achievement signifies a significant change in the way economies generate and maintain value.AI data centres have become the new backbone of the global economy as digital services, cloud computing, and artificial intelligence (AI) become critical to productivity and national competitiveness.
According to the IEA’s most recent report, “the comparison provides a telling marker of the changing nature of modern, highly digitalised economies,” highlighting how global investment is moving away from fossil fuels and towards computing infrastructure.
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AI Data Centres: The Engine of the Digital Revolution
AI Data centres, which were formerly thought of as simple digital information storage facilities, have developed into intricate ecosystems that fuel the most sophisticated AI systems in the world. Almost every significant technological advancement, from autonomous systems and real-time cloud analytics to gigantic language models like ChatGPT, depends on the enormous processing power contained within these facilities.
According to the IEA analysis, AI data centres’ electricity usage is expected to increase fivefold by 2030, potentially doubling the amount of energy currently used by all data centres worldwide. The tremendous computational needs of AI model deployment and training, which frequently call for thousands of high-performance GPUs as well as constant cooling and power systems, are reflected in this rise.
Although at a slower rate than AI-specific facilities, traditional or “conventional” AI data centres, which manage cloud storage, enterprise computing, and internet infrastructure, will also witness an increase in energy use.
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The United States Takes the Lead
Nearly half of the increase in demand for AI data centres worldwide is anticipated to come from the United States, with the majority of the remaining demand coming from Europe and China. Massive expenditures from hyperscale cloud providers like Amazon Web Services, Google Cloud, Microsoft Azure, and Meta, as well as recent entrants concentrating on AI training infrastructure, are largely responsible for the U.S. dominance.
The majority of new AI data centres, according to the IEA, are being constructed in urban areas with a population of more than a million, frequently forming clusters around established technology hubs like Northern Virginia, Dallas, Dublin, Frankfurt, and Beijing.
The enormous magnitude of the AI infrastructure boom is demonstrated by the fact that half of the planned facilities will have capacities greater than 200 megawatts, or nearly enough to power 150,000 households. In addition to being technological wonders, these megacenters are vital strategic assets that have an impact on everything from national energy systems to local labour markets.
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The Growing Challenge: Energy and Grid Constraints
AI Data centre expansion is not without challenges, though. The IEA cautions that the current electrical infrastructure is being strained by the quick construction of large-scale facilities, especially in crowded urban areas.
According to the organisation, “connection queues and grid congestion are increasing in many regions.” “Connection requests for new AI data centres are already backed up for years in several major markets.”
In the United States and several regions of Europe, utility companies are finding it difficult to meet the increased demand for high-voltage connections and a steady supply of electricity, which makes the congestion especially noticeable. The delays run the risk of raising the cost of electricity for other industries in addition to slowing down new buildings.
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Supply Chain Bottlenecks Slow Progress
Global supply chain constraints are another major obstacle to the expansion of AI data centres, according to the paper. The scarcity of parts like electrical transformers, gas turbines, essential minerals, and high-voltage cables is impeding both new construction and grid improvement initiatives.
Geopolitical conflicts that impact the sourcing of commodities like copper, lithium, and rare earth elements, as well as post-pandemic supply imbalances and growing demand for renewable infrastructure, have all contributed to the shortages.
Many technology and energy companies are using innovation to solve these problems. Solid-state transformers (SSTs), next-generation devices intended to increase grid efficiency and flexibility, are being developed by companies such as Amperesand and Heron Power. SSTs can facilitate the more seamless integration of renewable energy sources while offering a quicker reaction to grid instability, which is essential for AI data centres that need constant power.
The IEA points out that expanding production to global levels would take a lot longer, and broad deployment of these technologies is still at least a year or two away.
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The Energy Equation: How AI Data Centres Will Power Up
An equally urgent challenge is raised by the sharp increase in computational demand: Where will all the electricity come from?
According to IEA projections, most new data centres will run mostly on renewable energy by 2035, with the help of natural gas and advanced nuclear technology. Both economic reasoning and mounting environmental pressure on tech companies to lower their carbon footprints are reflected in this trend.
Solar Energy Leads the Way
Solar energy is becoming the most promising renewable energy source because of its scalability and quickly decreasing costs. To reduce their operational emissions, major tech corporations are already making significant investments in solar farms.
For instance, Google recently declared that by 2030, all of its offices and data centres will run entirely on carbon-free energy, while Amazon has committed to being the biggest corporate purchaser of renewable energy worldwide.
Natural Gas and Small Modular Reactors (SMRs)
Natural gas, which provides dependable baseload electricity to supplement sporadic renewables, will continue to play a significant transitional role. According to IEA estimates, natural gas will provide 220 terawatt-hours of power for data centres by 2035, compared to 400 terawatt-hours from renewable sources.
Small modular nuclear reactors (SMRs), which are smaller, factory-built reactors that might supply big data clusters with continuous, localised energy, are another emerging possibility. According to the paper, SMRs might add 190 terawatt-hours of low-carbon power to the data centre ecosystem if they are successfully commercialised.
Environmental and Policy Implications
Policymakers, energy planners, and environmental advocates face difficult dilemmas as AI-driven infrastructure grows. Data centres are essential for economic expansion and innovation, but they also consume a lot of electricity, water, and rare materials.
Expansion and sustainability must be balanced. Because of worries about power shortages and carbon emissions, nations like the Netherlands and Ireland have already implemented temporary moratoriums on new data centre licenses. To make sure that new developments are in line with more general climate goals, a number of U.S. states are updating their environmental and zoning regulations.
Conversely, the growth of data centres is also spurring significant investments in grid modernisation and renewable energy, which is speeding up the overall energy transformation. According to the IEA, digital infrastructure has been a key driver of the nearly twofold increase in worldwide investment on clean energy since 2020.
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A New Energy Hierarchy: Data Over Oil
Oil served as the cornerstone of world economic dominance for more than a century. However, the equilibrium has drastically changed in 2025. Investment patterns increasingly favour information-processing technologies over hydrocarbon extraction technologies.
This symbolic shift is highlighted by TechCrunch’s analysis of the IEA data: $580 billion invested in data centres against $540 billion for new oil output. This is the beginning of a new economic paradigm, not just a financial statistic.
Data has emerged as the new resource that drives industry, innovation, and even geopolitical power as countries vie for digital supremacy. From decentralised edge servers to hyperscale AI clusters, the physical infrastructure that supports it is rapidly evolving into the contemporary equivalent of refineries and oil fields.
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Conclusion: Powering the AI-Driven Future
The race to build next-generation AI data centres is changing corporate priorities, the energy landscape, and the global economy. The boundaries of global dominance are changing as investment flows move from oil rigs to server racks.
How well governments, businesses, and energy providers can strike a balance between innovation and sustainability will be determined over the course of the next ten years. The data centres of the future will determine not only the digital economy but also the course of global development, regardless of whether they are fuelled by solar energy, nuclear fusion, or smart grids.
The world’s shift from oil to artificial intelligence (AI) is a turning point in history, marking the end of the extraction era and the beginning of the intelligence era. Additionally, the real indicator of progress in this new period will be bytes of AI data rather than barrels of oil.