The Iran-Israel-US war comes at a time when artificial intelligence is emerging as one of the biggest energy consumers of the decade. As AI spreads across every sector of human activity, the global race to scale it collides with a highly volatile force: geopolitics. This convergence exposes how dependent technology is on physical resources.
Gas-fired power stations are the largest source of power for U.S. data centers, data from the International Energy Agency (IEA) shows. Reuters reported that Dominion Energy’s power generation fleet, which supplies power to the “data center alley” in Northern Virginia, was 44% dependent on natural gas in 2024. As energy markets tighten and wealthier nations and big tech companies get long term access to more energy, through renewable capacity and long-term contracts, the constraints become sharper for developing economies which would lead to higher electricity costs, limited grid capacity and reduced access to advanced computing infrastructure.
This clearly shows a situation of energy-backed AI divide. The ability to build and scale intelligence is directly proportional to access to affordable and reliable power. What was once a digital gap in the internet era could evolve to structural inequality. Poorer nations are already facing the risk of falling behind the AI adoption as they are lacking the infrastructure and investments to manage AI’s disruptive effects on economy and labor markets. AI, despite being “digital,” is deeply physical: it runs on electricity, infrastructure, rare minerals, and capital. When energy becomes scarce or expensive, the consequences ripple unevenly. Over time, this rebalancing may reshape the AI value chain, concentrating control not just over technology, but over the economics of intelligence itself.
UNCTAD data suggests that Strait of Hormuz disruption could lead to falling stock prices, weakening currencies, and rising cost of external debt for developing countries. This will reduce the investable surplus for global investors.
Global uncertainty linked to the crisis is pushing capital toward safer bets such as US Dollar, defensive stocks, and reducing flow into emerging markets. Expansion plans into Gulf markets, once seen as a natural growth corridor for tech startups, are also facing operational challenges as geopolitical instability is affecting investor sentiment.
There is a deeper shift underway. EY report shows that between January and September 2025, Sovereign wealth funds were involved in AI venture transactions totaling $46 billion. Sovereign wealth funds in West Asia, among the most active investors in global technology, may temporarily redirect capital toward energy security and defense. These funds have made significant global investments in technology and AI, positioning these sectors as key pillars in their efforts to diversify their economies away from oil. For startups reliant on long-term funding, this reallocation could tighten liquidity just as AI infra and development costs are rising due to the geopolitical tensions.
The current developments point out the convergence of multiple stress points. Energy markets are shifting; supply chains are tightening, changing investor sentiments and shifting capital flows. AI is exposed to all these factors and unlike the earlier tech developments, AI is energy hungry, requires new tech infrastructure, and each of these factors is being tested by the unfolding crisis.
Disruptions in Qatar’s gas ecosystem are fuelling concerns over helium supply—a vital input for semiconductor manufacturing and advanced cooling technologies. Meanwhile, tensions around the Strait of Hormuz are likely to drive energy costs for chipmakers worldwide.
Training and cooling large AI models require electricity and water. Running them, 24/7,365 days requires constant power which is sourced from fossil fuels, particularly in energy stressed developing nations. In a report by London School of Economics, published in 2025, Data centers contribute about 1% of global energy-related greenhouse gas emissions and are among the fastest-growing sources of emissions. By 2035, increased data center energy use could lead to an additional 0.4–1.6 gigatonnes of CO2 equivalent (GtCO2e) emissions. With rising geopolitical tensions, this may lead to higher dependence on fossil fuels such as coal, which is carbon intensive.
In times of geopolitical issues, rising AI investments could lead to multi-sectoral economic impact. It can drive up energy consumption, strain supply chains, complicate sustainability goals, and widen inequalities in access to resources. The current situation points to the reality that Artificial intelligence is as much an energy and industrial narrative as it is a technological one.
Published on April 13, 2026
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