The economic fallout from the rapid spread of artificial intelligence extends beyond the technology sector to electricity grids, vital metals markets, supply chains, government and corporate debt, in a growing interdependence that raises questions about the global economy’s ability to absorb the cost of this boom.
And according to an analysis published by Reuters, promises of smarter and less expensive technologies are hiding a huge infrastructure that needs investments, energy and raw materials, while reliance on borrowing to finance data centers and projects related to artificial intelligence is expanding.
Artificial Intelligence Raises Hidden Demand for Electricity
Financial and market writer Mike Dolan highlighted a graph by the Pew Research Center showing the growing share of text content published online that is produced with the help of artificial intelligence technologies.
The breadth of automated content reveals how quickly these technologies are reshaping the digital environment, but at the same time it raises questions about the energy needed to power the models, platforms, and data centers behind this production.
Every expansion of AI requires greater computing power, which means increased electricity consumption and the need to create new data centers, transmission networks, and power plants.
But estimates of future energy demand could be inflated, energy writer Ron Bosso said, drawing on findings by journalist Leila Kearney about U.S. data centers waiting to be connected to power grids.
The results suggest that a large number of these centers are either not actually operational or remain merely a paper-recorded project, which has spawned a phenomenon dubbed “ghost data centers.”
Calculating these installations within the projected demand could inflate electricity consumption estimates, and prompt energy companies and investors to channel huge funds to build generation capacity and grids that may not be required at the projected size.
Bio-mineral race pushes up liability standards
The demands of artificial intelligence and digital transformation are not limited to electricity, but extend to the bio-metals used in semiconductors, batteries, power grids, and high-tech equipment.
And metals market specialist Andy Home pointed to a report by Chatham House, which called for ensuring responsible extraction of vital minerals as global competition for control of their resources and supply chains intensifies.
The reading warns that the international race to acquire these minerals has pushed environmental, social and governance standards to a late stage, in exchange for prioritizing increased production and securing supplies.
But pressure from governments and local communities on mining companies is increasing, with the number of reports of human rights violations in the sector increasing by 73 percent in 2025.
This increase points to a rise in popular opposition to obscure or dangerous practices in the mining sector, and to the fact that the provision of minerals necessary for technological transformation will not be acceptable if it comes at the expense of the environment and the rights of the population and workers.
Governments and businesses are therefore faced with the difficult equation of securing the necessary raw materials for technology and clean energy, while maintaining standards of transparency, governance and protection of communities affected by extraction processes.
Can the Chinese experience be repeated?
Global Energy Transition writer Gavin McGuire addressed elements other countries could draw on China’s experience to transition to cleaner energy sources.
And China has invested extensively in renewable energy, electric vehicles, batteries, infrastructure and associated industrial networks, giving it an advanced position in a number of energy transition technologies.
But shifting China's experience to other economies does not guarantee the same results, owing to the different size of markets, the state's financing capabilities, the industrial structure, the resources available, and the nature of governance and decision-making systems.
And so countries seeking to adopt elements of the Chinese model should consider the potential costs and benefits, and not treat it as a ready model for all economies.
Strait of Hormuz redraws energy routes
Asian commodities and energy market specialist Clyde Russell discussed potential routes for transporting oil and gas supplies from the Middle East, as the crisis surrounding the Strait of Hormuz continues and risks to global supply chains escalate.
Strait-related disruptions are prompting producer nations and consumers to consider alternative routes for transporting oil and gas, with the goal of reducing dependence on a single sea corridor critical to global markets.
However, the development of alternative routes requires significant investments in pipelines, ports, storage and transportation facilities, and cannot be accomplished as a quick solution to an emergency crisis.
The Hormuz crisis shows that energy security does not depend on the volume of resources alone, but also requires diversifying export routes, building strategic reserves, and strengthening the capacity of supply chains to withstand geopolitical shocks.
Trade Restrictions and Supply Chains
And in another topic, editor Anna Zemanski reviewed a dialog between Peter Thal Larsen, global editor at Reuters Breaking Views, and journalist and writer Ed Conway, about the impact of bottlenecks and trade restrictions on the movement of the global economy.
These include U.S. tariffs and Chinese restrictions on exports of rare earth minerals, which are involved in the manufacture of many technological and military products and renewable energy equipment.
Through these tools, governments seek to protect their industries, pressure their competitors, or ensure the retention of strategic resources, but attempts to restrict international exchange of goods and resources often have difficulty achieving lasting results.
Trade restrictions may lead companies to seek out alternative suppliers, routes, and markets, and may lead to higher prices, slower production, and reshape supply chains rather than stop them altogether.
Debt wave behind AI boom
Along with the growing demand for electricity and minerals, borrowing dedicated to funding AI infrastructure is expanding.
Market specialist writer Jamie McGeever argues that companies are raising increasing amounts of debt markets to build data centers, develop chips, and expand computing capabilities and associated power grids.
The expansion raises questions about the impact of issuing more corporate debt in financial markets, particularly U.S. Treasury yields, at a time when the U.S. government, in turn, continues to increase borrowing.
Rebecca Patterson and Sebastian Malaby, of the Council on Foreign Relations, discussed with Torsten Sloak, a partner and chief economist at Apollo, the potential risks to markets and the broader state of U.S. public finances.
The central question is whether the wave of AI funding via debt may turn into a systemic risk to markets, or whether concerns about its outcomes are overblown.
The answer depends on the ability of new investments to generate sufficient revenues and profits to service the debt. If AI technologies raise productivity and generate strong returns, financial commitments may become manageable, but if expectations about demand and returns are exaggerated, companies may face expensive assets and debt that are difficult to repay.
Related risks to the global economy
These developments reveal that the AI boom is not a separate technological shift, but part of a global equation that combines technology, energy, raw materials, trade, and finance.
Data centers need electricity, increased energy production and advanced technologies need vital minerals, and securing these resources fuels commercial and geopolitical competition, while a large part of new infrastructure is financed by borrowing.
Hence, the risks lie not in one sector, but in the transmission of shocks between sectors; Amplifying electricity demand expectations could lead to unnecessary investments, while restrictions on vital minerals could disrupt projects and raise their cost, and excessive borrowing could lead to financial pressures if expected returns are not realized.
This equation puts governments and businesses on the balancing act of accelerating investment in artificial intelligence, ensuring energy security and supply chains, protecting environmental and social standards, and preventing the accumulation of debt that could become a burden on the global economy.
And so the boom in artificial intelligence will shift from a technical race to a comprehensive economic test, the result of which will be linked to the ability of countries and markets to manage real energy demand, regulate mineral extraction, diversify supplies, and direct borrowing towards productive and sustainable investments.
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