Rising energy costs amid geopolitical tensions are not only impacting fuel prices but also threatening global industries, including the rapidly growing AI sector.
Although driving up US petrol prices may be Donald Trump’s top priority when he demands that Iran reopen the Strait of Hormuz, if the situation continues, rising energy costs will be felt well beyond the gas pump.
Global Energy Shock and Economic Ripple Effects
Fractured supply chains and systemically higher power prices will put pressure on global consumers and industries. Threatening the precarious economics of the AI boom could be one outcome for the United States.
Many economies that rely on oil imports, particularly those in the global south, are facing severe shortages of oil and its byproducts. The Philippines has declared a national energy emergency, Indonesia has mandated work from home Fridays, and shops in Egypt are subject to curfews.
Impact on Global Economies
⚡ Global Energy Crisis Impact
- Oil Shortages: Global South economies hit
- Philippines: Energy emergency declared
- Indonesia: Work-from-home Fridays
- Egypt: Curfews imposed on shops
- Main Cause: Strait of Hormuz disruption
- Impact: Inflation & supply chain stress
The US can mostly avoid these issues because it is a wealthy energy exporter. It cannot, however, totally prevent the global increase in energy costs, which many analysts now predict will last for months even if the strait reopens in a few days, as the escalating cost of filling up US cars demonstrates.
Many businesses will therefore be cautiously examining their cash flow forecasts. However, the difficulties can be more severe for an industry that is extremely energy-hungry, whose business model is still in the early stages of development, and whose investments are supported by large debts.
AI Industry Under Pressure
In an attempt to allay concerns about AI’s potential effects on the environment in the lead-up to what is anticipated to be a massive launch on the stock market later this year, OpenAI’s Sam Altman offered an unsettling analogy in February.
He stated, “People speak about how much energy it takes to train an AI model, but it also takes a lot of energy to train a human.” “It takes around 20 years of life, including all the stuff you eat during that period, to become intelligent.”
Energy Costs vs AI Growth
🤖 AI Boom Financial Risks
- Revenue: ~$60 billion
- Capex: ~$400 billion
- Debt Exposure: High borrowing
- Key Risk: Rising energy costs
- Infrastructure: Datacenter expansion
- Threat: Profitability pressure
In its routine assessment of the risks facing the UK financial system last week, the Bank of England brought attention to the possible connection between energy prices and the share prices of AI businesses.
The Bank’s financial policy committee started off by pointing out that before to Trump’s war, investors had already expressed concerns about the industry. “Prior to the war, selling pressure resulted from growing debt-financing needs and worries about whether promised returns on very big AI-related investments would materialize,” the report stated.
Financial System Risks and Warnings
“Given the energy-intensive nature of the supply chain for essential components and the operation of datacenters, the conflict could exacerbate these concerns.”
It was part of a broader warning that, given the likelihood that it will “impact on economy, boost inflation and tighten financial conditions,” the Iran war could worsen already-existing market vulnerabilities.
Global Trade and Investment Concerns
Robert Staiger, the World Trade Organization’s senior economist, has also linked AI to the conflict’s effects. He told me last month that a protracted period of high energy prices could “crimp” investment in the industry. He remarked, “The boom is incredibly energy consuming.”
In its most recent global trade outlook, the WTO determined that 70% of investment growth in the US during the first three quarters of last year was in AI-related items of some kind, highlighting the practical ramifications of a potential retrenchment.
Complex Financing and Hidden Risks
A forensic note by the US law firm Quinn Emanuel, which was released last month, began by pointing out that the sector’s revenues last year were approximately $60 billion (£45.3 billion) and its capital expenditures were $400 billion, exposing the sheer complexity of the financial engineering underlying the AI investment mega-boom.
It is depressing reading for those of us who are old enough to recall the global financial crisis of 2008; asset-backed securities and off-balance sheet special purpose companies are prominent.
Debt Structure and Market Vulnerability
In essence, infrastructure companies like CoreWeave and the “hyperscalers” spearheading the AI movement are borrowing unfathomably vast sums of money in an attempt to build out datacenters (though recent study by AI skeptic Ed Zitron reveals real-world initiatives lag well behind the promises).
Since the lenders are frequently private businesses like asset managers, it is more difficult for regulators or even investors to keep track of each company’s overall liabilities.
Regulators, particularly the Bank of England, have repeatedly cautioned about the operations of this expanding private lending sector, pointing out their opacity. These concerns are distinct but related.
Tech businesses have issued bonds directly in certain instances. However, much more bizarre arrangements—familiar from the period leading up to the Great Crash—are at work.
Operators of data centers have begun establishing off-balance sheet special purpose companies that borrow against the enormous data centers and their prospective rental income. These debts are sometimes combined, divided, and sold to investment managers and pension funds.
These kinds of systems might give the impression that risks are being distributed rather than accumulated, as older readers may remember, and they make it extremely difficult to determine precisely who is responsible for what.
Analysts at Quinn Emanuel estimate that in the last two years, over $120 billion in datacenter debt has been transferred off the balance sheet. Additionally, “the extensively integrated AI ecosystem means that crisis at any single node… can cascade across several counterparties and finance tiers,” as they put it.
Future Risks and Market Outlook
Long-term increases in energy prices could theoretically be one cause of this “distress,” but forecasts of erratic interest rates and decreased consumer demand—both expected outcomes of the Middle East conflict—are also unlikely to be helpful.
However, given the financial trickery at play, even slightly higher energy costs may undoubtedly cause a reconsideration that might spread throughout US markets and beyond. Is this another way that Trump’s careless assault on Iran has unleashed forces beyond his control?
Frequently Asked Questions
1. What worries Donald Trump regarding the Strait of Hormuz?
Trump is worried about how rising oil prices would impact the price of gasoline in the US. The Strait of Hormuz’s disruptions limit the flow of oil around the world, raising energy costs and affecting economic stability.
2. What impact do rising energy prices have on the world economy?
Increased manufacturing and transportation costs, supply chain disruptions, lower consumer spending, and pressure on developing countries are all consequences of rising energy prices, which may lead to shortages, inflation, and slower global economic growth.
3. What makes the AI sector especially susceptible?
AI demands enormous amounts of energy for computation and data centers. According to Sam Altman, growing energy costs have the potential to drastically raise operating costs and jeopardize the profitability of AI investments.
4. What issues has the Bank of England brought up?
The Bank cautioned that rising energy prices and geopolitical unrest could lower the returns on AI investments, raise debt risks, and reveal weaknesses in financial markets associated with significant borrowing by the AI sector.
5. How might the AI industry’s financial concerns proliferate?
Asset-backed securities and off-balance-sheet vehicles are examples of complex financing that can mask hazards. Interconnected loans may cause broader instability among lenders, investors, and international financial institutions if one company has difficulties.
Conclusion
Long-term energy shocks could impede the development of AI, put pressure on international economies, and reveal weak financial systems, demonstrating how geopolitical conflict may have an impact on technology markets and global economic stability.
Disclaimer: This content is for informational purposes only and does not constitute financial or investment advice.
