Guest Essay
The impact of artificial intelligence (A.I.) is shifting from a stock market focus to a broader economic concern centered on debt. Robin Wigglesworth examines how the reliance on credit to finance A.I. developments could have significant repercussions.
Recent highlights such as Nvidia’s valuation exceeding $5 trillion and the anticipated public offerings of SpaceX, Anthropic, and OpenAI have captivated market attention. However, the underlying issue now revolves around the substantial debts financing these technological advancements. History shows that investment crazes fueled by debt often precipitate economic downturns, even if the technology transforms industries. The 19th-century railway expansion, the 20th-century telecommunications boom, and the 21st-century housing surge serve as stark reminders.
Understanding why debt has become integral to A.I. reveals shifts in investment strategies. Previously, cash-rich companies like Facebook or Google could fund data centers and infrastructure through internal revenues. Currently, developing large-scale A.I. models demands extensive computing power, leading companies, known as “hyperscalers,” to rely on loans, bonds, and other financial instruments.
The magnitude of debt accumulation is unprecedented. A Barclays conference on A.I. data centers described the market as “a rocket ride without seatbelts” and “bonkers.” In 2025, American A.I. firms secured $217 billion through debt markets, and by mid-2026 eclipsed that with $445 billion issued, estimated to reach $600 billion by year’s end according to Morgan Stanley. This sum surpasses the combined 2026 budgets of the U.S. Departments of Justice, Transportation, and Education.
Acknowledging this trend is essential. We must question how A.I.’s reliance on debt may shape the economic landscape amid the technology’s revolutionary potential.