The Economics of AI: Understanding Price Insensitivity in Infrastructure Investment

In the latest episode of Thoughts on the Market, Andrew Sheets, Global Head of Fixed Income Research at Morgan Stanley, explores the concept of elasticity—a foundational economic principle—and applies it to the current, explosive growth of Artificial Intelligence infrastructure.

Defining the Inelastic Nature of AI

Sheets introduces the concept of inelasticity to describe goods for which demand remains stable even when prices rise significantly. While consumers might switch from pizza to burgers if the price of the former increases, they are likely to pay for essential services like electricity regardless of cost. Sheets argues that the current AI build-out is exhibiting this exact behavior.

The Surge in Infrastructure Costs

Despite the massive increase in the prices of necessary components, demand for AI-related infrastructure continues to accelerate. Sheets highlights several striking statistics:

• Copper, essential for wiring data centers, has seen prices rise by about 40% in the last year.
• Gas turbines, required to power these facilities, are up 50%.
• Memory components have surged between 150% and 300% over the past year alone.

Despite these "extremely large price increases," the investment momentum remains unabated. Morgan Stanley estimates that large U.S. technology companies will spend roughly $800 billion this year—a figure that is expected to be "dwarfed" by an estimated $11 trillion in spending by 2027.

Why AI Spending Remains Price Insensitive

Sheets posits that this price insensitivity stems from the strategic importance companies place on AI. It is viewed as "maybe the most important technology in a decade." Because these companies possess the "financial resources and the patience to wait it out," they are willing to absorb higher costs and even higher debt costs to secure their position in the AI race, continuing to issue debt at a "record pace."

The Dual-Edged Sword of Inelasticity

The inelastic nature of the AI theme presents a "classic good news, bad news story" for the broader economy:

The Positive Outlook

• Resilient Growth: The unwavering commitment to this technology suggests that spending will not be "easily be shaken by outside events."
• Earnings Support: This massive capital expenditure acts as a buffer, supporting overall U.S. growth and corporate earnings, a perspective echoed by Morgan Stanley’s U.S. equity strategy team.

The Risks and Economic Implications

• Inflationary Pressures: The "robust demand" for AI components, even as prices soar, risks fueling inflation at a time when core measures are already "well above the Federal Reserve's target."
• Market Contagion: There is a concern that if AI-heavy companies remain insensitive to borrowing costs, it could drag other corporate costs "wider in sympathy," potentially impacting the broader U.S. corporate bond market.
• Uncertain Returns: Ultimately, Sheets notes that it "remains to be seen" what level of returns these historic investments will actually generate.

In summary, while the AI infrastructure boom is acting as a powerful engine for growth, its inelastic nature creates a complex economic environment characterized by rising costs, potential inflationary risks, and a significant degree of uncertainty regarding long-term financial outcomes.