A leading economist is sounding the alarm about the potential economic ripple effects of massive AI infrastructure spending by tech giants. Torsten Sløk, chief economist at Apollo Global Management, has warned that the debt-fueled capital expenditure by AI hyperscalers could significantly impact interest rates throughout 2026 and beyond.
The core issue centers on bond market dynamics. Major tech companies including Alphabet, Amazon, Meta, Microsoft, and Oracle collectively issued $100 billion in bonds during 2025—more than double their 2024 issuance according to Bank of America. These companies are racing to fund the construction of data centers and AI infrastructure necessary to support their artificial intelligence ambitions.
Sløk projects that AI hyperscalers will be major drivers of investment-grade (IG) bond issuance in 2026, with Wall Street banks forecasting total issuance between $1.6 trillion and $2.25 trillion for the year. This flood of new corporate debt entering the market could create significant pressure on interest rates across multiple sectors.
The economist’s primary concern is about market displacement. As more corporate bonds hit the market, investors will need to redirect capital from other fixed-income investments. “The significant increase in hyperscaler issuance raises questions about who will be the marginal buyer of IG paper,” Sløk wrote, questioning whether this will pull investment away from Treasury bonds or mortgage-backed securities.
If investors shift from Treasury purchases to corporate bonds, it could push Treasury yields higher, effectively raising the baseline interest rate across the economy. Alternatively, if capital flows away from mortgage markets, it could widen mortgage spreads and make home loans more expensive for consumers.
Sløk isn’t alone in his concerns. Mark Zandi, chief economist at Moody’s Analytics, has drawn parallels to the dot-com era, noting that current tech sector borrowing has eclipsed levels seen during that bubble. Zandi warned that if the tech sector’s growth trajectory stalls, the economic consequences could be severe.
The bottom line, according to Sløk, is clear: “The volume of fixed-income products coming to market this year is significant and is likely to put upward pressure on rates and credit spreads as we go through 2026.” Investors need to carefully assess how the AI buildout will be financed and what broader economic implications this massive capital reallocation might trigger.
Key Quotes
The significant increase in hyperscaler issuance raises questions about who will be the marginal buyer of IG paper. Will it come from Treasury purchases and hence put upward pressure on the level of rates? Or might it come from mortgage purchases, putting upward pressure on mortgage spreads?
Torsten Sløk, chief economist at Apollo Global Management, articulated the core concern about how massive AI infrastructure bond issuance could disrupt other fixed-income markets, potentially driving up costs for government borrowing or home mortgages.
The bottom line is that the volume of fixed-income products coming to market this year is significant and is likely to put upward pressure on rates and credit spreads as we go through 2026.
Sløk’s summary assessment emphasizes that regardless of which markets are affected, the sheer volume of corporate debt issuance to fund AI infrastructure will likely make borrowing more expensive across the economy throughout 2026.
Our Take
This warning represents a sobering reality check for the AI industry’s infrastructure ambitions. The parallel to the dot-com era is particularly instructive—during that period, massive capital investment in telecommunications and internet infrastructure preceded a painful market correction when growth expectations weren’t immediately met. While AI’s potential is real, the question of whether current infrastructure spending is appropriately scaled to near-term revenue opportunities remains open. The macroeconomic spillover effects add another dimension of risk. If AI capex spending drives up interest rates broadly, it could create a self-limiting cycle where higher borrowing costs slow economic growth, reducing demand for AI services and making it harder for companies to justify their infrastructure investments. Investors and policymakers should monitor not just AI technology development, but also these financial market dynamics that could ultimately determine the pace and sustainability of AI adoption.
Why This Matters
This analysis highlights a critical but often overlooked aspect of the AI boom: its potential to reshape broader financial markets and economic conditions. While much attention focuses on AI’s technological capabilities and competitive dynamics, the infrastructure required to support AI development demands unprecedented capital investment that could have far-reaching consequences.
The scale of borrowing is staggering—doubling year-over-year and potentially reaching over $2 trillion in 2026. This represents one of the largest corporate capital expenditure cycles in modern history, comparable to or exceeding the dot-com era buildout. If these investments drive up interest rates broadly, it could affect everything from mortgage costs to government borrowing expenses, potentially slowing economic growth.
For businesses and investors, this creates a complex risk-reward scenario. Higher interest rates could dampen economic activity and make other investments less attractive, while simultaneously questioning the sustainability of AI infrastructure spending. The comparison to the dot-com bubble serves as a cautionary tale—if AI growth disappoints or takes longer to materialize than expected, companies could be left with massive debt burdens and underutilized infrastructure. This story underscores that AI’s impact extends far beyond technology into fundamental economic structures.