전문가들은 5% 국채 수익률이 AI 붐의 분수령이 될 수 있으며, 정부 부채 부담을 통해 버블의 종결자 역할을 할 수 있다고 경고한다.
Whether the artificial intelligence boom can sustain itself may no longer hinge on the technology sector alone, but rather on the mounting debt pressures facing the U.S. government. Rockefeller International Chairman Ruchir Sharma has advanced a striking thesis: unlike previous cycles, the current debt excess resides with the government, not corporations. Consequently, he identifies the 10-year Treasury yield as the single most critical indicator for timing the potential burst of the AI bubble. Sharma explicitly warns that once the 10-year yield “decisively breaks above 5%”—a level not clearly breached since the dot-com bubble era—it could signal the end of the AI expansion.
The 10-year Treasury yield has already climbed to approximately 4.8%, placing it just one step away from that pivotal threshold. In a recent analysis published in the Financial Times, Sharma notes that over the past three centuries, nearly every major financial bubble has collapsed following a sharp rise in borrowing costs for core enterprises. From the 19th-century railroad bubble to the major bubbles of the modern central-banking era, the recurring pattern has been consistent: companies borrow heavily to capitalize on emerging themes, economic growth and inflation subsequently push interest rates higher, and the bubble eventually bursts—after which governments typically intervene to absorb the debt and stimulate the economy.
This cycle, however, operates under a fundamentally different structure. Since the 2020s, the United States has sustained fiscal deficits averaging roughly 6% of GDP—more than double the historical average. Meanwhile, household and corporate leverage have not meaningfully increased over the long term. It was only in the past year that major technology firms, confronted with shrinking cash surpluses, began issuing debt to fund AI infrastructure expansion. Even so, given the sheer scale of these mega-cap companies, their current debt burdens remain entirely manageable.
U.S. public debt outstanding has surged to $40.05 trillion, crossing the $40 trillion milestone for the first time, while interest expenses reached $1.17 trillion in the current fiscal year. More alarming still, the 30-year Treasury yield has jumped to 5.32%, its highest reading since 2007. Public debt servicing costs have doubled over the past five years to exceed 3% of GDP—a U.S. record and the steepest increase and highest level among major developed economies. These fiscal strains, compounded by rising energy prices, have lifted global government bond yields and simultaneously increased financing costs for AI developers. Sharma maintains that the 10-year Treasury yield remains the paramount metric to monitor. A decisive break above 5% would indicate that the funding environment has shifted into a more restrictive regime, making it substantially more difficult for large-scale AI initiatives to secure capital.
The underlying mechanism is straightforward: major technology firms must now compete directly with the U.S. government for available capital. When government bond yields surpass 5%, the corresponding inflation-adjusted real return exceeds 2.5%, potentially forcing some corporations out of the bond market altogether. Current market pricing implicitly assumes that “AI investment is immune to macro interest rate constraints.” However, Sharma cautions that this assumption could trigger a violent narrative reversal the moment the 5% threshold is breached.
The AI sector currently faces a profound funding shortfall. According to Sharma’s estimates, AI applications generate approximately $200 billion in annual revenue, whereas corporate expenditures on data centers and related infrastructure have already surpassed $1 trillion. To bridge this massive divide, AI companies are increasingly reliant on fresh bond issuances and equity financing. Should the 10-year Treasury yield breach 5%, both of these critical funding channels would likely face simultaneous pressure.
The speed at which rates could climb adds another layer of risk. If the 10-year yield breaks above 5% before November, it would represent an increase of more than 75 basis points within a six-month window. Historically, such rapid tightening has coincided with the termination of bull markets. Furthermore, that level would exceed the earnings yield of U.S. equities, a metric that has historically acted as a significant headwind for stock valuations.
Some analysts contend that a 5% yield merely reflects a return to the interest-rate environment of the 1990s, when the 10-year Treasury consistently traded above 5% throughout the decade alongside robust U.S. equity performance. Sharma strongly disputes this parallel, noting that America’s reliance on debt in the 1990s was substantially lower than it is today; that decade actually concluded with federal budget surpluses. Today, public debt approaches 100% of GDP, and debt-servicing costs are markedly higher. As public borrowing costs rise, they will crowd out private borrowers more rapidly and deliver a sharper shock to the speculative AI market.
Sharma emphasizes that substantive excess borrowing in this cycle has accumulated almost exclusively on the government’s balance sheet—and the vulnerability stems precisely from where the excess is greatest. What markets must closely track is the pace at which the 10-year Treasury yield crosses 5%, and how elevated long-term rates will impact AI corporate financing and the broader sustainability of the AI boom. While prevailing market consensus continues to operate under the belief that AI investment can decouple from macroeconomic interest-rate dynamics, continued government debt pressures pushing long-term rates higher will inevitably strain the external financing channels upon which AI expansion depends. Ultimately, a 5% 10-year Treasury yield may prove to be the definitive litmus test for the longevity of this AI-driven rally.