A critical question is emerging as artificial intelligence evolves from a Wall Street narrative into a tangible driver of U.S. economic growth: has the world's largest economy become excessively dependent on a rapidly advancing technology? On Wednesday, Peter Orszag, CEO of the prominent investment bank Lazard, offered a sobering assessment in an interview: "The U.S. economy has become a leveraged bet on the success of AI." Orszag argues that the sources of U.S. economic growth are now heavily concentrated in two intertwined pillars: AI technology itself and high-income consumers benefiting from AI-driven stock market gains. The fragility of this growth model lies in the potential for both engines to stall simultaneously if the AI narrative falters.
Data corroborates this view, showing AI has become the dominant force in economic expansion. According to the U.S. Bureau of Economic Analysis, real GDP grew at an annualized rate of 2.0% in the first quarter of 2026. Analysis from Bespoke Investment Group reveals that software and IT equipment investment contributed 134 basis points to that quarterly GDP growth. This implies that technology infrastructure drove approximately 67% of the economic growth for the quarter, surpassing the previous record set during the internet bubble in 1999 by about 10 basis points. The Kobeissi Letter stated on social media platform X: "Without AI-driven tech investment, Q1 GDP growth would have been close to zero."
The concentration of this growth is concerning. In its mid-year U.S. economic outlook titled "Capex Over Consumption," Morgan Stanley highlighted a structural shift: the U.S. economy is transitioning from being consumption-led to being powered by AI capital expenditure. While corporate AI investment is surging, consumer spending is decelerating under pressure from oil prices and income constraints. The firm forecasts non-residential business fixed investment to grow 7% in 2026, accelerating to 8% in 2027. Combined capital expenditures from Amazon, Alphabet, Meta, Microsoft, and Oracle could reach approximately $805 billion in 2026. Conversely, growth in real consumer spending is projected to slow from 2.1% in 2025 to 1.8% in 2026, with middle- and low-income groups particularly squeezed by high fuel costs. David Sacks, a former AI advisor in the Trump administration, noted pointedly in early May: "AI accounted for 75% of GDP growth in Q1. This trend is likely to continue. Technological leadership has always been a huge competitive advantage for the U.S., and now more than ever—halting AI progress would be tantamount to halting the U.S. economy."
The "high-income consumers" Orszag referenced form the other core pillar of the economy. Their purchasing power is not generated in a vacuum; they are beneficiaries of the AI-driven stock market rally. JPMorgan previously estimated that AI-related stocks constitute over 40% of the S&P 500's market capitalization. A 10% decline in their value could erase $2.7 trillion in U.S. household wealth and reduce consumer spending by approximately $95 billion. Barclays analysis indicates that AI directly contributes nearly 1% to U.S. GDP growth and supports consumption through a wealth effect from elevated tech stock valuations, creating a "dual-engine" economy.
However, the foundation of this dual-engine model is becoming increasingly imbalanced. Research from Cresset Capital shows the top 10% of income earners now account for nearly half of all consumer spending, while the top 20% of households hold about 70% of financial assets. Among the bottom 80% of earners, problems such as slowing real spending, depleted savings, and rising loan delinquency rates are becoming more pronounced. An economic expansion propped up by a minority of high earners and a handful of tech giants is inherently fragile.
Beyond growth concentration, Orszag's warnings extend to deeper structural risks in the labor market. He cautioned that the economy could face headwinds as businesses and workers adapt to AI-driven changes, describing the current situation as a potential "fast, big shock." He noted that "labor markets can handle fast, small shocks or slow, big shocks well—but this could be a fast, big shock."
This warning aligns with an accelerating wave of AI-related job cuts. According to Noor Trends, by mid-May 2026, over 179 companies had laid off 113,000 employees in AI-driven restructurings, a scale about one-third larger than the same period in 2025. This trend has spread from the tech sector to banking, healthcare, logistics, energy, and retail. Management is increasingly positioning AI as a replacement for large-scale human labor rather than merely a productivity tool.
The banking sector is a primary focus of this disruption. Just before Orszag's comments, Standard Chartered Group CEO Bill Winters announced a plan to cut over 15% of corporate and back-office roles—nearly 8,000 jobs—by 2030. With a global workforce of about 82,000, including over 52,000 back-office staff, the cuts will target functions like HR, risk, compliance, operations, and technical support. Winters explicitly cited AI and automation as the core drivers, aiming to "replace lower-value human capital with invested financial and investment capital" in some areas. He stated, "We are not reducing work, but we are reducing the number of roles to make way for machines, a trend that will accelerate with AI."
Standard Chartered is not alone. HSBC CEO Georges Elhedery concurrently stated that AI would "destroy some jobs and create new ones," as the bank considers an AI-driven restructuring potentially affecting around 20,000 roles. Citigroup continues its plan to cut 20,000 jobs globally in 2026. Morgan Stanley estimates that banking, tech, and professional services firms have reduced their workforce by about one-twentieth over the past year due to AI. Last week, Goldman Sachs President and COO John Waldron described the firm as a "human assembly line," stating "digital agents will become our robots," and revealed Goldman is using AI to scale operations without increasing hiring.
Echoing Orszag's "fast, big shock" characterization, the World Economic Forum's 2026 "Chief Economists Outlook" shows two-thirds of chief economists expect AI to cause moderate job losses over the next two years. Over a ten-year horizon, 57% of respondents anticipate a net loss of jobs, with only about one-third expecting AI-driven job creation to exceed losses. The report also indicates that 97% of surveyed economists expect AI to have a "significant impact" on U.S. economic growth—a proportion far exceeding that for any other major economy.
Despite his deep concerns about over-reliance, Orszag does not wholly dismiss the direction. He remarked in the interview, "Like many bets, it could work out, it could not work out, but it's a good bet to make." This statement acknowledges both the substantive risks and the strategic rationale.
Taking a longer-term view, Lombard Odier predicts AI could raise the U.S. average annual productivity growth rate from 1.60% to 1.85% over the next decade. While first-quarter real GDP grew at a 2% annualized rate, this contrasts sharply with a softening labor market and slowing job growth. AI has undeniably become a central pillar of the U.S. economy, contributing two-thirds of GDP growth, driving hundreds of billions in capital expenditure, and fueling mergers and consolidation across the utility sector. Concurrently, layoff plans are accelerating from Wall Street to multinational banks, and the consumption divide between high and middle-to-low-income earners is widening.
Orszag's warning is fundamentally about concentration risk, not a rejection of AI's potential. An economic expansion reliant on the capital expenditure of a few tech giants and the wealth effect on a minority of high-income consumers, supported by a supply chain—from chip design to data centers and power supply—deeply dependent on the continued AI boom, creates significant vulnerability. Any shortfall in expectations could trigger rapid and severe feedback effects. Orszag's "leveraged bet" metaphor aptly captures the duality of this historical moment: the U.S. economy is betting on a technology's success with a degree of concentration rare in history, while the flip side of that leverage—both financial and economic—is a dramatically expanded risk exposure.
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