NextFin News - Alan Greenspan, the former Federal Reserve Chair who famously presided over the "irrational exuberance" of the 1990s, warned on Friday that the current artificial intelligence boom lacks the structural economic momentum that defined the dot-com era. Speaking in an interview with Bloomberg News on March 27, 2026, Greenspan argued that while AI represents a significant technological leap, it has yet to trigger the broad-based productivity surge that allowed the U.S. economy to achieve non-inflationary growth three decades ago.
Greenspan, now 100, led the U.S. central bank from 1987 to 2006 and is widely remembered for his data-driven approach that favored allowing the economy to "run hot" when technology-driven productivity gains were evident. His latest assessment comes at a time when U.S. President Trump’s administration has increasingly invoked the mid-1990s as a blueprint for current monetary policy, suggesting that AI-driven efficiency will naturally suppress inflationary pressures. However, Greenspan’s skepticism suggests that the "secret sauce" of the 1990s—a rare alignment of demographics, globalization, and a specific type of capital deepening—is currently missing.
The data supporting Greenspan’s caution is found in the diverging paths of capital expenditure and labor output. During the 1990s, productivity growth averaged roughly 2.5% annually, nearly double the rate of the previous two decades. In contrast, despite the billions of dollars poured into AI infrastructure by tech giants over the last two years, official labor productivity figures for early 2026 remain stubbornly below 1.5%. Greenspan noted that the 1990s boom was characterized by the rapid "commoditization" of the internet, which lowered costs for every sector from retail to manufacturing almost immediately. AI, by comparison, remains a high-cost, energy-intensive endeavor with benefits that are currently concentrated in a handful of software and semiconductor firms.
This perspective is not without its detractors. Analysts at Goldman Sachs and several Silicon Valley venture firms have argued that productivity gains from AI are "lagging indicators" that will only become visible once the technology is fully integrated into corporate workflows. They point to the "Solow Paradox" of the 1980s—where computers were seen everywhere except in the productivity statistics—as a historical precedent for the current delay. However, Greenspan’s view represents a more cautious, "old school" monetarist stance that prioritizes realized data over speculative potential. His judgment, while influential, is increasingly viewed by some younger market participants as a reflection of a bygone era of globalization that has since been replaced by protectionist trade policies and fragmented supply chains.
The implications for the Federal Reserve are immediate. If the "Greenspan era" productivity miracle does not materialize, the central bank will have less room to keep interest rates low without risking a resurgence of inflation. While U.S. President Trump has frequently called for lower rates to fuel the AI race, the lack of a corresponding productivity jump puts the Fed in a precarious position. The current market environment is further complicated by geopolitical tensions in the Middle East and shifting trade dynamics, factors that were largely absent during the relatively stable geopolitical climate of the late 1990s.
Ultimately, the distinction Greenspan draws is one of economic "friction." The 1990s internet boom reduced the friction of information exchange globally. AI, in its current form, is a tool for optimization that requires massive upfront investment and specialized talent, creating new types of friction in energy markets and labor transitions. Without a breakthrough that democratizes these gains across the wider economy, the current boom may remain a high-tech enclave rather than a broad-based economic engine.
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