Fed's AI Productivity Bet Echoes Greenspan Era Gamble

Kevin Warsh's potential return to the Federal Reserve comes with a familiar playbook: bet big on technology-driven productivity gains. It's a strategy that echoes Alan Greenspan's late-1990s gamble on the internet revolution—a bet that paid off spectacularly until it didn't.

The parallels are striking. Just as Greenspan allowed the dot-com bubble to inflate based on promises of internet-driven productivity, Warsh appears positioned to embrace AI as the next transformative force justifying current market exuberance and monetary accommodation.

The Greenspan Precedent

During the late 1990s, Greenspan made a controversial decision that defined his legacy. Despite mounting concerns about asset bubbles, he kept interest rates relatively low, arguing that the internet would unleash unprecedented productivity gains that would validate soaring stock prices.

The theory was elegant: if technology could dramatically increase worker output, then higher stock valuations weren't speculative froth—they were rational anticipations of future earnings growth. For several years, the data supported this view. Productivity growth surged from an average of 1.4% in the 1970s and 1980s to over 2.5% in the late 1990s.

But the story had a sequel. When the productivity miracle proved less miraculous than hoped, the bubble burst spectacularly. The NASDAQ lost 78% of its value between 2000 and 2002, wiping out $5 trillion in market capitalization.

Warsh's AI Wager

Now Warsh seems prepared to make a similar bet on artificial intelligence. His previous writings and speeches suggest he views AI as potentially more transformative than the internet revolution, capable of boosting productivity across virtually every sector of the economy.

The early evidence is tantalizing. Companies investing heavily in AI report significant efficiency gains. Microsoft claims its Copilot tools increase programmer productivity by 55%. Goldman Sachs estimates AI could boost global GDP by 7% over the next decade through productivity improvements.

But here's where it gets interesting: unlike the internet boom, which primarily affected information-based industries, AI promises to revolutionize everything from manufacturing to healthcare to legal services. The potential productivity gains could be an order of magnitude larger.

The Market's AI Premium

Financial markets are already pricing in this AI productivity boom. The Magnificent Seven tech stocks trade at valuations that assume sustained earnings growth well above historical norms. The S&P 500 trades at 22 times forward earnings, compared to a long-term average of 16 times.

This premium exists because investors believe AI will deliver the productivity gains necessary to justify these multiples. Remove that assumption, and current valuations become difficult to defend.

Warsh understands this dynamic. His challenge will be calibrating monetary policy to support genuine productivity-driven growth while avoiding the speculative excess that characterized the dot-com era.

Different This Time?

Several factors distinguish today's AI revolution from the internet bubble of the late 1990s. First, the technology is already delivering measurable results rather than just promising future benefits. Second, the companies driving AI development have stronger balance sheets and more diversified revenue streams than the dot-com darlings of yesteryear.

Perhaps most importantly, the current AI boom is being driven by established tech giants with proven business models rather than speculative startups burning through venture capital.

But skeptics raise valid concerns. AI adoption remains concentrated among large corporations with significant resources. Small and medium-sized businesses—which employ the majority of American workers—have been slower to embrace AI tools. Without broad-based adoption, the productivity gains may remain limited to a narrow slice of the economy.