Powell Says AI Boom Isn’t a Bubble — But a Real Economic Driver Fueling Productivity and Investment

Federal Reserve Chair Jerome Powell has drawn a sharp line between the current artificial intelligence boom and the dotcom bubble of the early 2000s, arguing that today’s surge in AI spending is anchored in profitable, established businesses and tangible economic activity — not speculative mania.

“I won’t go into particular names,” Powell told reporters after the Fed’s policy meeting on Wednesday, “but they actually have earnings. These companies … actually have business models and profits and that kind of thing. So it’s really a different thing” from the dotcom bubble, he said.

According to Fortune, it was perhaps Powell’s most direct acknowledgment yet that artificial intelligence is now a fundamental driver of U.S. growth. Over the past two years, the AI industry has spurred hundreds of billions of dollars in data center construction, semiconductor manufacturing, and cloud infrastructure investment — a scale that rivals some of the largest industrial expansions in modern history.

A Structural Shift, Not a Monetary Bubble

Powell was clear that the AI boom isn’t being fueled by easy money or low interest rates. “I don’t think interest rates are an important part of the AI or data center story,” he said. “It’s based on longer-run assessments that this is an area where there’s going to be a lot of investment, and that’s going to drive higher productivity.”

That stance runs counter to one of Wall Street’s popular narratives — that loose financial conditions could be inflating another tech bubble. Instead, Powell described a structural transformation: a long-term bet by corporations that AI will reshape how work is done.

Major tech companies are spending at a historic pace to seize that future. Nvidia, whose chips power much of the global AI infrastructure, is on track to generate over half a trillion dollars in annual revenue. Microsoft and Alphabet have committed hundreds of billions of dollars in capital expenditure for new data centers, networking systems, and AI research. But unlike the speculative surge of the late 1990s, Powell noted, these firms are already profitable and reinvesting cash flow — not borrowing aggressively — to fund the buildout.

Goldman Sachs has backed that interpretation. In a recent note titled “The AI Spending Boom Is Not Too Big,” the bank’s chief U.S. economist Joseph Briggs argued that “anticipated investment levels are sustainable, although the ultimate AI winners remain less clear.” The Goldman team estimated that AI’s productivity potential could add between $8 trillion and $19 trillion to the U.S. economy in present value terms, depending on how quickly the technology spreads across industries.

“We are not concerned about the total amount of AI investment,” Briggs wrote. “AI investment as a share of U.S. GDP is smaller today — less than 1% — than in prior large technology cycles, which peaked between 2% and 5%.” In other words, despite the hype, the AI buildout is still in its early innings.

Grounded in the Real Economy

Powell pointed out that AI’s footprint is already visible beyond balance sheets and earnings reports.

“It’s the investment we’re getting in equipment and all those things that go into creating data centers and feeding the AI,” he said. “It’s clearly one of the big sources of growth in the economy.”

His comments align with private-sector forecasts suggesting that AI infrastructure spending could soon rival the economic boost once delivered by the U.S. shale revolution. JPMorgan economists recently estimated that the buildout could add roughly 0.2 percentage points to annual GDP growth over the next year — a meaningful lift for an economy of America’s scale.

The AI-driven investment wave has also reshaped industrial and energy dynamics. Utilities across the U.S. are racing to expand grid capacity as power demand surges from data centers. Energy executives have described the current load growth as the steepest in decades. Meanwhile, construction firms are reporting record backlogs for AI-related projects, from silicon fabrication plants to cooling systems and fiber networks.

In short, Powell is talking about cranes, concrete, and capital goods — not just code.

Although being optimistic, Powell warned that the long-term impact of AI on productivity and jobs remains uncertain.

“I don’t know how those investments will work out,” he said, acknowledging that it’s too early to tell how much of that productivity story will come through.

Economists have cautioned that the benefits of AI are likely to be unevenly concentrated among a small number of large firms that can afford the technology, while many others lag behind. Moreover, the short-term effect of automation could be disinflationary for wages and potentially negative for employment.

Powell acknowledged that tension, noting that a lot of companies that are making layoff announcements are talking about AI and what it can do, which underscores the paradox that the same technology boosting output might also slow job creation.

The Fed chief also referenced recent labor market adjustments, observing that job growth, once adjusted for statistical overcounting, is now pretty close to zero.

The Fed’s Balancing Act

Powell’s comments highlight a broader challenge of balancing the near-term slowdown in job growth against the long-term promise of an AI-led productivity surge. The Fed’s dual mandate, maximum employment and stable prices, could be complicated by the uneven rollout of a technology that simultaneously drives efficiency and disrupts labor demand.

Yet Powell’s remarks show that the Fed sees the AI boom as a real, durable driver of investment and growth — not a speculative mirage.

With corporate America pouring unprecedented sums into AI infrastructure and applications, Powell’s distinction between bubble and transformation may prove critical in shaping how both investors and policymakers navigate what could be the defining economic trend of the decade.