Last week, I spent several days in Philadelphia for the Annual Meeting of the National Association for Business Economics (NABE). The event brings together economists from central banks, think tanks, corporations, and universities to assess the state of the global economy. The theme this year was Global Economy in Transition: Finding Opportunity Amid Disruption. Sessions explored the pressures shaping global business and policy: geopolitical instability, shifting trade regimes, monetary divergence, and the disruptive force of technology. There were also discussions of long-term structural issues such as climate risk, labor markets, and the balance of economic power.

The purpose of this gathering, as my dear friend Kent insists, is not to forecast the price of copper next quarter, but to expose the fundamental choices (and their costs) that reshape our financial lives. While a fun and lively gathering, the atmosphere was serious, analytical, and ultimately, pragmatic.

As Kent and I highlighted two weeks ago, conventional recession indicators suggest a healthy economy, though recent trends in the labor market for college graduates paint a different picture. We pointed to some appalling anecdotes and statistics, including the case of the Computer Science major who submitted 5,762 job applications, only to hear back from none.

This reality begs the question of whether job creation in the age of AI will ever speed up as individuals, companies, governments, and educational institutions adapt. If so, when?

In a podcast interview, LinkedIn’s Chief Economist, Karen Kimbrough, expresses optimism for the future of work in the age of AI. She acknowledges the unusually slow hiring rate for recent grads, but nonetheless offers the reassuring take that current trends are cyclical and that AI-embracing grads will fare the best in the labor market.

If there really is a rainbow after the storm and her forecasts come to fruition, when will we start seeing the evidence of it? What actions must be taken by companies, governments, and job seekers themselves to ensure a future where AI development works in favor of job seekers rather than against them? What does it mean for job seekers to “embrace AI?” What incentives underpin whether or not we, as a society, will work to ensure that AI does not leave today’s college grads behind?

Let me be clear: I believe in the promise of AI. As a power user, I rely on multiple foundation models daily to streamline my work and solve problems faster than ever. The productivity is real, the tools are evolving quickly, and the cost per use keeps dropping. Naturally, I want to invest in the future I’m already living. And like many of my colleagues, I’ve tilted my portfolio to give a little extra love to AI-heavy tech stocks. But here’s the thing… I’m also an economist. Which means I’ve seen this movie before. And I know how it ends.

Wealth built on asset bubbles feels exhilarating until the floor gives out. As investors, professionals, and decision-makers, we owe it to ourselves to remember a basic truth: price may ride the wave, but value is tethered to the ocean floor. When the current recedes, the fundamentals remain. That is where wealth actually lives.

This article is a guide to navigating the excitement of asset bubbles, especially the AI boom, while staying grounded in financial reality. It draws on economic history, hard data, and the cautionary tales of past bubbles to offer a simple message: Invest, yes. But don’t forget to check your parachute.

In 2025, if you asked the average economist about the U.S. labor market, the answer might sound reassuring: the unemployment rate is holding steady around 4%, inflation is relatively under control, and job growth continues month after month. But ask a 23-year-old college graduate with a crisp new diploma and a browser full of unanswered job applications, and you’ll hear a different story.

A quiet crisis is unfolding in the United States that eludes headline economic metrics yet is painfully evident in overflowing inboxes, mounting loan statements and waning optimism among young Americans entering the workforce. In mid-2025 the unemployment rate for recent U.S. college graduates reached 5.8%, according to Bureau of Labor Statistics data, its highest level in more than a decade apart from the pandemic spike. More strikingly, this graduate jobless rate now exceeds the national figure, overturning the long-standing pattern in which new degree-holders enjoyed lower unemployment than the wider labor market.

When I walked into the TechEx AI & Big Data Expo in Santa Clara last week, I didn’t expect clarity. I expected noise: buzzwords ricocheting off LED screens, startups pitching productivity miracles, enterprise executives nodding sagely to sales demos. And all of that was definitely there. But what stayed with me wasn’t the flash. It was a quieter insight: most professionals aren’t worried that AI will replace them. They’re worried they’re already being measured against it.