The job market is in a funk.

Since May, the economy added just 29,000 positions a month. Official statistics for September are unavailable owing to the government shutdown, but private payroll data was not encouraging.

If you’ve lost a job or recently graduated without skill in a hot area like nursing, job searches are long and frustrating.

Across the entire economy, hiring rates have fallen below pre-COVID levels, in significant measure because businesses are deploying Artificial Intelligence to boost productivity.

OpenAI, Microsoft, Meta, and other tech companies are spending hundreds of billions of dollars to advance AI models. The broader economy benefits but the unemployed don’t.

In the 1990s, the buildout of the internet featured businesses blanketing the country with millions of miles of fiber optic cable that far exceeded the demand that emerged. Stock prices soared but ended in a bubble that burst in March 2000.

Could this happen with AI?

AI investments consist of firms like OpenAI, Microsoft and Meta spending heavily to develop programs like ChatGPT, Copilot and Llama, building data centers with Nvidia chips and other hardware to train and run those and creating agents to perform business and consumer tasks.

Similarly investing are spinoffs like Anthropic—founded by several former OpenAI employees—and neoclouds like CoreWeave, Nebius Group and Nscale Global Holdings Ltd. that build data centers to lease access to Nvidia’s chips.

McKinsey estimates that worldwide spending on data centers and electrical capacity could reach $6.7 trillion by 2030.

In 2023 and 2024 alone, leading tech firms committed sums to build data centers that exceed the amount spent over 40 years to build interstate highway systems adjusted for inflation.

Over 100 million Americans use AI programs, but 97% don’t pay a nickel for it.

According to an MIT study, 95% of businesses say they are getting little return on their AI investments. And that may explain why they are reluctant to shell out more than the $30 a month per user Microsoft charges for Copilot or something similar.

The free AI functions embedded in Google’s search engine serve my research needs well.

Expert: Is AI a Force for Good or a Destructive Power... Find Out Here

In 1794, Eli Whitney patented the Cotton Gin. It enabled the South’s cotton economy that flourished in the 19^th century, but he didn’t profit much from it.

For one thing, patent laws had lots of loopholes but another problem was that farmers could easily copy the device—that is build their own. It’s hard to profit from an invention if folks can build a similar machine for personal use.

That may be happening with AI, too.

AI programs are displacing software engineers, and AI is learning how to build agents for ordinary folks.

In any case, economists are notoriously bad at measuring the consequences of transformative technologies in real time.

During the 1980s, desktop computers emerged and reduced headcounts in clerical and administrative tasks. In the 1990s, the Internet accelerated this process.

Yet, economists couldn’t find it in the data. The Nobel Prize-winning economist Robert Solow lamented “you can see the computer age everywhere but in the productivity statistics.”

When I repeated this to my attorney in 1995, he responded that prior to desktop computers his firm had seven lawyers and 10 support personnel but with computers, those numbers had reversed.

Once again, economists might do less data mining and simply look around and talk to CEOs.

With robots aided by AI, Walmart like Amazon has automated warehouses, and CEO Doug McMillon anticipates a major impact on virtually all white collar jobs.

Now Walmart is building AI agents for its customers, suppliers and workers—just like the southern planter building his own cotton gin.

Over the next three years, McMillon wants to keep headcount constant as the retailer increases sales.

The ability to apply AI and collaborate effectively with agents, colleagues and customers is what will keep someone employed.

But how will AI pay for itself?

Likely the same way web browsers and social media do now—selling advertising and products. Meta will use data gleaned from AI searches to target ads.

Last year, OpenAI added a search engine to ChatGPT to challenge Google, and this year it will let users buy products by linking up with shopping platforms.

At Walmart, McMillon sees some existing positions like delivery drivers increasing, but most others transformed or disappearing and new positions created—one of those is “agent builder.”

For most unemployed and recent graduates becoming AI-fluent and an effective collaborator with both machine and man will be key to breaking through to start a new or first career ladder.

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Peter Morici is an economist and emeritus business professor at the University of Maryland, and a national columnist.