Tech Layoffs Hide a Scarier Number: Labor Participation at 1976 Levels

Roughly 720,000 prime-age Americans stopped working or looking for work between May and June, marking the biggest one-month drop in labor force participation among workers aged 25 to 54 — excluding the pandemic — since June 1976, according to the St. Louis Fed.

That is the number Joe Procopio, writing for Inc.com, says should scare the tech industry far more than the headline layoff counts that have dominated coverage for the past two years.

The numbers behind the individual stories

The recent CNBC report that anchors Procopio's analysis follows Dan Coda, a technical program and project manager in Durham, North Carolina, laid off in December 2025 and now six months unemployed. "Starting around December 2025, when he was laid off from his previous role, [Dan] Coda says he spent more than 300 hours job hunting, submitting dozens of applications, hearing back about 15 potential roles and going through multiple rounds of interviews to no avail," CNBC reported.

Coda gave up. The article is titled "Why People Are Dropping Out of the Workforce and Not Looking for New Jobs: 'The Market Wore Me Down.'"

Procopio, who has spent years reporting on the tech labor market and hiring practices, says Coda's numbers are actually better than what he hears from his own network of laid-off tech workers. Three hundred hours of job hunting? He has heard "thousands" of hours from hundreds of laid-off people. Dozens of applications? He has seen file dumps of hundreds of individually tailored applications. Fifteen callbacks is above the norm — it is usually about one a month, if you are lucky. And multiple interview rounds pales next to the ten rounds he has documented for a single job.

The aggregate problem

The individual stories are now quantifiable, but Procopio argues the aggregate data is what matters. According to U.S. Bureau of Labor Statistics data cited by CNBC, more than 1.9 million Americans — roughly 1 in 4 unemployed people — were jobless but still looking for work for longer than six months in June.

The U.S. is hitting unemployment numbers not seen since the Great Recession, both in workers laid off and in the long-term unemployed, yet the unemployment rate itself remains relatively low.

Procopio points to the Labor Participation Rate — the share of people actively working or looking for a job — as the metric that reveals the structural damage. After the Great Recession of 2008-2009 and the dot-com collapse at the turn of the millennium, employment, hiring and salaries eventually recovered, but labor participation took an extra couple of years to catch up. Over 26 years, especially in tech, it has never fully recovered, he writes.

CNBC warns of what could come next: "A continuous low-hire, low-fire job market could make it more challenging to find work and push more people out of the workforce altogether." Procopio notes the industry has been in low-hire mode for years and has not yet reached low-fire.

How AI accelerates the exit

What separates this layoff cycle from previous ones, Procopio writes, is the tendency of companies doing the firing to blame AI for the cuts — whether or not that blame is accurate, and he argues it is not. Tech workers have received the message loud and clear: "AI has made you obsolete."

Experienced older tech workers are responding by leaving the workforce entirely — retiring early, going independent, or changing careers and downsizing — and thanks to the windfall cycle of tech, many have the means to do so. The industry, Procopio notes, is already starting to need a lot of them back, and their ranks have not been replenished.

The people exiting are both men and women, and the majority are ages 25 to 34, says Heather Long, chief economist at Navy Federal Credit Union, who specializes in the economics of the middle class.

The downstream risk

Procopio argues that no single company can proactively counter a macroeconomic downward shift, so defense is the rational posture. But labor participation should function as a leading indicator, not an afterthought, particularly in tech and other forward-facing industries, because its downstream effects cascade through everything else — who is buying what, and how much.

If participation does not recover, Procopio expects major downstream effects in inflation, purchasing, consumption and eventually GDP growth. Business customers will continue to demand more for less, and AI has promised them exactly that.

His closing argument: the companies best positioned to survive what is coming are those that deliver more real value at lower cost — not by replacing people with AI, but by using AI to make their people more valuable.