Three Hidden Effects of AI Job Loss...And How to Get Ready
When AI displaces workers, the damage doesn't stop at the pink slip. It travels through the tax code, into your kids' classrooms, through the pension fund, and out the other side. Here's what to know.
Jennifer Schultz is a health economist at the University of Minnesota Duluth and a former state legislator. In April, she published a piece in the Minnesota Reformer pointing out a hidden effect of our fragile moment: if AI eliminates enough jobs, it doesn’t just hurt the household finances of the laid-off workers. It threatens the financial architecture that Social Security and Medicare are built on. The FICA payroll tax — 15.3% split between workers and employers — is the mechanism through which current workers fund current retirees. Fewer workers, less fuel in the tank. It’s a smart and eye-opening look past the first-order loss to the secondary effects.
To be clear, the first-order picture is alarming enough. A 2025 working paper from RAND found that 84 percent of federal revenue is tied to labor — not just payroll taxes, but the income taxes, consumer spending, and local sales taxes that flow from people having jobs and spending money. The whole funding architecture of American government runs on workers having jobs. AI threatens to remove that foundation without replacing it.
And it isn’t just the flow of money in the market that’s driving this. It’s also policy choices: in July 2025, Congress passed the One Big Beautiful Bill Act, which permanently restored 100% bonus depreciation for qualified business equipment. That’s a mouthful. Here’s what it means: a company that spends $10 million on AI systems can write off the entire cost immediately. A company that spends $10 million on salaries can write off salaries too — but the tax code now explicitly makes the machine the cheaper call. Congress modernized the treatment of capital. It left workers’ training and transition support behind.
The job losses that follow aren’t purely the product of AI getting smarter. They’re also in part the product of deliberate decisions about what gets subsidized.
Now, on to some second-order effects workers (and lawmakers) should understand right now. Here are three places the damage travels after the pink slip.
1. YOUR KIDS’ SCHOOL
Schools in most states depend on a combination of property taxes and state income tax revenue, both of which are tied to employment. When workers lose jobs, income tax receipts fall. When working-class neighborhoods hollow out — which is what happens in places like Detroit, Duluth, or Pittsburgh after major industry displacement — property values soften and the tax base underneath the local school budget shrinks.
An estimate from South Carolina, published in the Post and Courier, found that 800 AI-attributed job losses in that state in 2025 translated to roughly $700,000 in lost school tax revenue. That’s one state, one year, at relatively early displacement levels. The structural issue the estimate points to: a company that replaces 40 human workers with an AI system loses $2.4 million in payroll expenses and the government loses the tax revenue that came with those salaries. The AI system doesn’t pay income tax. It doesn’t pay into Social Security. It might pay some property tax if it has a data center in that state, but that’s nothing compared to the property tax that hundreds or thousands of employees generate from the housing they buy or finance with their wages.
Some of the states most exposed — states like Michigan, Pennsylvania, Illinois — all have significant concentrations of exactly the administrative, customer service, and mid-level professional roles that automation is hitting hardest. They also have school districts already operating on thin margins after decades of deindustrialization. This wave is hitting the same communities twice.
2. THE RETRAINING TRAP
The standard response to AI displacement is: “new jobs will be generated.” And the next sentence tends to be “workers will need to retrain.” What goes unsaid is that the systems designed to fund that retraining are the same ones being hollowed out by displacement itself.
The federal Workforce Innovation and Opportunity Act funds roughly $1 billion a year in retraining, career counseling, and wage subsidies for displaced workers. That sounds significant until you understand the J.P. Morgan Private Bank estimate that AI is on track to displace approximately one million jobs per year over the next decade — a pace roughly five times faster than globalization managed at its peak. One billion dollars spread across a million displaced workers is a thousand dollars each. One community college semester. Not a career.
State unemployment insurance funds face the same kind of math. When AI automation renders an entire job category obsolete — not one factory but an entire occupational category — displaced workers can’t simply wait for conditions to improve in their sector. They need to move to a different sector entirely, which takes longer and costs more than current state unemployment-insurance systems are designed to support. The AI Frontiers analysis of this structural mismatch does a great job of explaining the problem: the programs we built assumed temporary disruption within industries. AI is producing potentially permanent disruption, and across them.
There’s a ghost in this data that makes it worse. A Fortune analysis found that nearly 75% of AI-displaced workers don’t apply for unemployment benefits at all — in part because union membership, which is one of the best predictors of whether someone even knows to apply, has fallen to a historic low of 9.9%. The people most likely to be displaced quietly, without applying for help, are also the people least likely to have been told how to ask for it. They disappear from the unemployment statistics, which makes the headline numbers look manageable. They don’t disappear from poverty statistics. (Don’t be part of that number: have a look at “If You’re One of the People Worried About This,” below.)
3. THE PENSION CLIFF
This one moves slower, but when it arrives it’s going to swamp us.
Public pension systems in states like Illinois, New Jersey, and Pennsylvania are already carrying significant unfunded liabilities. They are funded by a combination of investment returns and ongoing contributions from active public employees and their employers. If state and local budgets come under pressure from declining tax revenues — which, as we’re discussing, is what AI-driven displacement of the private-sector tax base produces — governments face a familiar choice: cut services, raise taxes, or reduce contributions to pension funds. History is fairly clear that the last one tends to happen first.
Illinois went from a BBB- credit rating with a negative outlook in 2020 to an A-minus today — a genuine recovery that required years of painful fiscal discipline. Any erosion of the state’s income tax base from large-scale private-sector displacement would pressure the very gains that recovery was built on. New Jersey, Pennsylvania, and Michigan face versions of the same dynamic.
For workers who’ve spent decades in private-sector defined-contribution plans — also known as 401(k)s — the picture is different but not better. If AI displacement pushes workers out of well-paying jobs and into lower-wage positions (which the data suggests is the more likely outcome than outright unemployment), those workers reduce their contributions, potentially for years. The compounding loss over time is difficult to recover from. A 55-year-old account manager displaced into a gig economy role at 60% of their prior income doesn’t go back to maxing out their 401(k).
A Number Nobody’s Counting
There is a statistic at the center of all three of these problems that is rarely discussed, because it’s a missing number, rather than one of the many that are shouting at us.
Labor force participation — the share of adults who are either working or actively looking for work — is projected to fall from 62.6% in 2025 to around 61% by 2030, and as low as 55% by 2050. The key detail: unemployment rates are expected to remain roughly stable over the same period. Two numbers moving in opposite directions? How can that be? It means people are leaving the workforce entirely rather than registering as unemployed.
People who stop looking for work don’t show up in the unemployment rate. And they also don’t pay payroll taxes. They don’t contribute to Social Security. They don’t fund their kids’ schools. But they do become eligible for Medicaid, SNAP, and social services — the programs whose funding depends on the tax base of people who are still working.
The headline unemployment number is going to look fine for a long time. Don’t be fooled. Because the systems underneath that stable-seeming number are going to be anything but stable.
If You’re One of the People Worried About This
One of our most-read pieces on Hard Reset right now is our guide for newly unemployed tech workers — which tells you something about who’s reading and what they’re scared of. So a direct note: the story above is about structural forces. Here’s what those forces mean at the level of your household.
If you’ve been displaced or are worried about displacement, the single most important thing to understand is that the retraining programs that exist are underfunded for the scale of what’s coming, but they exist…and most people don’t use them. The federal WIOA program funds career counseling and training vouchers through every state’s workforce development system — find your state’s program here. If you’ve been laid off, apply for unemployment insurance immediately even if you’re not sure you qualify — the 75% non-application rate I cited above means there’s a real chance you’re leaving money on the table.
The pension and Social Security numbers above aren’t a reason to panic about your future retirement. But they are a reason to treat any assumptions you’ve been making about those programs as the shakiest part of your financial plan, and to adjust your savings accordingly where you can. The systems are not broken yet. But they are being stressed in ways that haven’t been honestly described to the people who depend on them. And that’s us.
Further Reading
Jennifer Schultz, “If AI cuts jobs, it would also threaten Social Security and Medicare” — Minnesota Reformer, April 2026. The piece that inspired me to put this one together; worth reading in full.
Carter C. Price and Akshaya Suresh, “Federal Revenue When AI Replaces Labor” — RAND Corporation, 2025. The working paper on what happens to the tax base in each displacement scenario.
Anton Korinek and Lee Lockwood, “The Future of Tax Policy: A Public Finance Framework for the Age of AI” — Brookings Institution, February 2026. The most rigorous treatment of what “ambitious fiscal innovation” would have to look like.
“Why companies using AI should pay more property taxes — especially school taxes” — Post and Courier, December 2025. The school revenue estimate.
“AI job disruption may be compounded because nearly 75% don’t apply for unemployment benefits” — Fortune, March 2026. The non-application rate and union membership data.
“A Proactive Response to AI-Driven Job Displacement” — Mercatus Center, October 2025. Source for the OBBBA tax code change and its implications for automation incentives.