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Carly Kaprive thought she’d be working again within three months.
A year after leaving her project-management job in Kansas City and moving to Chicago, the 32-year-old has applied 700 times, sat through interviews that vanished mid-stream (“We’ve decided not to fill the role after all”), and is still, stubbornly, unemployed.
She is the human face of a statistical riddle.
The national unemployment rate is only 4.3 %—a level that once signaled a tight, worker-friendly market—yet hiring is crawling along at the slowest pace since 2013. Economists at KPMG call it the “jobless boom”: GDP is growing, layoffs for the already-employed are rare, but companies refuse to add staff. The result is a two-tier economy—low-fire for insiders, near-lockout for outsiders.
The evidence is everywhere, private data can still be found. Government reports are silenced by the ongoing shutdown; the October and September jobs releases have been postponed. What numbers do emerge from fragmentary sources:
- Challenger, Gray & Christmas says announced layoffs jumped 175 % in October versus a year ago.
- Payroll processor ADP logged a net gain of only 42,000 positions—better than the two prior months, but barely a pulse.
- Revelio Labs estimates the economy actually lost 9,000 jobs last month.
- The Federal Reserve Bank of Chicago pegs unemployment at 4.4 % and rising.
Even before the data blackout, the hiring rate—the share of employed people newly brought on each month—had slipped to 3.2 %, a level last seen when unemployment was 7.5 % during the sluggish 2013 recovery.
Why the paralysis?
Executives cite a laundry list of worries: tariffs, AI’s uncertain impact, interest rates stuck at two-decade highs, and now a federal budget impasse that clouds 2025 spending plans. Investment is pouring into AI server farms while the rest of the economy—manufacturing, housing, bricks-and-mortar retail—idles.
Immigration crackdowns have added another twist. Deportations and visa restrictions trimmed labor supply just as demand cooled, masking weakness in the headline unemployment figure. Fed chair Jerome Powell calls the outcome a “curious balance”: fewer people to hire, but even fewer jobs on offer.
Long-term unemployment is creeping toward recession-like levels. More than 26 % of job-seekers have been out six months or longer, up from 21 % a year ago. A growing share have stopped looking entirely, erasing themselves from the official count.
Carly Kaprive refuses to be erased. She has earned an AWS Cloud Practitioner certificate, widened her search to nonprofits and start-ups, and budgets every dollar of unemployment insurance. She checks her inbox each morning, still hoping the 701st application is the one that sticks.
AI-driven layoffs have become a defining theme of 2025, as thousands of workers lose jobs while companies rapidly adopt artificial intelligence. In October, Amazon cut 14,000 corporate roles, citing major investments in AI. A month earlier, Salesforce CEO Marc Benioff said the company eliminated 4,000 customer support positions because AI can now perform “50% of our work.” Similar announcements have come from Accenture, Lufthansa, Klarna, and others across the U.S. and Europe.
The trend coincides with a sharp rise in layoffs. According to outplacement firm Challenger, Gray & Christmas, U.S. job cuts in October totaled 153,074 — the highest October level since 2003 and up 183% from September. Overall, this year has seen the most layoffs announced since 2009.
For workers facing AI-related job loss, the big question is what to do next: shift careers, retrain, or search for similar roles elsewhere.
But before making major decisions, it’s worth questioning whether “AI” is truly the cause. Fabian Stephany, assistant professor at the Oxford Internet Institute, notes that some companies use AI as a convenient justification for layoffs. In some cases, job cuts may stem from earlier over-hiring or a broader economic slowdown rather than automation.
If AI isn’t actually replacing the work, then finding a similar position at another company may be the simplest move. For example, demand for software developers remains high in many organizations.
But if your job genuinely is being automated, upskilling becomes key.
Identify Adjacent Skills
Glassdoor Chief Economist Daniel Zhao says upskilling can help workers move into more resilient or growing fields. Stephany describes this as understanding your “bundle of skills” — because skills rarely exist in isolation. For instance, a software developer may also have communication or project management skills. Instead of jumping into something unrelated, such as crafts or a foreign language, consider learning skills closely connected to what you already know — like statistics or product design.
This allows you to shift into roles that are accessible without needing a new degree or major retraining.
Build AI Literacy
AI literacy is quickly becoming a baseline requirement in many industries. LinkedIn data shows it is the fastest-growing skill added to profiles among people who are getting hired.
“Just as typing and basic computer skills became universal expectations, AI literacy is likely to follow the same path,” Zhao said. Those who can effectively use AI tools or integrate them into workflows can differentiate themselves in the job market.
Importantly, the AI skills you develop should complement your existing expertise. For example:
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If you work in business operations, learning to prompt AI tools effectively is more practical than becoming a software engineer.
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If you’re a developer, using AI tools to debug or speed up coding work can increase your value.
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Soft skills like leadership, communication, and team management remain difficult for AI to replicate — making them even more valuable.
“You want to show you’re not being left behind by technology,” Stephany said. “That you’re running with it — and ideally, a bit ahead of it.”
AI-driven layoffs have become a major trend in 2025, with thousands of workers losing their jobs as companies ramp up investments in artificial intelligence. For example, Amazon laid off 14,000 corporate employees in October, citing AI and other strategic priorities. In September, Salesforce cut 4,000 customer support roles because AI could handle half of the work. Other firms across the U.S. and Europe, including Accenture, Lufthansa, and Klarna, are also streamlining operations with AI.
The U.S. experienced its highest number of layoffs in October since 2003, with 153,074 job cuts—a 183% increase from September and 175% higher than the same month last year. This marks the worst year for announced layoffs since 2009.
In this challenging economy, workers impacted by AI-related job losses face important questions about their next career steps: Should they switch industries or build new skills? Fabian Stephany, assistant professor at the Oxford Internet Institute, urges caution and investigation, noting some companies may use AI as an excuse for layoffs driven by other factors like past hiring mistakes or economic downturns.
If automation is not the true cause, the best approach is to seek similar roles elsewhere. For example, software developers are still highly sought after by many companies. But if a job is becoming obsolete due to AI, upskilling is critical.
Glassdoor Chief Economist Daniel Zhao highlights the value of upskilling to pursue more promising careers. He recommends reflecting on your diverse skill set, since skills tend to come in clusters rather than in isolation. Stephany echoes this idea, pointing out that learning skills adjacent to your current expertise is often more feasible and effective than pursuing unrelated fields. For instance, a developer might benefit more from learning statistics than from studying arts or foreign languages.
AI literacy is rapidly becoming an essential skill. LinkedIn’s recent report ranks AI literacy as the top emerging skill people are adding to their profiles and a key attribute among recent hires. Zhao compares AI literacy to computer literacy—soon to be a baseline requirement across jobs. Those who can experiment and apply AI effectively will be in greater demand.
Stephany’s research shows that demonstrating AI skills signals to employers that you are proactive and ahead of technological trends. Relevant skills could include writing prompts for chatbots, debugging code, or using AI-powered tools like GitHub Copilot.
He also advises developing AI skills that complement your existing role. For example, business operations professionals don’t need to retrain as programmers but should learn to communicate effectively with AI and craft effective prompts. Finally, soft skills—such as team leadership and people management—that AI cannot replicate remain crucial and can enhance your value.