Eleven million American workers face a stark choice in the coming decade. They must move into entirely new occupations as artificial intelligence and automation reshape the economy. Or risk falling behind.
That figure comes from fresh analysis by the McKinsey Global Institute. Released late last month, the 82-page study projects that automation could reduce labor demand by the equivalent of 36 million jobs by 2035. Yet growth in the broader economy and AI-related sectors should generate demand for more than 40 million positions. Net, the United States ends up with more jobs than today. But fewer workers, thanks to an aging population.
The real test lies in the shift itself. Of those 36 million affected roles, about 25 million workers can likely stay within their current occupations as industry expansion absorbs some automation pressure. The remaining 11 million, roughly 7 percent of the workforce, will need to switch occupations completely. The range spans 6 million to 16 million depending on how fast companies adopt the technology.
Workforce mobility emerges as the central test ahead.
Historically, about 215,000 U.S. workers switch occupational groups each year. The McKinsey projections demand roughly 770,000 such moves annually. That pace runs 3.6 times the long-term average. It even exceeds the churn seen during the pandemic years. “The next decade’s challenge is mobility, not scarcity,” the report states (McKinsey Global Institute).
Low-wage workers bear the heaviest load. They prove 7.6 times more likely than higher earners to need an occupational change. More than 75 percent of those who must move cluster in three areas: office and administrative support, retail and sales, and transportation and logistics. Think customer service representatives, cashiers, retail sales associates, office assistants and warehouse workers. Automation could handle 81 percent of hours in office support roles and high shares elsewhere.
Growth concentrates elsewhere. Healthcare, construction and management occupations stand to add millions. Roughly 60 percent of new employment lands in the top two wage quintiles. These roles often demand more advanced skills. In contrast, more than 70 percent of declining employment sits in the bottom two quintiles. The mismatch creates friction. Only one in seven displaced workers enjoys a direct pathway to a growing job with comparable pay and minimal retraining.
Six of seven affected workers will require substantial retraining. Many will absorb income loss during the transition. Tanguy Catlin, a McKinsey Global Institute director, highlighted the difficulty in a CNBC interview. “To get those credentials may require an investment of time and an investment of money, and that will be source of friction” for workers (CNBC).
Fortune covered the findings days after the report dropped. It emphasized how AI could create more positions than it eliminates yet still demand massive workforce help this decade (Fortune).
Bloomberg put the human stakes plainly. An AI jobs apocalypse may not loom as the primary threat. Instead, the bigger hurdle involves moving millions into new roles. The transition will prove tough (Bloomberg).
CNN Business reported the same core numbers. It noted the shift “may require the largest and most sustained workforce transformation in US history.” The outlet stressed that social media overflows with dire predictions. Yet the country should have more jobs available in 2035 than today (CNN Business).
Recent coverage adds nuance. A Quartz article on Sept. 30 pointed out that lower-wage workers face outsized risk while growth favors healthcare and construction (Quartz). Crypto Briefing on Oct. 3 observed that only one in seven displaced workers holds a direct path into expanding fields. The piece called mobility the hard part even as net job creation looks positive (Crypto Briefing).
Discussions on X this week echo the report. Users highlighted the 770,000 annual transitions needed and questioned whether current labor market data and retraining systems can keep up. One post noted AI fluency requirements in job postings have surged 11 times since 2022. Another flagged that office and admin roles could see automation claim 80 percent of hours.
The McKinsey team examined skills and barriers that shape pathways to growing occupations. They drew on previous waves of general-purpose technologies. AI itself could spawn 500,000 to 2 million jobs in brand-new roles. These might involve AI infrastructure, agent engineering, workflow design, governance, human oversight and evaluation.
Yet pathways don’t always align neatly. Workers from declining fields often lack the exact credentials or experience that healthcare providers or construction managers seek. Location matters too. Pay differences can deter moves. And many simply don’t know which opportunities exist or how to prepare.
Education systems built for young students won’t suffice. Catlin has called for updated retraining programs aimed at existing workers. Better, timely labor market data from governments could help. So could targeted funding for skills development. The report stops short of detailed policy prescriptions. It does make clear that without action the friction will mount.
Broader economic forces compound the picture. Baby boomer retirements shrink the labor pool. Net immigration has slowed. Recent shocks still ripple. The labor market already shows low hiring and low firing in many sectors. Voluntary quits sit near multi-year lows. Against that backdrop, tripling occupational switches demands serious coordination.
Some roles will evolve rather than vanish. Cashiers might shift from transaction processing toward customer engagement and AI system oversight. Administrative staff could focus more on complex problem solving while automation handles routine tasks. About 70 percent of U.S. workers may need some level of role reinvention even if they stay put.
The analysis builds on McKinsey’s earlier forecasts. A 2023 projection estimated 12 million career switches by 2030. The new work extends the horizon to 2035 and incorporates faster AI adoption assumptions. Uncertainty remains high. Faster automation or deeper labor demand cuts could push the transition figure toward the upper end of the range.
Executives and policymakers now confront concrete numbers. Companies must weigh productivity gains from AI against the cost of workforce upheaval. They may need to invest in internal training pipelines or partner with community colleges. Governments face pressure to modernize workforce systems built for an earlier era.
Workers themselves hold varying degrees of agency. Those with flexible skills or access to education stand better positioned. Others, particularly in vulnerable occupations and regions, will need support. The report’s message lands clearly. Jobs won’t disappear overall. But the map of where they sit and what they require will change dramatically.
And that change arrives faster than the economy has historically managed. The United States has absorbed technological shifts before. This one tests the speed and scale of adaptation like never before.