CareerTown.ai News | October 2026
Artificial intelligence may be about to trigger one of the largest workforce transformations in American history.
Approximately 11 million U.S. workers could need to switch occupations by 2035 as artificial intelligence, automation and other economic forces reshape the labor market, according to a new report from the McKinsey Global Institute.
The number could range from 6 million to 16 million workers, depending on how rapidly businesses adopt automation and how the technology ultimately affects demand for human labor.
That doesn't necessarily mean America is heading toward a future without jobs.
In fact, McKinsey reaches a surprisingly different conclusion: the United States could have more jobs in 2035 than it has today.
The challenge will be whether workers who lose opportunities in declining occupations can acquire the skills, credentials and experience necessary to move into the occupations that are growing.
McKinsey estimates that AI and other forms of automation could reduce demand for labor equivalent to approximately 36 million jobs over the next decade.
But automation doesn't automatically translate into 36 million unemployed Americans.
Economic growth, new technology, changing demographics and increasing demand in other industries could generate demand equivalent to approximately 41 million jobs during the same period.
For roughly 25 million workers affected by automation, growth within their existing occupations could potentially offset technological displacement.
The remaining 11 million workers—approximately 7% of current U.S. employees—could need to change occupations entirely.
That distinction fundamentally changes the AI employment debate.
The central problem may not be that America runs out of jobs.
It could be that the jobs available in 2035 are substantially different from the jobs millions of Americans perform today.
Moving 11 million Americans into different occupations would require an enormous amount of career mobility.
McKinsey estimates approximately 770,000 workers per year could need to switch occupations over the coming decade—around 3.6 times the historical rate of occupational transitions.
Imagine the scale of that transformation.
Administrative assistants could move into healthcare support.
Retail employees could transition into skilled trades.
Customer-service representatives could move into sales, healthcare or technology-enabled service positions.
Transportation workers could retrain for infrastructure, construction or technical occupations.
And millions of existing professionals may remain in their occupations while seeing their actual responsibilities transformed by AI.
The defining workforce issue of the next decade may therefore become career transition rather than simply job destruction.
The disruption isn't expected to be evenly distributed throughout the economy.
McKinsey identifies office and administrative support, retail and sales, and transportation and logistics among the occupational categories facing significant pressure.
These occupations contain many repetitive or predictable tasks that software, robotics and increasingly capable AI systems can potentially automate.
The U.S. Bureau of Labor Statistics is seeing similar patterns in its own projections.
For example, BLS previously projected employment of customer-service representatives to decline 5.5% from 2024 to 2034, representing approximately 153,700 fewer positions. Procurement clerks were projected to decline 8.7%, while several categories of secretarial and administrative work were also expected to contract.
The message for workers isn't necessarily that these occupations will disappear.
Instead, fewer people may be required to perform the same amount of work.
One of the most concerning findings involves lower-income workers.
McKinsey estimates lower-wage employees could be approximately 7.6 times more likely than higher-wage workers to need to change occupations.
That creates a major economic challenge.
The people most likely to require retraining may also be the people least able to afford it.
A worker living paycheck to paycheck may find it extremely difficult to stop working for several months to obtain a credential, attend training or complete an apprenticeship.
Someone supporting children or caring for an elderly parent may be unable to relocate for a new opportunity.
Career transition therefore isn't simply a question of whether training programs exist.
Workers need realistic pathways that allow them to earn while they learn.
There is another side to the forecast.
McKinsey projects substantial employment growth in areas including healthcare, professional and technical services, construction and management.
Approximately 60% of employment growth could occur in occupations within the top two wage quintiles, according to the report.
Artificial intelligence itself could also create entirely new categories of work.
Companies will need people to implement AI systems, manage automated workflows, supervise AI agents, evaluate machine-generated information, maintain infrastructure and ensure that automated systems operate safely and effectively.
Some of tomorrow's fastest-growing jobs already exist.
Others may not have names yet.
Government projections provide additional evidence of where opportunities may develop.
The Bureau of Labor Statistics projects the U.S. economy will add approximately 5.9 million jobs between 2025 and 2035, increasing total employment from 170.3 million to approximately 176.2 million.
Technology-related occupations are among those positioned for particularly strong growth.
BLS has projected employment of data scientists to increase 33.5%, information security analysts 28.5%, operations research analysts 21.5%, computer and information research scientists 19.7%, and software developers 15.8% over its 2024–2034 projection period.
AI therefore presents a paradox.
It can eliminate demand for certain kinds of work while simultaneously increasing demand for workers capable of building, managing and working alongside the technology.
Changing occupations represents the most dramatic form of disruption.
But millions more Americans could experience a different kind of transformation.
Their job titles may remain the same while the work inside those jobs changes.
McKinsey estimates that more than 70% of workers could require some degree of reinvention.
An accountant may remain an accountant but increasingly supervise AI-generated analysis.
A recruiter may remain a recruiter but use AI agents to identify and communicate with candidates.
A salesperson may rely on AI for prospecting and account research.
A marketing professional may supervise AI-generated campaigns.
A manager may oversee teams consisting of both humans and AI agents.
In that environment, simply having years of experience may no longer provide the same competitive advantage.
Workers may increasingly be judged by how effectively they combine professional expertise with AI productivity.
For generations, workers were encouraged to develop expertise in a particular occupation.
The AI economy could require a different approach.
Future job security may depend increasingly on career mobility—the ability to transfer existing skills into new industries and occupations.
A worker's most important asset may not be a specific job title.
It could be the collection of skills underneath that title.
Communication.
Leadership.
Sales.
Problem solving.
Project management.
Technical knowledge.
Critical thinking.
Customer relationships.
AI literacy.
These capabilities can potentially travel between industries even when individual occupations decline.
That means workers may need to begin thinking less about protecting their current job and more about increasing their career adaptability.
Businesses also have a stake in making the transition successful.
Replacing millions of experienced workers isn't necessarily practical or economically desirable.
Companies could instead retrain existing employees for higher-value responsibilities.
An administrative employee who understands an organization deeply may be able to become an AI-enabled operations specialist.
A customer-service representative could transition into customer-success management.
A recruiter could become an AI-assisted talent strategist.
Internal training and apprenticeship programs could therefore become increasingly important.
Rather than asking:
"Which employees can AI replace?"
Forward-looking companies may benefit from asking:
"Which employees can AI make significantly more valuable?"
The McKinsey report ultimately offers neither a purely optimistic nor catastrophic prediction.
AI could generate enormous productivity gains.
The economy could create millions of jobs.
Many of those positions could pay more than the occupations being displaced.
But none of those benefits guarantee that an administrative assistant, cashier, driver or customer-service representative whose job disappears can easily become a healthcare worker, construction professional, manager or technology specialist.
That transition requires training.
It requires employers willing to hire people with transferable skills.
It requires educational institutions capable of responding quickly to changing labor demand.
And it requires workers to recognize changes in their occupations before those changes become unemployment.
The headline surrounding artificial intelligence shouldn't simply be:
"AI is taking jobs."
A more accurate warning may be:
"AI is changing where the jobs are."
That difference matters.
McKinsey's research suggests approximately 11 million Americans may need to find an entirely different occupation by 2035. But it also suggests that the American economy could generate enough new opportunities to absorb that disruption.
The challenge is connecting those two sides of the labor market.
Workers need to understand which occupations are declining.
They need visibility into where opportunities are growing.
They need to identify which of their existing skills transfer into those opportunities.
And increasingly, they need to understand how artificial intelligence can make them more productive within their next career.
The defining employment skill of the next decade may therefore be neither coding nor prompting.
It may be reinvention.
Because in an economy transformed by artificial intelligence, the workers best positioned to succeed may not necessarily be those who protect their current jobs the longest.
They may be the people who recognize where work is heading—and move there first.
CareerTown.ai — Connecting Talent, Technology and Opportunity in the AI Economy.
