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In McKinsey Global Institute’s 2026 U.S. forecast, AI and other automation are associated with more job demand created than reduced by 2035—but that does not mean every affected worker will find a suitable new job. The report estimates that about 41 million jobs of demand could be created and automation could reduce labor demand by the equivalent of about 36 million jobs, a modeled net difference of roughly five million. At the same time, about 11 million workers may need to move into different occupations.
What McKinsey’s forecast says—and what it doesn’t
McKinsey Global Institute’s Workforce in motion: Skills and pathways to future jobs in the United States, published September 29, 2026, models U.S. employment through 2035. Its base case estimates 41 million jobs of demand created and an automation-related reduction equivalent to about 36 million jobs. Subtracting the latter from the former gives roughly five million more jobs of demand.
These are projections, not a count of jobs already created or lost. “Demand created” does not mean a guaranteed opening for a particular worker, and the two totals do not identify whether the people facing reduced demand will be the ones filling new roles. The forecast also covers forces beyond AI, including demographic change, care needs, investment in construction and energy, and technology-related activity.
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The report’s authors write, “Counting jobs is an insufficient measure of the impact of new technology.” The net total says little by itself about which occupations will expand, what qualifications they will require, or whether workers can reach them without losing income.
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McKinsey estimates that about 11 million workers—roughly 7 percent of current employees—may need to change occupations by 2035. Its scenarios range from about 6 million to more than 16 million, depending on how quickly organizations adopt automation and how strongly it reduces demand for labor. The range is scenario-dependent, not a statistical confidence interval.
That 11 million figure is not a prediction that 11 million people will be laid off. The report estimates occupational transitions: workers may need to move because demand changes, even if they are not dismissed. It also estimates that about 25 million affected workers could remain in their current occupation as growth offsets automation-related reductions, though their tasks may change. On average, about 770,000 workers a year may need to switch occupational groups through the next decade—about 3.6 times McKinsey’s reported historical average.
More than 75 percent of workers who may need to change occupations are concentrated in three broad groups:
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- Office and administrative support
- Retail and sales
- Transportation and logistics
Broad occupational categories can hide very different tasks. Automation may change how a job is done without eliminating the occupation, while a growing occupation may still have tasks or roles that are reduced.
How automation’s technical potential translates into job demand
The report estimates that automation technologies could absorb about 54 percent of current U.S. work hours by 2035. That is a measure of technical potential, not a forecast that 54 percent of jobs will disappear. McKinsey models organizational and market responses as offsetting about 60 percent of automation’s labor impact; its resulting estimate is a reduction equivalent to about 21 percent of current work hours.
The distinction matters because automating a task does not automatically remove a job. An employer could use the time saved to produce more, reduce excess hours, add oversight, redesign workflows, or assign workers other tasks. How much of that capacity becomes lower labor demand is one of the forecast’s key uncertainties.
McKinsey’s model starts from a 2025 occupational baseline, uses the U.S. Bureau of Labor Statistics’ Standard Occupational Classification and maps it to Lightcast’s more granular occupation taxonomy. It anchors total employment growth to BLS projections of approximately 3.1 percent over a decade, then estimates how demand may be distributed across occupations as automation and other forces act. That makes the results a modeled allocation of projected demand, not a separate measurement of future total employment.
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McKinsey projects potential declines concentrated in office and administrative support, retail and sales, and transportation and logistics. It sees potential growth concentrated in healthcare, construction, and management, alongside demand connected to infrastructure, energy, technology, and digital services. The report groups growth drivers into a “human economy” (including aging, care, and rising living standards), a “physical economy” (including construction, infrastructure, and energy investment), and a “technology economy” (including digital and AI infrastructure and services). Some drivers depend on investment cycles and remain uncertain.
The report’s estimates also point to a distributional challenge: 60 percent of growing employment could be in the top two wage quintiles, while more than 70 percent of declining employment could be in the bottom two. It estimates that 84 percent of growing occupations require postsecondary education, compared with 45 percent of declining occupations. These are McKinsey’s projected occupational patterns, not observed results or a guarantee that an individual can move between the groups.
Why the transition pathway matters more than the job total
A growing role is not necessarily an accessible alternative for someone whose current work is under pressure. McKinsey assesses pathways using destination demand, overlap between current and required skills, the likelihood of preserving wages, and the time needed to earn credentials. It describes routes as direct, winding, or unpaved. Licensing, degree requirements, location, and language can block a move that looks plausible on a job-title chart.
Only about one in seven workers who may need a transition has a direct pathway to growing work with little or no retraining, according to the report. Almost half may face an “unpaved” path. McKinsey estimates that about 85 percent of growing jobs require credentials or certifications, which can add cost and time before a worker can qualify.
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1Fix the driver behind crashes, sound loss and screen glitches2Repair Windows errors before they cause bigger problems3Scan for outdated or missing drivers - takes under a minuteFor a worker considering a move, the useful question is therefore not simply whether the destination occupation is growing. Check the requirements and trade-offs together:
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- Demand: Is the occupation projected to grow in the location where you can work?
- Skills: Which of your existing skills transfer, and which must be learned?
- Credentials: Does the role require a license, degree, certificate, or other formal qualification?
- Time and pay: How long will qualification take, and is the likely wage sufficient during and after the transition?
- Access: Are the relevant jobs reachable given geography, experience, and other barriers?
McKinsey’s authors summarize the challenge this way: “The next decade’s challenge is mobility, not scarcity.” That is a statement about the report’s modeled U.S. labor-market outlook through 2035, not a promise that growth will be evenly shared or easy to reach.
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The transition estimate is most sensitive to two factors identified by McKinsey: the pace at which organizations adopt automation and the degree to which adoption reduces labor demand. Faster adoption and more substitution raise the modeled need for occupational transitions; slower adoption or more augmentation lower it. The report’s scenario range captures those different assumptions, while broader economic forces and investment patterns also affect which occupations grow.
The figures should be read as a guide to possible scale and direction, not a precise prediction for an individual worker, a particular employer, or every U.S. region. McKinsey’s report is a forecast based on stated modeling choices; its 2035 outcomes remain uncertain.
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