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McKinsey Global Institute projects that AI and other forces could generate more U.S. job demand than automation reduces by 2035—but that net gain does not mean workers will be spared disruption. In its 2026 base case, the institute estimates 41 million jobs of demand against an automation-related reduction equivalent to about 36 million jobs. At the same time, about 11 million workers may need to change occupations. These are projections, not observed job losses or guaranteed new hires.
What McKinsey’s forecast says—and what it doesn’t
McKinsey Global Institute’s September 29, 2026 report, Workforce in motion: Skills and pathways to future jobs in the United States, estimates that by 2035 the U.S. economy could see 41 million jobs of demand and an automation-related labor-demand reduction equivalent to about 36 million jobs. The base-case arithmetic is roughly five million more jobs of demand than jobs reduced by automation.
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That is a net estimate across the economy, not a promise that five million particular people will find work. The jobs created and the jobs reduced may be in different occupations, places, and years. Nor does the estimate mean AI alone creates all the demand: McKinsey includes changes driven by care and aging, construction and infrastructure, energy, technology services, and new occupations, alongside automation.
The report’s authors caution that “Counting jobs is an insufficient measure of the impact of new technology.” A net total cannot show who bears the costs of moving between jobs, whether new roles preserve pay, or whether workers can qualify for them.
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Why a net gain can still mean millions of career changes
McKinsey estimates about 11 million workers—roughly 7 percent of current employees—may need to move into different occupations by 2035. It also estimates that about 25 million workers affected by automation could remain in their current occupations as growth in those occupations offsets reduced labor demand. Staying in the same occupation does not necessarily mean doing the same tasks: many roles may be reshaped.
The 11 million figure is a modeled base-case estimate, not a count of people certain to be laid off. Across scenarios that vary adoption speed and how much automation reduces labor demand, McKinsey estimates that roughly 6 million to more than 16 million workers could need occupational transitions. The report does not present that range as a statistical confidence interval.
In the base case, the scale works out to about 770,000 workers a year changing occupational groups over the next decade, which McKinsey estimates is around 3.6 times its historical average. More than 75 percent of workers who may need to transition are concentrated in office and administrative support, retail and sales, and transportation and logistics.
Automation potential is not the same as jobs eliminated
McKinsey estimates that automation technologies could absorb about 54 percent of current work hours by 2035. That does not translate one-for-one into job losses. The report models organizational and market responses—such as using freed capacity to produce more, redesign workflows, oversee systems, or reduce excess hours—as offsetting about 60 percent of automation’s labor impact. Its resulting estimate of labor-demand reduction is equivalent to about 21 percent of current work hours.
The analysis starts from a 2025 baseline and uses U.S. Bureau of Labor Statistics occupational categories, mapped to Lightcast’s more detailed occupation taxonomy. McKinsey anchors total employment growth to BLS projections of approximately 3.1 percent over a decade, then models how demand may be distributed across occupations as automation and other forces change work.
The transition estimate depends especially on two uncertainties: how quickly organizations adopt automation and how much they use it to substitute for labor rather than augment it. Faster adoption combined with greater substitution raises the modeled need for occupational moves; slower adoption or more augmentation lowers it. The figures describe possible futures, not measured outcomes.
Which kinds of work may shrink or grow?
McKinsey sees potential declines concentrated in office and administrative support, retail and sales, and transportation and logistics. Potential growth is concentrated in healthcare, construction, and management, as well as infrastructure, energy, technology, and digital services. These are broad occupational groupings: different jobs within the same group can have very different task mixes, and a role may change without disappearing.
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The catch: growing jobs may not be reachable directly
Having more demand overall does not make workers interchangeable. A worker whose role contracts may lack the skills, credentials, experience, location, or time needed to enter a growing occupation. McKinsey evaluates pathways by factors including skill adjacency, wage preservation, destination demand, and the time needed to earn credentials. It describes routes as direct, winding, or unpaved, with licensing, degree, geographic, and language barriers capable of blocking an otherwise plausible move.
Only about one in seven workers who may need to transition is estimated to have a direct path to growing work with little or no retraining. Nearly half may face an “unpaved” path. McKinsey estimates that about 85 percent of growing jobs require credentials or certifications, so the headline job-demand gain cannot by itself answer whether workers can make the transition.
For workers considering a move, the relevant question is not just whether a field is growing. It is whether a specific destination job is accessible from their current experience, whether its pay is workable, and what training or licensing it requires. The report’s authors put the broader challenge this way: “The next decade’s challenge is mobility, not scarcity.”
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What to take from the forecast
- More job demand than automation-related reductions is possible. McKinsey’s base case projects a net gain in U.S. job demand through 2035, but it remains a model, not a realized outcome.
- Disruption is not evenly distributed. The report expects occupational transitions to cluster in office support, retail and sales, and transportation and logistics.
- Access matters as much as the aggregate count. Credentials, skill gaps, wages, geography, and timing can make a growing occupation difficult to reach.
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