Automation Could Reshape 36 Million US Jobs by 2035

Automation will affect 36 million jobs in the United States by 2035, according to a new report cited by CNBC — roughly a fifth of the current workforce facing some form of technology-driven change over the next decade.

The figure anchors a growing body of labor-market research on how artificial intelligence and robotics will redistribute work rather than simply eliminate it. The report goes beyond the headline number to rank the ten occupations it considers most exposed, offering jobseekers and employers a concrete map of where disruption will concentrate.

What does 'affect' actually mean for workers?

Labor economists generally distinguish between job displacement — roles disappearing entirely — and job transformation, where routine tasks get automated while human work shifts toward supervision, judgment, and customer interaction. The 36 million figure covers the broader category: positions whose task composition will change materially, not necessarily roles that vanish.

For an individual worker, that distinction matters. A bookkeeper in 2035 may still hold a job, but the daily work will likely center on reviewing automated outputs and handling exceptions rather than manual data entry. Wages and hiring demand will follow the tasks that remain human, not the job title.

Which occupations face the highest exposure?

The report identifies ten occupations hit hardest by automation. Roles dominated by routine, repeatable tasks — data processing, scheduling, basic record-keeping, and standardized customer service — consistently rank at the top of exposure indexes across similar studies, because current AI systems and workflow software can perform those tasks reliably.

By contrast, occupations combining physical dexterity, unpredictability, and interpersonal judgment tend to rank lower. The spread between high- and low-exposure roles is where the real career-planning signal sits: workers in high-exposure occupations face a closing window to retrain toward adjacent, less automatable functions.

How should readers weigh a 2035 projection?

Forecasts with a 2035 horizon carry wide uncertainty bands. Projection methodologies typically extrapolate current technology adoption curves, task inventories from occupation databases such as O*NET, and employer surveys; they rarely anticipate breakthroughs or adoption bottlenecks. CNBC's coverage of the report does not specify the sample size or modeling assumptions, so readers should treat the 36 million figure as a scenario estimate, not a forecast of layoffs.

Still, the direction is consistent across the field. Studies from McKinsey, Goldman Sachs, and academic labor economists have all pointed the same way over the past several years: exposure is concentrated, measurable, and already visible in hiring patterns for the most routine-heavy roles.

What can an individual do with this data?

The practical read is role-level, not national. If your current job consists mostly of standardized information handling, the report implies compressed wage growth and weaker hiring demand over the next decade. Skills that pair domain knowledge with automation oversight — reviewing machine outputs, managing exceptions, communicating results — are the clearest hedge.

Employers in high-exposure sectors are already restructuring around this trajectory, which means internal mobility toward less automatable tasks is often easier than an external career pivot. Workers who move early, while their current role still provides income and training access, hold a stronger negotiating position than those who wait for displacement pressure to build.

The report's 2035 timeline gives the labor market a full decade to adjust — but the occupations named in it will likely see hiring shifts well before that deadline arrives.