Will AI replace medical dosimetrists?

Not on current evidence. Less than 30 minutes of a typical shift goes to tasks that AI or robots are doing today. The other 8h (100%) stays with people. Separately, BLS expects about 5% more of these jobs by 2035 (all jobs: +3.5%).

None of this job's tasks show regular AI use yet. That can mean the work is hands-on or in person, or simply that it rarely comes up in AI usage data.

Not in workplaces like this one, based on a 2026 review of robot deployments. 2 more tasks have only been done in factory setups built around the machine, so they stay with people here.

8h of a typical shift, or 100%, goes to tasks with no AI or robot evidence yet. No AI usage or robot deployment has shown up for these so far. The biggest:

• Design the arrangement of radiation fields to reduce exposure to critical patient structures, such as organs, using computers, manuals, and guides. (1h 46m a shift)
• Identify and outline bodily structures, using imaging procedures, such as x-ray, magnetic resonance imaging, computed tomography, or positron emission tomography. (56m a shift)
• Develop radiation treatment plans in consultation with members of the radiation oncology team. (44m a shift)
• Plan the use of beam modifying devices, such as compensators, shields, and wedge filters, to ensure safe and effective delivery of radiation treatment. (37m a shift)
• Calculate the delivery of radiation treatment, such as the amount or extent of radiation per session, based on the prescribed course of radiation therapy. (37m a shift)

Much of it comes down to where and how the work happens. In-person, hands-on and high-stakes work is where AI and robots have made the least headway so far. In the official O*NET survey of people in this job:

• 95% say a mistake would be very or extremely serious
• 85% talk face to face with others every day
• 75% use their hands on tools, objects or controls more than half the time

On Indeed, job postings in the Medical Technician sector are at 125% of their February 2020 level (all U.S. postings: 104%), down 2.6% from a year earlier, as of Oct 9, 2026. BLS separately expects about 200 openings a year in this job through 2035. Across all U.S. postings, 7.3% now mention AI skills. Sector postings cover more than this one job and move for many reasons besides AI.

The median pay is about $147,470 a year ($70.90 an hour), 189% above the median for all U.S. jobs ($50,980). Most people in this job earn between $111,670 and $185,450 a year; that range covers the middle 80%. Pay figures are from BLS, May 2025, and vary a lot by state and employer. Pick a state to compare:

BLS projects growth of 5% from 2025 to 2035, compared with 3.5% growth for all jobs. That's about 3,700 jobs in 2035. It expects about 200 openings a year, mostly from people retiring or changing careers. These projections don't single out AI as a cause.

About 3,410 people in the U.S., roughly 0.00% of all workers (BLS, May 2025). That makes it the 750th largest of the 796 jobs on this site. BLS expects about 3,700 in 2035.

The most common requirement is a bachelor's degree: about 40% of people in the job said so in the official O*NET survey. O*NET rates the job at level 4 of 5 for preparation, which usually means: bachelor's degree. Requirements vary by state and employer, especially for licensed work.

These come from the job's official skill ratings and from the tasks that AI and robots touch least today. Building them keeps you strong in the parts of the work that still need a person:

• Skills that matter more here than in most jobs: Science, Mathematics, Critical Thinking, Time Management
• Get strong at the parts of the job that stay with people (listed above), which take 8h of a typical shift
• Tools employers list: Epic Systems, Eclipse IDE, MEDITECH software

These use similar skills. Matches come from 109 official ratings of skills, knowledge and work activities, and each needs the same or less preparation unless the official list relates the jobs directly:

• Radiologists (4h 26m touched, $421k median pay)

Each task carries its own evidence label. For this job: 1 with robots in real deployments, 18 with no AI or robot evidence found. The minutes per task are estimates, not measured hours, and "no evidence" doesn't prove a task is safe.