Share and intensity of work current AI systems can materially affect.
SOC 29-2036
Medical Dosimetrists AI displacement risk
Medical dosimetrists design radiation treatment plans, calculating dose distributions that maximize tumor coverage while sparing organs. Auto-contouring and auto-planning AI now draft plans in minutes — a genuine, deployed capability — making this one of the more exposed allied-health specialties, with verification and oncology-team consultation as the anchor.
Likely potential for exposed tasks to move to software after workflow integration.
The honest read is moderate-to-high task exposure: AI drafts, the dosimetrist verifies, adjusts, and defends the plan. Plan-quality accountability and edge-case anatomy keep the role, but the drafting hours are compressing now, not eventually.
Distribution
Where Medical Dosimetrists sits across 620 tracked roles
Displacement pressure 42 — higher than 70% of the 620 occupations tracked on displacement.ai.
Score version
This page uses Seed model v0.4 (seed-v0.4-2026-05), last reviewed 2026-08-15. Directional occupation-level planning model using hand-reviewed public research, task exposure estimates, wage context, and transition-pathway assumptions.
19 O*NET task statements matched to SOC 29-2036. The displayed task profile combines these official task statements with the current public score model.
Median wage context: $147,470 (May 2025, US national). The latest BLS row matched SOC 29-2036.
Scores are planning signals, not forecasts. Local hiring demand, employer-specific workflows, licensing, and credentials must be validated before making career decisions.
2030 economic stress test
How Anthropic's scenarios classify Medical Dosimetrists
SOC 29-2036 places this role in the paper's cognitive occupation group. These group-level outcomes do not change the 42/100 role score and are not an occupation forecast.
+0.4% group wage
-0.5% cognitive employment since mid-2026; 2.9% cognitive unemployment.
Economy-wide: +1.6% GDP and 3.9% unemployment.
-0.3% group wage
-3.9% cognitive employment since mid-2026; 4.5% cognitive unemployment.
Economy-wide: +8.3% GDP and 4.6% unemployment.
-11.5% group wage
-21.5% cognitive employment since mid-2026; 17.9% cognitive unemployment.
Economy-wide: +32.4% GDP and 11.9% unemployment.
Compare the assumptions and limitations across all three scenarios. Source: The Anthropic Institute Working Paper No. 2026-02.
Official task evidence
O*NET task matches for Medical Dosimetrists
The current evidence import matched 19 task statements from Task Statements 31.0 (August 2026). These rows are used as a grounding layer for judging which parts of the occupation are repeatable, language-heavy, analytical, social, physical, or compliance-sensitive.
Dataset31.0 (August 2026)
Matched tasks19
SOC29-2036
- Core task / ID 22837
Design the arrangement of radiation fields to reduce exposure to critical patient structures, such as organs, using computers, manuals, and guides.
- Core task / ID 22848
Plan the use of beam modifying devices, such as compensators, shields, and wedge filters, to ensure safe and effective delivery of radiation treatment.
- Core task / ID 22844
Identify and outline bodily structures, using imaging procedures, such as x-ray, magnetic resonance imaging, computed tomography, or positron emission tomography.
- Core task / ID 22834
Calculate the delivery of radiation treatment, such as the amount or extent of radiation per session, based on the prescribed course of radiation therapy.
- Core task / ID 22833
Calculate, or verify calculations of, prescribed radiation doses.
- Core task / ID 22838
Develop radiation treatment plans in consultation with members of the radiation oncology team.
Source: O*NET Resource Center, Task Statements. Raw import target: data/raw/onet/task-statements-31-0.txt.
Task profile
Where AI changes the work
Calculate delivery of radiation treatment per session
Exposure 58, automation 34%, augmentation 60%.
O*NET evidence: Calculate the delivery of radiation treatment, such as the amount or extent of radiatio... (ID 22834)
Design radiation field arrangements to spare organs
Exposure 52, automation 29%, augmentation 62%.
O*NET evidence: Design the arrangement of radiation fields to reduce exposure to critical patient struc... (ID 22837)
Identify and outline structures using imaging
Exposure 56, automation 33%, augmentation 60%.
O*NET evidence: Identify and outline bodily structures, using imaging procedures, such as x-ray, magnet... (ID 22844)
Develop treatment plans with the oncology team
Exposure 36, automation 16%, augmentation 56%.
O*NET evidence: Develop radiation treatment plans in consultation with members of the radiation oncolog... (ID 22838)
TaskExposureAutomationAugmentation
Calculate delivery of radiation treatment per session5834%60%
Design radiation field arrangements to spare organs5229%62%
Identify and outline structures using imaging5633%60%
Develop treatment plans with the oncology team3616%56%
Transition pathways
Adjacent moves that preserve existing skills
role redesign
ModerateChief Medical Dosimetrist
Training horizon: 6-12 months. Skill overlap 68. Wage preservation signal 114.
- Own plan-quality protocols
- Lead AI-planning validation
- Supervise dosimetry staff
credentialed transition
ModerateMedical Physics Resident
Training horizon: 24-36 months. Skill overlap 56. Wage preservation signal 134.
- Complete a physics graduate program
- Enter CAMPEP residency
- Earn ABR certification
Comparison guides
Compare the next move before you commit
6-12 months
Medical Dosimetrists to Chief Medical Dosimetrist
Compare AI displacement pressure, wage preservation, skill overlap, training time, and first proof project for moving from Medical Dosimetrists into Chief Medical Dosimetrist.
24-36 months
Medical Dosimetrists to Medical Physics Resident
Compare AI displacement pressure, wage preservation, skill overlap, training time, and first proof project for moving from Medical Dosimetrists into Medical Physics Resident.
What the AI risk score means for Medical Dosimetrists
The displacement pressure score for Medical Dosimetrists is 42. That score blends task exposure, automation pressure, augmentation potential, wage vulnerability, transition feasibility, and source confidence. It is designed to help workers and workforce teams decide where to act first, not to claim a specific date when a job will disappear.
For this role, the clearest risk pattern is visible at the task level. Calculate delivery of radiation treatment per session carries 34% automation pressure, while Design radiation field arrangements to spare organs carries 62% augmentation potential. That means the best response is usually a targeted redesign of work: move away from repeatable production tasks and toward judgment, exception handling, coordination, stakeholder context, and accountable use of AI tools.
Labor-market context and wage risk
Median wage: $147,470 (May 2025, US national). Employment context: Radiation-planning specialty where auto-contouring is genuinely strong. Typical education: Bachelor degree plus dosimetry program and MDCB certification.
Wage vulnerability is 26, while transition feasibility is 64. A high wage-vulnerability score means workers should pay close attention to salary preservation before making a move. A high transition-feasibility score means there are adjacent paths that can reuse existing skills without requiring a complete career reset.
- Moderate displacement pressure
- Auto-planning drafts plans in minutes
- Plan verification stays accountable
Upskilling priorities
Skills that make this role more resilient
The safest upskilling plan starts with skills already close to the work. For Medical Dosimetrists, the strongest near-term skill priorities are listed below. These are useful whether the goal is to stay in the role, move to a redesigned version of the role, or transition into an adjacent occupation.
Treatment planning
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
Radiation dose planning
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
Auto-contouring verification
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
Oncology collaboration
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
90-day transition plan
The most practical next step is not to wait for a layoff or a full role redesign. Use the next 90 days to create evidence that you can operate in a safer, more AI-augmented version of the work.
- In the first 30 days, document the repetitive tasks in your current work and identify where AI can reduce drafting, lookup, classification, or reporting time.
- By 60 days, complete one small project connected to Chief Medical Dosimetrist, such as own plan-quality protocols.
- By 90 days, compare internal openings and external postings for Chief Medical Dosimetrist or Medical Physics Resident and update your resume around measurable workflow outcomes.
FAQ
Questions about AI and Medical Dosimetrists
Will AI replace Medical Dosimetrists?
Medical dosimetrists design radiation treatment plans, calculating dose distributions that maximize tumor coverage while sparing organs. Auto-contouring and auto-planning AI now draft plans in minutes — a genuine, deployed capability — making this one of the more exposed allied-health specialties, with verification and oncology-team consultation as the anchor. The better planning signal is not full replacement, but which tasks become automated, which tasks become AI-assisted, and which responsibilities still need human judgment.
Which parts of Medical Dosimetrists work are most exposed to AI?
Calculate delivery of radiation treatment per session and Identify and outline structures using imaging show the strongest automation pressure in this model. Design radiation field arrangements to spare organs and Calculate delivery of radiation treatment per session are better treated as AI-augmented work.
What should Medical Dosimetrists learn next?
Start with Treatment planning, Radiation dose planning, Auto-contouring verification. The most practical adjacent paths in this model are Chief Medical Dosimetrist and Medical Physics Resident.
How should this score be used?
Use it as a planning signal, not a prediction. Confirm local hiring demand, wages, licensing, credentials, and employer adoption before making a career move.
Sources
Evidence trail
OECD / 11 July 2023OECD Employment Outlook 2023: Artificial Intelligence and the Labour MarketO*NET Resource Center / Database 31.0 (August 2026)Occupation, Task, Skill, and Work-Activity DataUS Bureau of Labor Statistics / May 2025 estimates (released 15 May 2026)Occupational Employment and Wage Statistics