Share and intensity of work current AI systems can materially affect.
SOC 29-1071
Physician Assistants AI displacement risk
PAs diagnose, prescribe, perform procedures, and manage patient panels — clinical judgment work that AI supports but cannot own. Documentation tools reduce charting burden while expanding scope-of-practice laws keep demand surging.
Likely potential for exposed tasks to move to software after workflow integration.
The PA role exists to extend physician capacity, and AI extends it further: the same tools that draft notes and suggest differentials make each PA more productive. Team-based care accountability stays human.
Distribution
Where Physician Assistants sits across 620 tracked roles
Displacement pressure 20 — higher than 23% of the 620 occupations tracked on displacement.ai.
Score version
This page uses Seed model v0.4 (seed-v0.4-2026-05), last reviewed 2026-08-08. Directional occupation-level planning model using hand-reviewed public research, task exposure estimates, wage context, and transition-pathway assumptions.
28 O*NET task statements matched to SOC 29-1071. The displayed task profile combines these official task statements with the current public score model.
Median wage context: $135,880 (May 2025, US national). The latest BLS row matched SOC 29-1071.
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 Physician Assistants
SOC 29-1071 places this role in the paper's cognitive occupation group. These group-level outcomes do not change the 20/100 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 Physician Assistants
The current evidence import matched 28 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 tasks28
SOC29-1071
- Core task / ID 4075
Make tentative diagnoses and decisions about management and treatment of patients.
- Core task / ID 4074
Interpret diagnostic test results for deviations from normal.
- Core task / ID 4078
Prescribe therapy or medication with physician approval.
- Core task / ID 4076
Obtain, compile, and record patient medical data, including health history, progress notes, and results of physical examination.
- Core task / ID 4073
Examine patients to obtain information about their physical condition.
- Core task / ID 4077
Administer or order diagnostic tests, such as x-ray, electrocardiogram, and laboratory tests.
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
Examine and diagnose patients
Exposure 34, automation 11%, augmentation 58%.
O*NET evidence: Make tentative diagnoses and decisions about management and treatment of patients. (ID 4075)
Perform therapeutic procedures
Exposure 20, automation 6%, augmentation 32%.
O*NET evidence: Perform therapeutic procedures, such as injections, immunizations, suturing and wound c... (ID 4079)
Document patient data and progress
Exposure 58, automation 28%, augmentation 72%.
O*NET evidence: Monitor and document patients' progress during post-anesthesia period. (ID 17303)
Counsel patients on treatment plans
Exposure 26, automation 7%, augmentation 46%.
O*NET evidence: Instruct and counsel patients about prescribed therapeutic regimens, normal growth and ... (ID 4080)
TaskExposureAutomationAugmentation
Examine and diagnose patients3411%58%
Perform therapeutic procedures206%32%
Document patient data and progress5828%72%
Counsel patients on treatment plans267%46%
Transition pathways
Adjacent moves that preserve existing skills
role redesign
LowLead Advanced Practice Provider
Training horizon: 3-6 months. Skill overlap 74. Wage preservation signal 112.
- Coordinate APP teams
- Own clinical protocols
- Mentor new PAs
credentialed transition
LowSurgical Physician Assistant
Training horizon: 6-12 months. Skill overlap 66. Wage preservation signal 114.
- Build OR first-assist experience
- Complete surgical training programs
- Master perioperative care
Comparison guides
Compare the next move before you commit
3-6 months
Physician Assistants to Lead Advanced Practice Provider
Compare AI displacement pressure, wage preservation, skill overlap, training time, and first proof project for moving from Physician Assistants into Lead Advanced Practice Provider.
6-12 months
Physician Assistants to Surgical Physician Assistant
Compare AI displacement pressure, wage preservation, skill overlap, training time, and first proof project for moving from Physician Assistants into Surgical Physician Assistant.
What the AI risk score means for Physician Assistants
The displacement pressure score for Physician Assistants is 20. 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. Document patient data and progress carries 28% automation pressure, while Document patient data and progress carries 72% 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: $135,880 (May 2025, US national). Employment context: One of the fastest-growing clinical professions. Typical education: Master's degree plus state licensure.
Wage vulnerability is 24, while transition feasibility is 68. 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.
- Low displacement pressure
- Among the fastest-growing roles tracked
- Scope expansion drives demand
Upskilling priorities
Skills that make this role more resilient
The safest upskilling plan starts with skills already close to the work. For Physician Assistants, 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.
Clinical diagnosis
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.
Procedure skills
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.
AI documentation review
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.
Team-based care
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 Lead Advanced Practice Provider, such as coordinate app teams.
- By 90 days, compare internal openings and external postings for Lead Advanced Practice Provider or Surgical Physician Assistant and update your resume around measurable workflow outcomes.
FAQ
Questions about AI and Physician Assistants
Will AI replace Physician Assistants?
PAs diagnose, prescribe, perform procedures, and manage patient panels — clinical judgment work that AI supports but cannot own. Documentation tools reduce charting burden while expanding scope-of-practice laws keep demand surging. 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 Physician Assistants work are most exposed to AI?
Document patient data and progress and Examine and diagnose patients show the strongest automation pressure in this model. Document patient data and progress and Examine and diagnose patients are better treated as AI-augmented work.
What should Physician Assistants learn next?
Start with Clinical diagnosis, Procedure skills, AI documentation review. The most practical adjacent paths in this model are Lead Advanced Practice Provider and Surgical Physician Assistant.
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
International Labour Organization / 20 May 2025Generative AI and Jobs: A Refined Global Index of Occupational ExposureOECD / 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