AI Automation Index

Will AI Replace Orthodontists?

Task-level automation exposure for Orthodontists: 11 O*NET tasks scored against their work activities, plus the simulator.

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Developed & audited by Gini Loh

Automation Exposure

32% weighted task index

11 of 11 tasks scored

Median Salary

$289,140 / year

BLS OEWS, May 2025 — this exact occupation

Employment Level

Low

6,210 people hold this job — size, not growth

Projected 2025–35

+6.0% employment change

200 openings a year · BLS line item

Pay by state

BLS OEWS publishes 19 state estimates for this occupation. Each is its own survey estimate, not the national median adjusted for local prices.

$159,230 – $478,680

Highest medians

Connecticut $478,680

Colorado $416,000

Maryland $361,030

Michigan $357,090

Illinois $343,100

Lowest medians

Georgia $159,230

New York $172,980

Wisconsin $212,860

Ohio $219,300

North Carolina $224,990

State figures come from the 29-1023 row in the May 2025 state panel. States where the estimate was suppressed or too small to publish are absent.

What the score is made of

Each task is mapped to its work activities, scored for AI automation potential, and weighted by how important those activities are to the job. These are the components.

Automation potential 32%

Importance-weighted mean of the scored tasks. This is the headline index.

Physical work 27%

Share of weighted tasks in hands-on or machine-operating work activities.

Judgment & influence 46%

Share in analysis, decisions, teaching, directing, advising, or caring for others.

Routine administration 9%

Share in documenting, recording, and administrative activities.

Rewritten by O*NET 0%

Share of weighted tasks O*NET rewrote in a recent update. Reported, not folded into the score.

Consequence of error 15/100 Low

O*NET's own rating of how serious an uncorrectable mistake would be here — respondents, not us. Deliberately not in the index: the score measures what AI can do with the task content, and multiplying it by stakes would be our judgment dressed as data.

Constituent Task Mix

11 tasks for this occupation, weighted by work-activity importance. Shares below are of total task weight, not task count.

High exposure (≥ 60% of the task is automatable) 9%

1 tasks

Medium exposure (≥ 35%) 36%

4 tasks

Low exposure (below 35%) 55%

6 tasks

How would you survive?

Move your week away from the high-exposure tasks and toward the ones that need judgment. The simulator recalculates the index as you shift the mix.

Simulate Upskilling →

Constituent Tasks

#7734 · Core · 30% automatable

Diagnose teeth and jaw or other dental-facial abnormalities.

visual inspection — Dental diagnosis needs imaging and clinical exam

Diagnose dental conditions.

#7735 · Core · 10% automatable

Examine patients to assess abnormalities of jaw development, tooth position, and other dental-facial structures.

visual inspection — Oral examination requires direct hands-on inspection

Examine mouth, teeth, gums, or related facial structures.

#7733 · Core · 55% automatable

Study diagnostic records, such as medical or dental histories, plaster models of the teeth, photos of a patient's face and teeth, and X-rays, to develop patient treatment plans.

decision support — Treatment goals need clinical accountability and context

Analyze patient data to determine patient needs or treatment goals.

#7732 · Core · 8% automatable

Fit dental appliances in patients' mouths to alter the position and relationship of teeth and jaws or to realign teeth.

physical manipulation — Fine manual adjustment of dental appliances in mouth

Adjust dental devices or appliances to ensure fit.

#7737 · Core · 8% automatable

Adjust dental appliances to produce and maintain normal function.

physical manipulation — Fine manual adjustment of dental appliances in mouth

Adjust dental devices or appliances to ensure fit.

#7738 · Core · 42% automatable

Provide patients with proposed treatment plans and cost estimates.

interpersonal — Medical communication needs empathy and clinical accountability

Communicate detailed medical information to patients or family members.

#23973 · Core · 47% automatable

Advise patients to comply with treatment plans.

decision support — Treatment-effect advice needs clinical tailoring

Confer with clients to discuss treatment plans or progress. Advise patients on effects of health conditions or treatments.

#7736 · Core · 62% automatable

Prepare diagnostic and treatment records.

interpersonal — Patient history requires live elicitation and judgment

Record patient medical histories.

#7739 · Core · 30% automatable

Instruct dental officers and technical assistants in orthodontic procedures and techniques.

interpersonal — Provider training is clinical, hands-on, accountable

Train medical providers.

#7740 · Core · 40% automatable

Coordinate orthodontic services with other dental and medical services.

interpersonal — Treatment planning collaboration is accountable clinical work

Collaborate with healthcare professionals to plan or provide treatment.

#7741 · Core · 19% automatable

Design and fabricate appliances, such as space maintainers, retainers, and labial and lingual arch wires.

decision support — AI assists concepts; device design requires regulatory and physical testing

Design medical devices or appliances. Fabricate medical devices.

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Community Sentiment

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Method

How this was scored

1. Tasks. O*NET task statements for this occupation, from a release whose newest record is dated 08/2026.
2. Work activities. Each task maps to 1–5 Detailed Work Activities; each activity belongs to one of 41 Generalized Work Activities that O*NET rates for importance (1–5) in this occupation.
3. Automation potential. Every work activity carries one score for how far current AI can perform it end-to-end. Tasks inherit the mean of their activities.
4. Weighting. Task weight = 0.35 + 0.65 × (importance − 1)/4, scaled by how often the task is performed and by 0.7 for Supplemental tasks. Importance is the task's own O*NET rating where it exists (18,369 of 18,838 tasks); the rest inherit their work activities' importance. The index is the weighted mean.

Check: across the 910 occupations where O*NET also rates how far machine speed sets the pace, this index moves opposite to it (Spearman ρ = -0.49). The more a job is paced by equipment, the less of its task content AI can address — the relationship you would expect if the scoring is working.

Sources · O*NET 31.0 (task records to 08/2026) · BLS OEWS May 2025 · BLS projections 2025-2035 · rubric v2.1 · tasks for O*NET, not a forecast

See the full method →

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