Dentists, General

29-1021.00

Median wage $170,950/yr124,390 employed (US)Rank #778 of 923 scored · top 84% by substitution

Examine, diagnose, and treat diseases, injuries, and malformations of teeth and gums. May treat diseases of nerve, pulp, and other dental tissues affecting oral hygiene and retention of teeth. May fit dental appliances or provide preventive care.

Sub-scores

0–100 · band = confidence interval from rater disagreement

Substitution16

Exposure17

Augmentation45

Substitution — the headline: capability discounted by cost, barriers and adoption.

Exposure — technical capability alone, regardless of whether anyone deploys it.

Augmentation — how much AI assists without replacing. High here + moderate substitution = a changing job, not a disappearing one.

Tasks on the substitution scale

20 rated tasks, binned by substitution score.

Position among all scored occupations

Distribution of 923 occupation scores; the marker is this occupation.

Tasks with substitution ≥ 70

Run 1.0.0-draft.1 · computed 2026-08-05 · rater panel: claude-sonnet-5, claude-haiku-4-5-20251001 · intervals span rater disagreement.

Why this score

The five weighted dimensions of the composite, averaged across this occupation's tasks (importance-weighted, panel mean). Exact weights and formulas: /api/v1/methodology.

Task automatabilityw 35%16

panel mean rating 1.6/5 → substitution pressure 16/100

Technical feasibility todayw 20%18

panel mean rating 1.7/5 → substitution pressure 18/100

Cost vs. human wagew 15%19

panel mean rating 1.7/5 → substitution pressure 19/100

Adoption barriersw 20%inverted — strong barriers lower the score11

panel mean rating 4.5/5 (barrier strength) → substitution pressure 11/100

Sector adoption velocityw 10%14

panel mean rating 1.6/5 → substitution pressure 14/100

Task breakdown (20 tasks)

Substitution pressure per task, weighted by O*NET importance in the composite. Expand a task for the full rater audit trail — every rating, every model, every rationale.

Manage business aspects such as employing or supervising staff or handling paperwork or insurance claims.

CI 50–79 · exposure 62 · augmentation 75 · importance 4.2/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	4/5	Dental practices, being small business service providers in the digital economy, show strong adoption of practice management software and automation tools. Industry conferences and professional associations actively promote these systems, and financial pressures drive uptake.
Sector adoption velocity	claude-sonnet-5	3/5	Small dental practices are moderate adopters of practice management and billing software, but broader business management automation adoption is uneven and pilot-stage in this sector.
Augmentation potential	claude-haiku-4-5-20251001	4/5	AI-powered practice management tools substantially augment dentists and office managers by automating routine claims submission, eligibility checking, appointment reminders, and payroll processing, freeing time for strategic decisions and staff interaction.
Augmentation potential	claude-sonnet-5	4/5	AI-powered scheduling, billing, and claims software meaningfully boosts efficiency for administrative aspects of running a practice, even though human oversight of staff remains essential.
Task automatability	claude-haiku-4-5-20251001	4/5	Business management tasks like payroll, scheduling, insurance claims processing, and routine paperwork can be substantially automated with AI-powered HR and accounting software. Current systems can handle 60–80% of administrative load, though staffing decisions and complex personnel issues still require human judgment.
Task automatability	claude-sonnet-5	3/5	Paperwork, scheduling, and insurance claims processing can largely be automated with existing software, but employing/supervising staff requires human judgment and interpersonal management that current AI cannot perform end-to-end.assistant
Adoption barriers	claude-haiku-4-5-20251001	3/5	Moderate barriers exist: insurance claims require compliance with payer-specific rules and HIPAA regulations, dental practices often have legacy system integration friction, and some practices prefer human judgment on staffing decisions. No legal requirement mandates a human handle these tasks, but integration complexity and change management slow adoption.
Adoption barriers	claude-sonnet-5	2/5	No licensing requirement mandates a human for billing or admin tasks, though employment law and liability for hiring/firing decisions create some organizational friction.
Cost vs. human wage	claude-haiku-4-5-20251001	5/5	AI-powered practice management systems cost a fraction of a full-time office manager or administrative staff member, with monthly subscriptions typically under $1,000 versus $50,000+ annually for hired administrative labor.
Cost vs. human wage	claude-sonnet-5	3/5	Claims/paperwork automation is cheap relative to staff time, but the supervisory/HR component still requires human labor, keeping the blended cost roughly comparable to hiring an office manager.
Technical feasibility today	claude-haiku-4-5-20251001	4/5	Mature products for dental practice management (Dentrix, Eaglesoft, Curve, etc.) and general business automation (Zapier, UiPath, accounting platforms) are deployed at scale in dental practices today, reliably handling claims, payroll, scheduling, and document management.
Technical feasibility today	claude-sonnet-5	3/5	Practice management software and insurance claim automation tools are deployed widely in dental offices, but staff supervision and hiring decisions remain manual, so the composite task is only partially covered by mature products.

Produce or evaluate dental health educational materials.

CI 47–69 · exposure 50 · augmentation 88 · importance 3.4/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	2/5	Dentistry is a traditionally low-tech sector with limited digital infrastructure and slower AI adoption compared to information-intensive industries; while some practices experiment with AI content tools, mainstream production adoption remains limited.
Sector adoption velocity	claude-sonnet-5	2/5	Dental practices are mostly small businesses with lower digitization and slow AI tool adoption relative to information-sector firms, so uptake for this ancillary task is still nascent.
Augmentation potential	claude-haiku-4-5-20251001	4/5	AI can substantially assist dentists by drafting content, generating multiple variations, evaluating clarity and tone, and suggesting evidence-based improvements, significantly speeding up material development while the dentist maintains critical control over accuracy and messaging.
Augmentation potential	claude-sonnet-5	5/5	AI can rapidly draft, translate, simplify, or evaluate readability of dental health materials, letting the dentist focus on final clinical vetting rather than writing from scratch.
Task automatability	claude-haiku-4-5-20251001	2/5	AI can generate draft dental health content and assist with evaluation frameworks, but producing comprehensive, clinically accurate, patient-appropriate educational materials requires substantive human dental expertise and judgment to ensure safety and pedagogical effectiveness.
Task automatability	claude-sonnet-5	4/5	Producing or evaluating patient-facing dental health educational content (brochures, handouts, web copy, videos scripts) is largely text/content generation that current LLMs handle well, though final clinical accuracy review still needs a human., cutting drafting time substantially.
Adoption barriers	claude-haiku-4-5-20251001	2/5	Educational materials often require licensure sign-off or review by licensed dental professionals for regulatory or liability reasons, and clinical accuracy concerns create moderate friction, but no absolute legal bar prevents AI-assisted production if a dentist signs off.
Adoption barriers	claude-sonnet-5	2/5	No license is required to write patient education materials, though a dentist typically reviews content for clinical accuracy before distribution, creating light oversight friction.
Cost vs. human wage	claude-haiku-4-5-20251001	4/5	AI tools for content generation are inexpensive per use (fractions of a dollar), whereas a dentist's time costs $50–150+ per hour; even with overhead and review time, AI assistance significantly undercuts human-only production.
Cost vs. human wage	claude-sonnet-5	5/5	Drafting educational materials via an LLM costs pennies compared to a dentist's or staff's hourly billing rate, making AI drastically cheaper per unit of output.
Technical feasibility today	claude-haiku-4-5-20251001	3/5	LLMs and generative AI tools can create and evaluate educational content, and some dentists use them for drafting, but material error rates in clinical accuracy and lack of specialized educational validation mean no mature product reliably handles this end-to-end without expert review.
Technical feasibility today	claude-sonnet-5	3/5	Generic AI writing tools reliably draft health education content today, but no dentistry-specific product is widely deployed in practice for this narrow task; most use is ad hoc via general LLMs.

Analyze or evaluate dental needs to determine changes or trends in patterns of dental disease.

CI 25–80 · exposure 58 · augmentation 75 · importance 4.2/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	3/5	Dental practices are adopting AI imaging analysis slowly compared to other professional services; pilots are common but production deployment remains mixed across solo and group practices. Integration typically still requires dentist review rather than autonomous operation.
Sector adoption velocity	claude-sonnet-5	2/5	Dental practice is a physical, small-business-dominated sector with historically slow AI adoption outside of imaging diagnostics pilots.
Augmentation potential	claude-haiku-4-5-20251001	4/5	AI-assisted disease detection substantially augments a dentist's productivity by highlighting lesions and trends automatically, reducing reading time and improving consistency, while the dentist retains clinical judgment and patient communication responsibility.
Augmentation potential	claude-sonnet-5	4/5	AI-driven analytics and imaging tools can meaningfully help dentists identify patterns, flag anomalies, and analyze population trends, enhancing but not replacing their judgment.
Task automatability	claude-haiku-4-5-20251001	5/5	Current AI systems can analyze dental imaging (X-rays, intraoral scans) to detect caries, periodontal disease, and other pathology with diagnostic accuracy matching or exceeding human dentists. Trend analysis in disease patterns from longitudinal data can be automated end-to-end with >50% time savings using off-the-shelf computer vision and data analytics systems.
Task automatability	claude-sonnet-5	2/5	This requires clinical examination, judgment, and synthesis of population or patient-level dental health data that current AI cannot autonomously perform end-to-end, though it can assist with data analysis components.
Adoption barriers	claude-haiku-4-5-20251001	3/5	Dentists are licensed professionals, and licensure laws typically require a licensed dentist to examine the patient and make clinical decisions; however, AI increasingly performs triage and screening with human sign-off. Liability and oversight requirements create moderate friction but do not prevent AI deployment.
Adoption barriers	claude-sonnet-5	4/5	Dental diagnosis and disease-trend interpretation are tied to licensed professional judgment and liability, creating strong professional and regulatory barriers to full automation.
Cost vs. human wage	claude-haiku-4-5-20251001	5/5	AI inference on dental images costs pennies per scan, plus minimal integration overhead, versus a dentist's loaded wage of $50–100+ per hour for analysis time. The cost ratio is one or two orders of magnitude in AI's favor.
Cost vs. human wage	claude-sonnet-5	2/5	AI tools can cheaply process imaging or records data, but the full analytic and epidemiological judgment task still requires costly human clinical expertise, keeping overall cost comparable to or higher than pure AI substitution.
Technical feasibility today	claude-haiku-4-5-20251001	4/5	FDA-cleared and clinically validated AI products for dental disease detection (e.g., AI-powered caries and periodontitis screening tools) are deployed in dental practices today with demonstrated reliability. Minor gaps remain in rare conditions and comprehensive trend forecasting, but core disease analysis is production-ready.
Technical feasibility today	claude-sonnet-5	2/5	Some dental analytics and imaging AI products exist for cavity/disease detection, but no deployed product independently evaluates broader trends or patterns of dental disease at the level implied by this task.

Plan, organize, or maintain dental health programs.

CI 25–30 · exposure 25 · augmentation 63 · importance 3.6/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	2/5	Dental practices remain relatively traditional and small-business-oriented, with slower digital transformation compared to information-intensive sectors. While practice management software adoption is growing, AI-driven program planning and maintenance adoption remains limited and largely pilot-stage in the dental sector.
Sector adoption velocity	claude-sonnet-5	2/5	Healthcare administrative planning sees slow AI adoption due to regulatory, clinical, and organizational complexity compared to fast-adopting sectors like finance or tech.
Augmentation potential	claude-haiku-4-5-20251001	3/5	AI can assist dentists with data analysis, literature review, scheduling optimization, and draft documentation for health programs, improving productivity on planning tasks. However, the augmentation is limited to analytical and administrative components; strategic judgment and organizational leadership remain primarily human-driven.
Augmentation potential	claude-sonnet-5	4/5	AI can meaningfully assist with data analysis, trend identification, scheduling optimization, and report generation to support programmatic planning decisions.
Task automatability	claude-haiku-4-5-20251001	2/5	Planning and organizing dental health programs requires understanding organizational context, stakeholder needs, regulatory compliance, and strategic decision-making. While AI can assist with data analysis and draft documentation, the human judgment needed for program design, resource allocation, and organizational leadership cannot be fully automated to the 50% time-saving threshold.
Task automatability	claude-sonnet-5	2/5	Program planning involves strategic judgment, resource allocation, and stakeholder coordination that current AI can support but not autonomously execute end-to-end at equal quality.
Adoption barriers	claude-haiku-4-5-20251001	4/5	Dental health programs typically require a licensed dentist to plan and oversee them due to professional standards, regulatory requirements (state dental boards, public health regulations), and liability concerns. Organizational policies and professional licensing create meaningful legal and institutional barriers to full automation.
Adoption barriers	claude-sonnet-5	3/5	No strict licensing requirement for program planning itself, but organizational accountability and professional judgment create moderate friction against full automation.
Cost vs. human wage	claude-haiku-4-5-20251001	2/5	AI tools for program planning and organization require significant integration, customization, and oversight by experienced dental professionals. The total cost of deployment and human supervision remains comparable to or exceeds the cost of a dentist performing these tasks directly.
Cost vs. human wage	claude-sonnet-5	2/5	Human administrators/dentists remain necessary for decision-making and oversight, so AI mainly supplements rather than replacing the cost of the labor involved.
Technical feasibility today	claude-haiku-4-5-20251001	2/5	No deployed product reliably performs end-to-end dental health program planning and maintenance independently. Tools exist for scheduling and record management, but the strategic planning, organizational coordination, and maintenance aspects require human dentist expertise and decision-making that current AI systems do not demonstrate in production.
Technical feasibility today	claude-sonnet-5	2/5	AI tools can assist with data analysis or drafting program materials, but no deployed product independently plans or maintains dental health programs in practice.

Advise or instruct patients regarding preventive dental care, the causes and treatment of dental problems, or oral health care services.

CI 25–29 · exposure 25 · augmentation 75 · importance 4.5/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	2/5	Dental practices are moderately digitized but slower than finance or tech sectors. Patient education via AI is in pilot phases; few practices have deployed autonomous advisory systems in production. Regulatory and liability caution slows real-world uptake.
Sector adoption velocity	claude-sonnet-5	2/5	Healthcare/dental practices are historically slow AI adopters for patient-facing clinical communication, though administrative AI tools are spreading faster than clinical advice tools.
Augmentation potential	claude-haiku-4-5-20251001	4/5	AI can substantially assist dentists by drafting personalized patient education materials, organizing treatment explanations, and providing talking points tailored to the patient's diagnosis, allowing dentists to deliver counseling faster and more consistently while retaining clinical control.
Augmentation potential	claude-sonnet-5	4/5	AI can generate patient handouts, multilingual explainers, and follow-up reminders that let dentists spend consultation time more efficiently while still personally delivering key advice.
Task automatability	claude-haiku-4-5-20251001	2/5	While AI can generate patient education materials and provide general information about dental care, the task requires personalized clinical judgment, understanding individual patient contexts, and adaptive communication. Current AI systems cannot reliably deliver the full counseling interaction with the nuance needed for different patient types and conditions.
Task automatability	claude-sonnet-5	2/5	AI chatbots can deliver generic oral hygiene advice, but individualized clinical instruction tied to a patient's exam findings, history, and treatment plan requires the dentist's judgment and direct patient rapport.dent
Adoption barriers	claude-haiku-4-5-20251001	4/5	Dentists bear legal and professional responsibility for patient advice; liability concerns around incorrect or contextually inappropriate guidance, plus state-regulated scope-of-practice rules, create significant barriers to full automation of clinical counseling without licensed professional sign-off.
Adoption barriers	claude-sonnet-5	4/5	Dental advice tied to diagnosis and treatment is part of licensed clinical practice; liability and scope-of-practice rules require a licensed professional to give personalized guidance.
Cost vs. human wage	claude-haiku-4-5-20251001	3/5	AI-generated educational content and chatbot support is relatively inexpensive to deploy, but the overhead of clinical validation, liability insurance, and dentist oversight makes the all-in cost comparable to straightforward patient education by dental hygienists or dentists.
Cost vs. human wage	claude-sonnet-5	2/5	While generating generic educational content is cheap, integrating case-specific advice into clinical workflow still requires dentist time for accuracy and liability reasons, limiting cost savings.
Technical feasibility today	claude-haiku-4-5-20251001	2/5	Chatbots and educational content generators exist, but they lack the clinical integration, liability tolerance, and real-time responsiveness required for reliable deployment as patient advisors in dental practice. Existing systems perform narrowly on scripted information delivery rather than adaptive patient counseling.
Technical feasibility today	claude-sonnet-5	2/5	Patient education chatbots and printed AI-generated materials exist in some practices, but no deployed product reliably substitutes for a dentist's personalized counseling during an appointment.

Design, make, or fit prosthodontic appliances, such as space maintainers, bridges, or dentures, or write fabrication instructions or prescriptions for denturists or dental technicians.

CI 20–30 · exposure 30 · augmentation 63 · importance 4.5/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	2/5	Dental practices are relatively conservative adopters of automation; while some large groups and labs use CAD/CAM, wide-scale adoption of AI-driven design and prescription remains limited. Adoption is concentrated in high-volume labs rather than general dental offices.
Sector adoption velocity	claude-sonnet-5	2/5	Dental practices, especially solo/small general practices, are slow to adopt advanced digital workflows compared to information-sector industries, though CAD/CAM adoption is growing steadily.
Augmentation potential	claude-haiku-4-5-20251001	3/5	AI can assist dentists by generating initial design options, automating prescription formatting, and flagging potential fit issues, modestly raising productivity in the design and documentation phases. However, augmentation is limited to planning stages; clinical fitting and adjustment remain manual.
Augmentation potential	claude-sonnet-5	4/5	Digital scanning, CAD design software, and AI-assisted image analysis significantly speed up appliance design and prescription writing, meaningfully boosting dentist productivity while they remain in control.
Task automatability	claude-haiku-4-5-20251001	2/5	While AI can assist with initial design concepts and write some fabrication instructions, the task requires significant hands-on fitting, adjustments to individual patient anatomy, and final quality verification that demands physical presence and clinical judgment. Current AI cannot perform the full end-to-end clinical and manufacturing workflow with 50% time savings.
Task automatability	claude-sonnet-5	2/5	Physical fabrication and intraoral fitting require hands-on manipulation and clinical judgment that current AI cannot perform; only the design/prescription-writing sub-component is partially automatable via CAD/CAM software.
Adoption barriers	claude-haiku-4-5-20251001	4/5	Dentists must be licensed professionals who legally design and certify prosthodontic work; liability for appliance failure rests with the dentist. Regulatory frameworks require professional oversight of prescription and fitting, and patient contact/clinical assessment cannot be fully delegated to AI.
Adoption barriers	claude-sonnet-5	5/5	Dental licensure laws require a licensed dentist or authorized professional to design and prescribe prosthodontic appliances and perform fittings, creating hard legal barriers to full automation.
Cost vs. human wage	claude-haiku-4-5-20251001	2/5	AI-assisted CAD/CAM design tools can reduce some design labor, but the total cost of AI infrastructure, training, integration with clinical workflows, and required human supervision remains comparable to or exceeds the direct cost of a dental technician's labor for most practitioners.
Cost vs. human wage	claude-sonnet-5	2/5	Digital design software reduces some lab costs but still requires dentist time, imaging equipment, and technician fabrication, so overall cost savings versus traditional workflow are moderate, not order-of-magnitude.
Technical feasibility today	claude-haiku-4-5-20251001	2/5	Some CAD/CAM systems exist for denture design, and AI can draft prescriptions, but no deployed system reliably handles the complete prosthodontic workflow from patient assessment through final fitting without substantial human oversight and correction. Clinical validation and fit assessment remain difficult for autonomous systems.
Technical feasibility today	claude-sonnet-5	3/5	CAD/CAM systems and digital scanners are deployed in many practices for crown/denture design, but final fitting, adjustment, and prescription judgment still require the dentist; no product fully replaces the task.

Examine teeth, gums, and related tissues, using dental instruments, x-rays, or other diagnostic equipment, to evaluate dental health, diagnose diseases or abnormalities, and plan appropriate treatments.

CI 20–25 · exposure 30 · augmentation 75 · importance 4.8/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	2/5	Dental practices are predominantly small, independent, or regional; digitization is slower than in other professional services, and adoption of AI agents remains mostly in pilots (CAD analysis tools) rather than production displacement of diagnostic work. Regulatory and liability concerns slow adoption velocity.
Sector adoption velocity	claude-sonnet-5	2/5	Healthcare/dental sectors are historically slow adopters of AI for diagnosis due to regulatory, liability, and workflow integration challenges, with pilots more common than widespread production use.
Augmentation potential	claude-haiku-4-5-20251001	4/5	AI systems (particularly image analysis and decision-support tools) substantially assist dentists by highlighting abnormalities in x-rays, flagging potential diagnoses, and speeding pattern recognition, meaningfully raising productivity in the diagnostic phase while the dentist remains in the loop for final judgment and patient interaction.
Augmentation potential	claude-sonnet-5	4/5	AI-powered radiograph and imaging analysis tools meaningfully assist dentists in detecting caries, bone loss, and abnormalities, improving diagnostic accuracy and speed while the dentist remains the decision-maker.
Task automatability	claude-haiku-4-5-20251001	2/5	While AI can assist with image analysis of x-rays and detect some abnormalities, the full task requires hands-on examination with dental instruments, tactile feedback, real-time clinical judgment, and complex treatment planning that current AI cannot perform end-to-end. Significant human expertise remains irreplaceable for the diagnostic and planning components.
Task automatability	claude-sonnet-5	2/5	Physical examination and instrument-based probing of teeth/gums cannot be performed by current AI; AI can assist with image analysis but the hands-on diagnostic exam requires a human clinician physically present.
Adoption barriers	claude-haiku-4-5-20251001	5/5	Dentistry is heavily regulated; only a licensed dentist can legally diagnose dental disease, plan treatment, and sign off on clinical findings. Liability and malpractice risk are high, and patient contact and trust in a human clinician are strong legal and cultural requirements.
Adoption barriers	claude-sonnet-5	5/5	Dental diagnosis and treatment planning legally require a licensed dentist; this is a heavily regulated, licensed clinical act with direct patient contact and liability.
Cost vs. human wage	claude-haiku-4-5-20251001	2/5	AI-assisted imaging analysis has moderate cost, but the full diagnostic and planning workflow still requires a licensed dentist's time and expertise; integration overhead and oversight for clinical accuracy mean AI cost per completed diagnostic episode remains substantial relative to what a dentist charges per patient visit.
Cost vs. human wage	claude-sonnet-5	2/5	AI imaging tools add cost as a supplement rather than a replacement for the dentist's exam, so total cost per patient visit is not meaningfully reduced by AI alone.
Technical feasibility today	claude-haiku-4-5-20251001	3/5	Deployed AI systems can reliably analyze dental x-rays and assist with detection of certain conditions (caries, bone loss), but no product independently performs the complete examination, diagnosis, and treatment planning with clinical reliability across the full scope of pathology. Products exist in narrow scope (image analysis only) rather than the full task.
Technical feasibility today	claude-sonnet-5	2/5	AI-assisted radiograph analysis products (e.g., caries detection software) are deployed in some practices, but full diagnostic examination integrating tactile, visual, and radiographic data is not performed autonomously by any product today.

Formulate plan of treatment for patient's teeth and mouth tissue.

CI 20–20 · exposure 25 · augmentation 63 · importance 4.6/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	2/5	Dental practices show slow adoption of clinical AI tools; most remain in pilot or limited integration phases. Dentistry is a traditionally conservative, small-practice-dominated sector with fragmented technology adoption and high reliance on individual provider judgment.
Sector adoption velocity	claude-sonnet-5	2/5	Dental practice is a physically-oriented, licensure-heavy sector with historically slow AI adoption compared to information/finance sectors, though imaging AI adoption is growing.
Augmentation potential	claude-haiku-4-5-20251001	3/5	AI can assist by highlighting diagnostic findings, suggesting evidence-based options, and flagging contraindications or treatment patterns, thereby streamlining the dentist's deliberation. However, augmentation is limited to narrower clinical subtasks (imaging review, option generation) rather than transforming the full planning process.
Augmentation potential	claude-sonnet-5	4/5	AI diagnostic and imaging-analysis tools meaningfully assist dentists by flagging pathology, suggesting treatment options, and organizing data, improving speed and consistency of plan formulation while the dentist remains the decision-maker.
Task automatability	claude-haiku-4-5-20251001	2/5	While AI can assist with diagnostic imaging analysis and suggest treatment options based on clinical data, formulating a comprehensive treatment plan requires integrating patient history, clinical judgment, risk assessment, and informed consent—tasks that demand human expertise and accountability. Current AI cannot reliably replace this end-to-end without substantial human oversight.
Task automatability	claude-sonnet-5	2/5	Treatment planning requires physical exam findings, imaging interpretation, patient risk factors, and clinical judgment integrated in real time; AI can assist but cannot yet independently produce a reliable, liability-bearing plan end-to-end.
Adoption barriers	claude-haiku-4-5-20251001	5/5	Dentists are licensed professionals whose treatment planning carries legal and ethical responsibility; malpractice liability, regulatory requirements for professional judgment, and state dental practice acts legally require a licensed dentist to formulate and authorize the treatment plan. This is a hard barrier to full automation.
Adoption barriers	claude-sonnet-5	5/5	Treatment planning is a licensed clinical act; dentists must legally formulate and sign off on treatment plans, creating a hard regulatory and liability barrier to full automation.
Cost vs. human wage	claude-haiku-4-5-20251001	2/5	AI diagnostic and planning tools require licensing, integration into practice workflows, and dentist oversight to validate recommendations; the all-in cost remains comparable to or exceeds the value of partial automation, especially given liability and quality assurance demands.
Cost vs. human wage	claude-sonnet-5	2/5	Software licensing and integration costs are non-trivial relative to the marginal time a dentist spends planning, and human oversight/liability review is still required, keeping cost savings modest.
Technical feasibility today	claude-haiku-4-5-20251001	2/5	AI products exist for diagnostic support (caries/pathology detection in radiographs) and can flag treatment considerations, but no deployed system independently formulates complete, patient-specific treatment plans that meet clinical and legal standards. Existing tools function as assistants, not autonomous planners.
Technical feasibility today	claude-sonnet-5	2/5	AI-assisted diagnostic imaging tools (e.g., caries detection software) exist and are deployed, but full treatment-plan generation products are not in widespread production use as autonomous decision-makers.

Write prescriptions for antibiotics or other medications.

CI 5–20 · exposure 17 · augmentation 63 · importance 4.5/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	1/5	Dentists operate in regulated, human-contact-intensive healthcare sectors with strong legal and professional barriers to automation. Adoption of prescription AI is not occurring in production because the legal requirement for clinician signature makes displacement impossible.
Sector adoption velocity	claude-sonnet-5	2/5	Healthcare, especially dental practice, is a slower-adopting sector for clinical decision-making tasks due to regulation and liability, though EHR-integrated decision support is spreading gradually.
Augmentation potential	claude-haiku-4-5-20251001	3/5	AI could assist by flagging drug interactions, suggesting appropriate antibiotics based on diagnosis, or automating documentation—raising the dentist's efficiency in the review-and-sign workflow. However, the core clinical judgment and legal responsibility remain with the human.
Augmentation potential	claude-sonnet-5	4/5	AI can meaningfully assist by flagging drug interactions, suggesting dosages, and auto-populating prescription templates, improving speed and safety while the dentist remains the decision-maker.
Task automatability	claude-haiku-4-5-20251001	1/5	Prescription writing requires clinical judgment about patient-specific factors (allergies, contraindications, drug interactions, dosing) and legal authority that AI cannot exercise. While AI could draft template prescriptions, the dentist must make all clinical decisions and legally sign the prescription, so no meaningful autonomous automation is feasible.
Task automatability	claude-sonnet-5	2/5	Drafting the prescription text can be AI-assisted, but the clinical decision of what to prescribe requires diagnosis, patient history review, and legal accountability that AI cannot yet independently perform end-to-end.
Adoption barriers	claude-haiku-4-5-20251001	5/5	Prescribing is legally restricted to licensed healthcare providers and must be signed by a dentist; state and federal regulations prohibit delegation of this task to unlicensed or automated systems. Liability, malpractice exposure, and controlled-substance oversight create hard legal barriers.
Adoption barriers	claude-sonnet-5	5/5	Prescribing medication is a legally restricted act requiring a licensed prescriber's authorization; regulatory and liability barriers are very strong.
Cost vs. human wage	claude-haiku-4-5-20251001	1/5	The actual prescribing cost (clinician time, review, signing) remains necessary and unchanged; AI assistance does not reduce the human workload below what the licensed dentist must perform, making the combined cost likely equal to or higher than the human cost alone.
Cost vs. human wage	claude-sonnet-5	2/5	AI decision-support tools are cheap to run, but since a licensed professional must still review and legally authorize every prescription, the overall cost savings are limited.
Technical feasibility today	claude-haiku-4-5-20251001	2/5	No deployed AI system independently writes prescriptions in clinical practice; such systems exist only as decision-support tools requiring full clinician oversight. Regulatory and liability frameworks require a licensed provider to author and sign all prescriptions, preventing full automation even with high-accuracy AI assistance.
Technical feasibility today	claude-sonnet-5	2/5	EHR systems offer decision support and drug interaction checks, but no deployed product independently writes and authorizes prescriptions without a licensed dentist's decision and signature.

Diagnose and treat diseases, injuries, or malformations of teeth, gums, or related oral structures and provide preventive or corrective services.

CI 3–20 · exposure 13 · augmentation 50 · importance 4.6/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	2/5	Dental practices are fragmented (many small, independent practices), conservative in technology adoption, and heavily dependent on hands-on clinical work. While some larger practices and DSOs pilot imaging AI and practice management tools, meaningful automation of diagnosis and treatment remains rare in production, with adoption slower than information-intensive sectors.
Sector adoption velocity	claude-sonnet-5	2/5	Healthcare/dental practice is a moderately digitized but physically-bound sector where AI adoption for core clinical tasks remains in early pilot stages (e.g., X-ray analysis tools), far from production-scale autonomous diagnosis or treatment.
Augmentation potential	claude-haiku-4-5-20251001	3/5	AI-assisted radiograph interpretation, caries detection software, and treatment planning tools can meaningfully reduce dentist review time and improve diagnostic consistency on imaging tasks. However, augmentation is limited to specific sub-tasks (imaging analysis) rather than transforming the full clinical workflow, since manual treatment and patient interaction remain dentist-dependent.
Augmentation potential	claude-sonnet-5	3/5	AI-assisted radiograph analysis and diagnostic decision-support tools are increasingly used to help dentists detect caries or anomalies, improving accuracy and speed while the dentist retains full clinical control.
Task automatability	claude-haiku-4-5-20251001	2/5	Diagnosis of dental conditions requires clinical examination, palpation, imaging interpretation, and patient history integration—tasks where AI shows promise in image analysis but cannot perform physical examination, tactile feedback, or full clinical judgment end-to-end. Treatment (drilling, filling, extraction) requires manual dexterity and real-time adaptation that dental robots cannot do reliably without significant human oversight, falling well short of 50% time savings at equal quality.
Task automatability	claude-sonnet-5	1/5	Diagnosis and hands-on treatment require physical examination, imaging interpretation combined with tactile assessment, and manual dexterity for procedures (fillings, extractions, etc.) that no current AI system can perform end-to-end.
Adoption barriers	claude-haiku-4-5-20251001	5/5	Dentistry is strictly regulated: only licensed dentists can legally diagnose and treat dental disease in most jurisdictions. Malpractice liability, patient contact requirements, and state/federal scope-of-practice laws create hard legal and regulatory barriers that prevent autonomous AI substitution regardless of technical capability.
Adoption barriers	claude-sonnet-5	5/5	Dental diagnosis and treatment are tightly regulated, requiring licensed practitioners, direct patient contact, and legal liability for care, making autonomous AI substitution essentially prohibited.
Cost vs. human wage	claude-haiku-4-5-20251001	2/5	Current AI diagnostic tools and supportive software cost thousands to tens of thousands annually plus integration overhead, while a general dentist's loaded cost (salary ~$160k+ with overhead) is distributed across many procedures. For diagnosis and treatment combined, AI tools remain supplementary rather than cost-competitive replacements for the full task.
Cost vs. human wage	claude-sonnet-5	1/5	There is no AI substitute capable of delivering the physical treatment, so cost comparison favors the human dentist entirely; any AI use is supplementary, not a replacement of labor cost.
Technical feasibility today	claude-haiku-4-5-20251001	2/5	AI systems can assist with radiograph interpretation and caries detection at research-grade accuracy, and some dental software supports charting, but no deployed product reliably diagnoses complex cases or performs treatment autonomously. Products exist in narrow scopes (image analysis) but with notable error rates and require human dentist validation; end-to-end task execution remains infeasible.
Technical feasibility today	claude-sonnet-5	1/5	No deployed product performs full diagnosis-to-treatment cycles for dental disease; AI imaging aids exist but are narrow adjuncts, not autonomous diagnosticians or treatment providers.

Administer anesthetics to limit the amount of pain experienced by patients during procedures.

CI 0–5 · exposure 5 · augmentation 25 · importance 4.7/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	1/5	No measured adoption of autonomous AI systems for anesthetic administration exists in dental practice; the field remains heavily regulated and relies on manual clinical protocols with licensed professionals.
Sector adoption velocity	claude-sonnet-5	1/5	Dentistry is a physical, hands-on healthcare field with minimal AI adoption for direct clinical procedures like anesthesia administration.
Augmentation potential	claude-haiku-4-5-20251001	2/5	AI could offer limited assistance through decision-support tools for anesthetic selection or drug interaction checking, but the core manual and clinical assessment tasks remain squarely in the dentist's hands with minimal augmentation potential.
Augmentation potential	claude-sonnet-5	2/5	AI may assist with dosage calculation guidance or monitoring data analysis, but offers little direct augmentation to the physical act of administering anesthesia.
Task automatability	claude-haiku-4-5-20251001	1/5	Administering anesthetics requires complex clinical judgment about patient history, dosage calculation, delivery technique, and real-time physiological monitoring. Current AI systems cannot physically administer injections or intravenous anesthetics, nor reliably assess individual patient risk factors and contraindications to enable autonomous administration.
Task automatability	claude-sonnet-5	1/5	Administering anesthetics requires physical manipulation, injection, and real-time patient monitoring that current AI systems cannot perform end-to-end.ance.
Adoption barriers	claude-haiku-4-5-20251001	5/5	Dental anesthesia administration is legally restricted to licensed dentists or supervised auxiliaries in virtually all jurisdictions, and patients expect a licensed professional to assess risk and deliver anesthetics. Liability asymmetry and regulatory mandates create hard barriers to automation.
Adoption barriers	claude-sonnet-5	5/5	Administering anesthetics is a licensed medical act with strict legal, safety, and liability requirements mandating a qualified professional to perform and be accountable.
Cost vs. human wage	claude-haiku-4-5-20251001	1/5	AI has minimal role in anesthetic administration itself; the loaded cost of a dentist administering anesthesia remains far lower than any hypothetical AI system when accounting for liability, regulatory compliance, and the need for human oversight and physical capability.
Cost vs. human wage	claude-sonnet-5	1/5	There is no viable AI substitute performing this physical task, so cost comparison favors the human by default since AI cannot deliver the output at all.
Technical feasibility today	claude-haiku-4-5-20251001	2/5	While AI can assist with anesthetic selection recommendations via clinical decision support, no deployed system autonomously administers anesthetics or monitors patient response during administration. The task requires licensed human judgment and physical intervention that remains the standard of care in dental practice.
Technical feasibility today	claude-sonnet-5	1/5	No deployed product administers dental anesthesia autonomously; this remains firmly in the physical, hands-on domain of licensed clinicians.

Use masks, gloves, and safety glasses to protect patients and self from infectious diseases.

CI 0–0 · exposure 0 · augmentation 0 · importance 4.9/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	1/5	This is a mandatory manual safety practice in healthcare with no meaningful opportunity for AI adoption. Adoption velocity is not applicable as the task must be performed by humans directly.
Sector adoption velocity	claude-sonnet-5	1/5	Dental clinical care is a hands-on, in-person physical task with essentially no AI adoption for this specific safety behavior.
Augmentation potential	claude-haiku-4-5-20251001	1/5	AI cannot meaningfully assist in the physical act of donning or managing PPE. The task is straightforward, routine, and requires no cognitive support that AI could provide.
Augmentation potential	claude-sonnet-5	1/5	AI provides no meaningful assistance to the physical act of donning protective equipment during patient care.
Task automatability	claude-haiku-4-5-20251001	1/5	Donning protective equipment is a physical task requiring dexterity and situational awareness in a clinical environment. Current AI systems have no capability to physically manipulate masks, gloves, and safety glasses or to perform these protective actions for humans.
Task automatability	claude-sonnet-5	1/5	This is a physical infection-control action requiring a human body to don PPE while treating a patient; no AI system performs this.
Adoption barriers	claude-haiku-4-5-20251001	5/5	Occupational safety regulations and standards of care legally require the dentist or clinical staff themselves to manage PPE; no delegation or substitution to automated systems is feasible or permitted under health and safety law.
Adoption barriers	claude-sonnet-5	5/5	Infection control is legally mandated (OSHA/health regulations) and requires a licensed clinician to physically perform patient care with PPE; this cannot be delegated to software.
Cost vs. human wage	claude-haiku-4-5-20251001	1/5	AI has no practical role in this task, making cost comparison meaningless. A human performing this task incurs minimal direct cost (equipment is inexpensive and time is brief).
Cost vs. human wage	claude-sonnet-5	1/5	There is no AI substitute performing this physical action, so cost comparison favors the human by default since AI cannot deliver the output at all.
Technical feasibility today	claude-haiku-4-5-20251001	1/5	No deployed AI product can physically apply or manage personal protective equipment. This is fundamentally a manual labor task outside the scope of current AI capabilities.
Technical feasibility today	claude-sonnet-5	1/5	No deployed product exists that physically wears protective equipment or performs this safety task on behalf of a dentist.

Use dental air turbines, hand instruments, dental appliances, or surgical implements.

CI 0–0 · exposure 0 · augmentation 25 · importance 4.7/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	1/5	Dental practice remains highly manual, and even early-stage robotic-assist tools have minimal adoption; the sector is not adopting autonomous AI agents for direct patient instrumentation.
Sector adoption velocity	claude-sonnet-5	1/5	Healthcare/dentistry is a slow-adopting, highly regulated, physical-contact sector with minimal automation of hands-on procedures; adoption of AI here is limited to diagnostics and imaging, not instrument use.
Augmentation potential	claude-haiku-4-5-20251001	2/5	AI currently assists dentistry mainly through diagnostic imaging analysis and treatment planning, not through real-time augmentation of hand-instrument use; modest productivity support exists but does not fundamentally transform the procedural execution itself.
Augmentation potential	claude-sonnet-5	2/5	Some computer-guided systems (e.g., static/dynamic navigation for implants) assist precision, but broad instrument use across general dentistry sees little AI augmentation currently.
Task automatability	claude-haiku-4-5-20251001	1/5	Dental procedures requiring hand instruments, air turbines, and surgical implements demand real-time sensorimotor precision, haptic feedback, and adaptive response to patient anatomy and pain responses that current AI systems cannot perform end-to-end. No deployed AI can reliably operate these instruments inside a patient's mouth with the dexterity, safety, and judgment required.
Task automatability	claude-sonnet-5	1/5	This is a physical, hands-on clinical task requiring fine motor control inside a patient's mouth; no current AI system or robot performs general dental drilling, extraction, or restorative work autonomously.
Adoption barriers	claude-haiku-4-5-20251001	5/5	Dental practice is heavily regulated; only licensed dentists can legally perform operative dental procedures. Patient contact, liability for surgical error, and licensing requirements create hard legal and professional barriers to automation.
Adoption barriers	claude-sonnet-5	5/5	Dental procedures require a licensed dentist by law, involve direct patient contact, and carry high liability for error, making this one of the most protected physical-professional tasks.
Cost vs. human wage	claude-haiku-4-5-20251001	1/5	The capital cost of robotic dental systems, maintenance, integration, and required human oversight would far exceed the loaded wage of a general dentist, and no such systems are in cost-competitive deployment.
Cost vs. human wage	claude-sonnet-5	1/5	There is no viable AI substitute performing this physical task, so cost comparison favors the human dentist entirely; any robotic assistance requires expensive equipment plus the dentist's continued presence.
Technical feasibility today	claude-haiku-4-5-20251001	1/5	No production AI system performs dental instrumentation autonomously today; research prototypes exist but are far from clinical deployment and lack the reliability, safety certification, and regulatory approval required for patient care.
Technical feasibility today	claude-sonnet-5	1/5	No deployed products autonomously operate dental air turbines or surgical implements on patients; robotic dental systems remain research-stage or narrowly assistive (e.g., guided implant placement) with a dentist fully in control.

Fill pulp chamber and canal with endodontic materials.

CI 0–0 · exposure 0 · augmentation 25 · importance 4.5/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	1/5	Dentistry remains a low-digitization, human-contact-intensive sector with minimal AI automation in clinical procedures. Endodontic filling is a hands-on, anatomically variable task performed in small practices and specialist offices, not in high-volume, standardized industrial settings conducive to rapid AI adoption.
Sector adoption velocity	claude-sonnet-5	1/5	Clinical dentistry is a physical, hands-on field with minimal AI displacement of procedural tasks; adoption is limited to diagnostic imaging and administrative support, not hands-on procedures.
Augmentation potential	claude-haiku-4-5-20251001	2/5	AI can assist with pre-operative imaging analysis and treatment planning, but once the clinician begins the procedure, current AI offers limited real-time assistance. The task itself is tactile and requires continuous human judgment, leaving little room for meaningful in-procedure augmentation.
Augmentation potential	claude-sonnet-5	2/5	AI can assist with pre-procedure planning (e.g., imaging analysis of canal anatomy) but offers little real-time assistance during the actual filling procedure itself.
Task automatability	claude-haiku-4-5-20251001	1/5	Filling a pulp chamber and canal with endodontic materials requires real-time 3D spatial reasoning, haptic feedback, sub-millimeter precision, and adaptive decision-making based on internal tooth anatomy that varies per patient. Current AI systems cannot perform this delicate in-vivo manual procedure end-to-end.
Task automatability	claude-sonnet-5	1/5	This is a precise physical procedure (obturating a cleaned root canal with gutta-percha or similar materials) requiring fine motor manipulation inside a patient's mouth; no current AI or robotic system can perform this end-to-end.
Adoption barriers	claude-haiku-4-5-20251001	5/5	Dental licensing laws and clinical practice regulations explicitly require a licensed dentist to perform or directly supervise endodontic treatment. The procedure carries significant liability for failure (periapical pathology, patient harm), creating legal and regulatory barriers to any form of autonomous substitution.
Adoption barriers	claude-sonnet-5	5/5	Dental procedures require a licensed dentist, direct physical contact, sterile technique, and legal liability for clinical outcomes, creating hard regulatory and licensing barriers.
Cost vs. human wage	claude-haiku-4-5-20251001	1/5	The capital cost of any robotic dental system capable of this task, plus integration, training, and oversight, far exceeds the loaded cost of a dentist performing the procedure directly. Endodontics is already a high-margin, specialist-level service.
Cost vs. human wage	claude-sonnet-5	1/5	There is no AI-driven alternative to compare cost against; the task is entirely human-performed, making AI substitution costs effectively infinite/inapplicable.
Technical feasibility today	claude-haiku-4-5-20251001	1/5	No deployed product performs autonomous endodontic filling in clinical practice. While imaging analysis and treatment planning have AI support, the actual physical task of instrumentation and material placement requires a licensed dentist and remains manual; no robotic or AI system is in reliable clinical production for this subtask.
Technical feasibility today	claude-sonnet-5	1/5	No deployed dental product performs canal obturation autonomously; robotic dental assistance remains research-stage and not in clinical production.

Treat exposure of pulp by pulp capping, removal of pulp from pulp chamber, or root canal, using dental instruments.

CI 0–0 · exposure 0 · augmentation 25 · importance 4.5/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	1/5	Dentistry remains a low-automation sector with strong reliance on human clinical judgment and manual skill. Adoption of AI or robotics for invasive procedures like root canals is negligible in current practice.
Sector adoption velocity	claude-sonnet-5	1/5	Dentistry is a hands-on, in-person healthcare field with minimal automation of clinical procedures; adoption of AI is largely confined to diagnostics and imaging, not treatment execution.
Augmentation potential	claude-haiku-4-5-20251001	2/5	While AI-assisted imaging analysis (e.g., detecting pulp exposure or planning root canal anatomy) could provide some assistance, current systems offer limited support for the core manual and decision-making components of performing the procedure itself.
Augmentation potential	claude-sonnet-5	2/5	AI can assist with diagnostic imaging (e.g., detecting pulp exposure or canal anatomy via radiograph analysis) but offers little direct augmentation during the actual instrument-based treatment.
Task automatability	claude-haiku-4-5-20251001	1/5	This task requires precise manual manipulation of dental instruments inside the oral cavity, real-time decision-making based on visual/tactile feedback, and the ability to respond to anatomical variations and complications. Current AI systems lack the dexterity, sensory integration, and adaptive control needed to perform endodontic procedures end-to-end.
Task automatability	claude-sonnet-5	1/5	This is a hands-on invasive clinical procedure requiring fine motor control, tactile feedback, and real-time adaptation inside a patient's mouth—far beyond current AI or robotic capability to perform end-to-end.
Adoption barriers	claude-haiku-4-5-20251001	5/5	Dental treatment, including endodontics, is heavily regulated and requires a licensed dentist to perform or directly supervise the work. Legal and regulatory frameworks explicitly restrict these procedures to licensed professionals, creating a hard barrier to full automation.
Adoption barriers	claude-sonnet-5	5/5	Only licensed dentists (or supervised specialists) may legally perform pulp capping and root canal treatment, and physical invasive care carries high liability and requires direct human contact.
Cost vs. human wage	claude-haiku-4-5-20251001	1/5	The cost of developing, validating, maintaining, and insuring a robotic system capable of endodontic procedures would far exceed the cost of a trained dentist performing the work, especially when accounting for liability and malpractice risk.
Cost vs. human wage	claude-sonnet-5	1/5	There is no viable AI substitute performing this procedure, so cost comparison favors the human dentist entirely; any assistive tech adds cost rather than replacing labor.
Technical feasibility today	claude-haiku-4-5-20251001	1/5	No deployed AI or robotic system performs pulp capping, pulp removal, or root canal treatment independently in clinical practice today. While some research exists on dental robotics, no production systems reliably execute this complex surgical task at scale in real dental offices.
Technical feasibility today	claude-sonnet-5	1/5	No deployed product performs pulp capping or root canal therapy autonomously; robotic dental systems are experimental at best and not used for this task in production.

Remove diseased tissue, using surgical instruments.

CI 0–0 · exposure 0 · augmentation 25 · importance 4.3/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	1/5	Surgical automation in dentistry remains experimental; the overwhelming majority of tissue removal is performed by human dentists using traditional hand instruments, with minimal production deployment of autonomous or agent-based systems.
Sector adoption velocity	claude-sonnet-5	1/5	Clinical dental surgery is a highly manual, in-person healthcare task with minimal AI adoption for the physical procedure itself.
Augmentation potential	claude-haiku-4-5-20251001	2/5	Robotic assistance (like guided systems or image-based navigation) can provide some support to the dentist's technique, but current tools do not materially transform productivity or reduce the dentist's active surgical role.
Augmentation potential	claude-sonnet-5	2/5	AI can assist with diagnostics, imaging analysis, or treatment planning beforehand, but offers little direct assistance during the physical act of tissue removal.
Task automatability	claude-haiku-4-5-20251001	1/5	Removing diseased tissue requires fine motor manipulation in a complex, patient-specific oral cavity with real-time visual feedback and tactile judgment. Current AI systems have no deployed capability to perform surgical procedures autonomously.
Task automatability	claude-sonnet-5	1/5	This is a physical surgical procedure requiring fine motor control, tactile feedback, and real-time judgment inside a patient's mouth; no current AI system can perform this manipulation.
Adoption barriers	claude-haiku-4-5-20251001	5/5	Dental surgery is legally restricted to licensed dentists in all jurisdictions; liability for patient harm is substantial, and autonomous or semi-autonomous surgical systems face severe regulatory barriers and malpractice risk.
Adoption barriers	claude-sonnet-5	5/5	Only a licensed dentist may legally perform invasive surgical procedures on patients, and liability/regulatory requirements make substitution essentially impossible.
Cost vs. human wage	claude-haiku-4-5-20251001	1/5	Surgical robotic systems are extremely expensive to acquire, maintain, and operate, and still require a licensed dentist to execute the procedure; the capital and labor costs far exceed a human dentist's direct service cost.
Cost vs. human wage	claude-sonnet-5	1/5	There is no viable AI substitute performing this physical task, so cost comparison favors the human dentist entirely.
Technical feasibility today	claude-haiku-4-5-20251001	1/5	No AI system reliably performs surgical tissue removal in production today. Robotic surgery requires human supervision at every step and cannot independently assess tissue health or make autonomous surgical decisions.
Technical feasibility today	claude-sonnet-5	1/5	No deployed product performs autonomous dental surgical tissue removal; robotic dental surgery remains research-stage at best.

Apply fluoride or sealants to teeth.

CI 0–0 · exposure 0 · augmentation 0 · importance 4.1/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	1/5	Dental practices remain largely manual and non-automated; adoption of AI or robotics for routine clinical tasks is negligible even in early-adopter practices, with no evidence of production-scale substitution.
Sector adoption velocity	claude-sonnet-5	1/5	Dental care is a low-digitization, physical-contact sector with minimal AI deployment for hands-on procedures, showing negligible automation adoption for this specific task.
Augmentation potential	claude-haiku-4-5-20251001	1/5	AI offers no meaningful assistance for the hands-on application of fluoride or sealants; the task is already straightforward and heavily dependent on direct manual skill and real-time clinical judgment.
Augmentation potential	claude-sonnet-5	1/5	AI provides essentially no assistance to the physical act of applying fluoride or sealants, though it may help elsewhere in dental practice like scheduling or diagnostics.
Task automatability	claude-haiku-4-5-20251001	1/5	Applying fluoride or sealants requires precise physical manipulation of instruments inside a patient's mouth, real-time tactile feedback, and adaptation to individual tooth anatomy. Current AI systems cannot perform physical manipulation or perform reliably in uncontrolled biological environments.
Task automatability	claude-sonnet-5	1/5	This is a hands-on physical procedure requiring fine motor manipulation inside a patient's mouth; no current AI system can perform the physical application of fluoride or sealants.
Adoption barriers	claude-haiku-4-5-20251001	5/5	Dental procedures require a licensed dentist or hygienist by law in virtually all jurisdictions, and liability for patient harm from automation remains unresolved. Patient comfort and consent add additional human-contact requirements.
Adoption barriers	claude-sonnet-5	5/5	Applying fluoride/sealants is a licensed clinical procedure typically requiring a dentist or dental hygienist, with direct patient contact and liability, making non-human substitution legally and practically barred.
Cost vs. human wage	claude-haiku-4-5-20251001	1/5	The capital cost of specialized dental robotics, integration, maintenance, and required supervision far exceeds the labor cost of a dental hygienist or dentist performing this straightforward 5–10 minute procedure.
Cost vs. human wage	claude-sonnet-5	1/5	There is no viable AI substitute performing this physical task, so any AI-based alternative would require entirely new robotic hardware costing far more than a hygienist's or dentist's time.
Technical feasibility today	claude-haiku-4-5-20251001	1/5	No deployed AI or robotic system reliably performs in-mouth fluoride or sealant application in clinical settings. While dental robots exist in research, they are not in routine clinical production and require extensive human oversight.
Technical feasibility today	claude-sonnet-5	1/5	No deployed product performs this physical clinical procedure; dental robotics for this specific task remain research-stage at best and are not in production use.

Eliminate irritating margins of fillings and correct occlusions, using dental instruments.

CI 0–0 · exposure 0 · augmentation 25 · importance 4.1/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	1/5	Dental practices remain largely traditional in automation adoption, with minimal production deployment of autonomous intraoral procedures. The sector is slower to digitize than finance or IT, with high regulatory burden and human-centered clinical workflows.
Sector adoption velocity	claude-sonnet-5	1/5	Clinical dentistry involving hands-on instrument use has essentially no AI adoption for direct task execution; the sector is slow to adopt physical automation.
Augmentation potential	claude-haiku-4-5-20251001	2/5	Current AI offers minimal augmentation for margin finishing and occlusion work; intraoral imaging and planning tools provide some assistance, but real-time guidance during instrument work is limited. The tactile and real-time judgment demands of this task restrict meaningful AI partnership today.
Augmentation potential	claude-sonnet-5	2/5	AI can assist with diagnostic imaging or occlusion analysis to inform the dentist's adjustments, but it does not meaningfully augment the actual manual correction process itself.
Task automatability	claude-haiku-4-5-20251001	1/5	This task requires precise manual dexterity, real-time visual feedback, and haptic sensitivity that current AI systems cannot perform end-to-end. Even with robotic arms, the complexity of intraoral work—navigating tight spaces, detecting micro-margins, and adjusting to individual patient anatomy—remains beyond current deployed capabilities.
Task automatability	claude-sonnet-5	1/5	This is a hands-on physical procedure requiring fine motor manipulation of dental instruments inside a patient's mouth; no current AI system can perform this physical task.
Adoption barriers	claude-haiku-4-5-20251001	5/5	This task is legally and clinically regulated as the practice of dentistry, requiring a licensed dentist to perform or directly oversee the work. Liability, patient safety standards, and licensing laws create hard barriers to full automation without human professional sign-off.
Adoption barriers	claude-sonnet-5	5/5	Dental procedures require a licensed dentist to legally perform intraoral clinical work, with direct liability and physical risk to patients preventing any automation.
Cost vs. human wage	claude-haiku-4-5-20251001	1/5	The capital cost, maintenance, and required oversight of any robotic dental system substantially exceeds the loaded hourly cost of a general dentist performing this task, making automation economically unfavorable at current technology maturity.
Cost vs. human wage	claude-sonnet-5	1/5	There is no AI substitute performing this physical intervention, so cost comparison favors the human dentist entirely since AI cannot deliver the output at all.
Technical feasibility today	claude-haiku-4-5-20251001	1/5	No production dental robot system reliably performs autonomous margin elimination and occlusion correction as a standalone task today. Research prototypes exist, but clinical deployment remains experimental and requires human operator control; no mature product performs this independently at scale.
Technical feasibility today	claude-sonnet-5	1/5	No deployed product performs physical dental adjustment procedures; this remains purely a manual clinical task performed by dentists.

Perform oral or periodontal surgery on the jaw or mouth.

CI 0–0 · exposure 0 · augmentation 38 · importance 4.0/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	1/5	Despite interest in surgical robotics, actual adoption of autonomous or semi-autonomous systems for oral surgery in dental practices remains minimal. Barriers are regulatory, financial, and cultural; most dental practices continue traditional surgical techniques without AI augmentation in production.
Sector adoption velocity	claude-sonnet-5	1/5	Dental surgery is a highly physical, hands-on domain with minimal AI integration into the actual surgical act; adoption is confined to imaging/diagnostic support, not the procedure itself.
Augmentation potential	claude-haiku-4-5-20251001	2/5	AI can assist with preoperative imaging analysis, surgical planning, and intraoperative navigation guidance, but these are supportive rather than transformative. The surgeon remains fully responsible for execution; augmentation is marginal compared to the surgeon's core skill and judgment.
Augmentation potential	claude-sonnet-5	3/5	AI can assist with pre-surgical planning, imaging analysis, and guided implant placement systems, improving precision, but the surgeon remains fully responsible for executing the procedure.
Task automatability	claude-haiku-4-5-20251001	1/5	Oral and periodontal surgery requires precise manipulation of delicate oral tissues, real-time adaptation to anatomical variation, and immediate response to bleeding or complications. Current AI systems cannot perform end-to-end surgical procedures autonomously, and the requirement for fine motor control and adaptive decision-making during surgery far exceeds today's capabilities.
Task automatability	claude-sonnet-5	1/5	Oral and periodontal surgery requires physical manual dexterity, tactile feedback, and real-time judgment in a living patient's mouth that no current AI system can perform end-to-end.
Adoption barriers	claude-haiku-4-5-20251001	5/5	Oral and periodontal surgery is a licensed, regulated procedure that dental boards legally require a licensed dentist to perform and sign off on. Liability, patient safety standards, malpractice exposure, and the medical necessity for human judgment create hard barriers to automation or delegation to non-licensed systems.
Adoption barriers	claude-sonnet-5	5/5	Performing surgery requires a licensed dentist or oral surgeon by law, with direct liability for patient safety, making this one of the most legally protected physical tasks.
Cost vs. human wage	claude-haiku-4-5-20251001	1/5	A dentist performing oral surgery commands significant specialist billing ($1500–$5000+ per procedure). Current surgical robots and AI systems, even if functional, would require substantial capital investment, maintenance, and surgeon oversight that collectively exceeds the cost of direct human surgical performance.
Cost vs. human wage	claude-sonnet-5	1/5	There is no viable AI-only substitute for this physical task, so any comparison favors the human dentist entirely; assistive tech adds cost rather than replacing labor.
Technical feasibility today	claude-haiku-4-5-20251001	1/5	No deployed AI system reliably performs oral or periodontal surgery independently. While AI assists with imaging and planning, surgical execution remains entirely dependent on human surgeons. Research prototypes for surgical robotics exist but do not meet production reliability standards for autonomous or semi-autonomous surgical procedures.
Technical feasibility today	claude-sonnet-5	1/5	No deployed product performs autonomous oral or periodontal surgery; surgical robotics for dentistry remain experimental and always require a licensed dentist operating or directly supervising.

Bleach, clean, or polish teeth to restore natural color.

CI 0–0 · exposure 0 · augmentation 25 · importance 3.5/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	1/5	Dental practices are traditional, rely on manual skill and patient interaction, and have not adopted autonomous robotic solutions for routine prophylaxis or cosmetic procedures at scale. Adoption remains minimal.
Sector adoption velocity	claude-sonnet-5	1/5	Dental care is a low-digitization, physical-contact sector with minimal AI adoption for hands-on procedures; robotics in dentistry remain experimental and rare.
Augmentation potential	claude-haiku-4-5-20251001	2/5	AI could assist in pre-treatment shade assessment or post-procedure documentation, but the core task of manual tooth cleaning and polishing offers limited room for AI augmentation while the human remains in control.
Augmentation potential	claude-sonnet-5	2/5	AI can assist with treatment planning, imaging analysis, or scheduling around this task, but offers negligible direct assistance during the physical bleaching/polishing procedure itself.
Task automatability	claude-haiku-4-5-20251001	1/5	Bleaching, cleaning, and polishing teeth requires precise manual dexterity, real-time adaptation to patient anatomy, and physical interaction with the oral cavity that current AI and robotic systems cannot perform end-to-end. While AI could assist in treatment planning, the hands-on execution demands human skill and cannot be automated today.
Task automatability	claude-sonnet-5	1/5	This is a hands-on physical procedure involving direct manipulation of instruments in a patient's mouth; no current AI system can perform the physical act of cleaning or polishing teeth.
Adoption barriers	claude-haiku-4-5-20251001	5/5	Dental treatment is heavily regulated; only licensed dentists and hygienists are legally authorized to perform these procedures. Patient safety, liability, and state licensure requirements create hard barriers to automation.
Adoption barriers	claude-sonnet-5	5/5	Dental procedures require licensed practitioners, direct physical contact, sterile technique, and liability oversight, making this a hard-barrier task legally reserved for licensed professionals.
Cost vs. human wage	claude-haiku-4-5-20251001	1/5	Even if automation were feasible, the capital investment in dental robotics, sterilization, and oversight infrastructure would far exceed the cost of a dental hygienist or dentist performing the task, making AI substantially more expensive.
Cost vs. human wage	claude-sonnet-5	1/5	There is no AI substitute performing this physical task, so AI cost is not comparable—the human (or robotic-assisted, non-AI) provider remains the only option.
Technical feasibility today	claude-haiku-4-5-20251001	1/5	No deployed product reliably performs in-mouth dental bleaching, cleaning, or polishing autonomously in clinical practice. Dental robotics remain experimental and lack the dexterity, safety approvals, and real-time responsiveness required for this task.
Technical feasibility today	claude-sonnet-5	1/5	No deployed AI product performs manual dental cleaning or polishing; this remains purely a manual clinical task performed by dentists or hygienists.

Related occupations — Healthcare Practitioners & Technical

How to read this

A high substitution score does not mean this job disappears — it means a large share of its current tasks face replacement pressure, so the mix of tasks is likely to change. High augmentation alongside substitution typically means the occupation reorganizes around the protected tasks. Wide confidence intervals mean the rater panel disagreed: treat those scores as open questions, not verdicts.

What would change this score

New model capabilities (automatability, feasibility), falling inference costs (cost ratio), regulation and licensing shifts (barriers), and measured sector adoption (velocity) all re-enter at every index release. Each release is recomputed, versioned and kept queryable — scores are claims with a date on them, not permanent labels.