Occupation · SOC 29-1051.00
Dispense drugs prescribed by physicians and other health practitioners and provide information to patients about medications and their use. May advise physicians and other health practitioners on the selection, dosage, interactions, and side effects of medications.
Also called: Clinical Pharmacist · Hospital Pharmacist · Pharm D (Pharmacy Doctor) · Pharmacist in Charge (PIC) · Informatics Pharmacist · Pharmacy Coordinator · Pharmacy Informaticist · Pharmacy Services Clinical Coordinator · Registered Pharmacist · Retail Pharmacist · Apothecary · District Pharmacy Supervisor
Job family: Healthcare Practitioners and Technical Occupations
A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch
/roles/role-29-1051-00/context.md directly.
A fast read on where AI already shows up in this occupation, where it stays a copilot, where humans remain in the loop, and what the labor market is doing. Built from observed Claude.ai conversations mapped to O*NET tasks and from published research — measures of usage and exposure, not advice or predictions that the job is going away.
Task areas most often handled directively in observed AI conversations — candidates to delegate with light review.
Task areas where people work with AI — iterating, learning, or checking — staying in the loop rather than handing the task off.
Task areas where a human was still judged necessary in a large share of observed conversations — not a safety ruling, an observed-need signal.
The capabilities O*NET rates most important for this occupation — the human ground the work is built on.
See all skills →Independent published positions, read together — not a forecast.
69th-percentile task overlap — yet about 14,200 openings a year (+4.6% projected, BLS), and observed AI use leans 7388% copilot, not hand-off (AEI) . What exposure means →
What today's research says about this occupation's exposure to AI, how AI is actually being used in it, and where employment is headed. These are positions within published studies — measures of exposure and usage, not predictions that this job will disappear.
Each study uses its own scale, so the raw scores are not comparable across rows — the percentile (this job's rank among all U.S. occupations with data) is the comparable figure, and sizes the bars.
| Measure | Rank vs all occupations | Percentile | Score |
|---|---|---|---|
| Overall AI exposure (Felten et al.) Moderate | 62nd | 0.6 | |
| LLM task exposure, γ (OpenAI / Eloundou) Moderate | 59th | 0.7 | |
| AI assistant applicability (Microsoft) High | 85th | 0.3 |
OpenAI's exposure study scores tasks three ways: with a language model alone (α 0.1), with simple added tooling (β 0.4), and including AI-powered software (γ 0.7). Higher means more of the job's tasks could be done at least twice as fast — not that they will be automated away.
This job mostly cannot be done remotely (Dingel–Neiman) — its hands-on tasks sit outside what software-based AI reaches.
A pre-LLM (2013) estimate of how automatable this job is by computerization and robotics. Shown for historical context only — it is not part of any current AI ranking.
Frey–Osborne probability 0.0 · 8th percentile among occupations · Low
Among measured AI assistant conversations mapped to this occupation (Anthropic Economic Index, 2026-01-15), these task types came up most. These are shares of observed AI conversations — not shares of the job, of worker time, or of what could be automated.
| Provide information and advice regarding drug interactions, side effects, dosage, and proper medication storage. | 7.6% | |
| Assess the identity, strength, or purity of medications. | 4.1% | |
| Compound and dispense medications as prescribed by doctors and dentists, by calculating, weighing, measuring, and mixing ingredients, or oversee these activities. | 1.2% | |
| Publish educational information for other pharmacists, doctors, or patients. | 0.9% | |
| Plan, implement, or maintain procedures for mixing, packaging, or labeling pharmaceuticals, according to policy and legal requirements, to ensure quality, security, and proper disposal. | 0.4% | |
| Analyze prescribing trends to monitor patient compliance and to prevent excessive usage or harmful interactions. | 0.2% |
Independent U.S. Bureau of Labor Statistics employment projection for 2024–2034 — a labor-market forecast, not an AI-impact forecast.
| Outlook | About average · +4.6% by 2034 |
| Projected annual openings | 14,200 |
| Employment 2024 → 2034 | 335,100 → 350,500 |
“Annual openings” counts new jobs plus replacements for workers who leave the occupation, so it can be large even when growth is modest.
The ILO's 2025 global study scores generative-AI exposure on the international ISCO-08 occupation system, not US SOC. Bridged through the published (and approximate, many-to-many) IBS O*NET-SOC ↔ ISCO-08 crosswalk, this US occupation corresponds to the international occupation below. Exposure here means how much of the work's tasks today's AI can attempt — task overlap, not automation, adoption, or jobs lost.
| International occupation (ISCO-08) | Task exposure (2025) | Most tasks fall in |
|---|---|---|
| Pharmacists · 2262 | 33% | Minimal |
Read the whole six-band gradient on the GenAI exposure gradient page. The crosswalk is approximate: a US occupation can map to several international ones, and the ILO scores describe the international occupation, not this exact US role.
How people actually apply AI to this occupation's tasks, from Claude.ai (Free and Pro) conversations in the Anthropic Economic Index, 2026-01-15. This is one AI assistant's consumer sample — not all AI, not the whole workforce. Autonomy and the collaboration mix are model-rated estimates; figures below the sample floor are hidden.
| Augmentation vs. automation | 73.9% working with AI · 21.1% handed to AI |
| Most common way people use AI here | Learning · you ask AI to explain or teach |
| Typical AI autonomy | 3.5 / 5 · higher = AI acts more independently |
| Used for work (vs. personal / coursework) | 8.6% |
The role's most common tasks in AI conversations, each tagged with how people work with the AI on it. “Usage” is the share of observed conversations, not of the job.
| Task | How | Usage |
|---|---|---|
| Provide information and advice regarding drug interactions, side effects, dosage, and proper medication storage. | Learning | 17.1% |
| Assess the identity, strength, or purity of medications. | Learning | 1.6% |
| Compound and dispense medications as prescribed by doctors and dentists, by calculating, weighing, measuring, and mixing ingredients, or oversee these activities. | Learning | 1.1% |
| Plan, implement, or maintain procedures for mixing, packaging, or labeling pharmaceuticals, according to policy and legal requirements, to ensure quality, security, and proper disposal. | Directive | 0.6% |
| Advise customers on the selection of medication brands, medical equipment, or healthcare supplies. | Learning | 0.5% |
| Publish educational information for other pharmacists, doctors, or patients. | Learning | 0.4% |
| Provide specialized services to help patients manage conditions such as diabetes, asthma, smoking cessation, or high blood pressure. | Learning | 0.4% |
Tasks where the model most often judged that a person remained necessary — a useful read on the current boundary, not a guarantee.
| Advise customers on the selection of medication brands, medical equipment, or healthcare supplies. | 100.0% | |
| Provide specialized services to help patients manage conditions such as diabetes, asthma, smoking cessation, or high blood pressure. | 100.0% | |
| Assess the identity, strength, or purity of medications. | 98.2% | |
| Provide information and advice regarding drug interactions, side effects, dosage, and proper medication storage. | 96.3% | |
| Publish educational information for other pharmacists, doctors, or patients. | 95.3% | |
| Compound and dispense medications as prescribed by doctors and dentists, by calculating, weighing, measuring, and mixing ingredients, or oversee these activities. | 95.3% |
Example prompts phrased from the tasks people most often delegate to AI in this occupation (Anthropic Economic Index). Each shows the underlying measured task and its share of observed AI use. They are suggested phrasings of real tasks — starting points, not endorsed instructions.
Help me provide information and advice regarding drug interactions, side effects, dosage, and proper medication storage. From: Provide information and advice regarding drug interactions, side effects, dosage, and proper medication storage. · 17.1% of measured AI use · learning
Help me assess the identity, strength, or purity of medications. From: Assess the identity, strength, or purity of medications. · 1.6% of measured AI use · learning
Help me compound and dispense medications as prescribed by doctors and dentists, by calculating, weighing, measuring, and mixing ingredients, or oversee these activities. From: Compound and dispense medications as prescribed by doctors and dentists, by calculating, weighing, measuring, and mixing ingredients, or oversee these activities. · 1.1% of measured AI use · learning
Help me plan, implement, or maintain procedures for mixing, packaging, or labeling pharmaceuticals, according to policy and legal requirements, to ensure quality, security, and proper disposal. From: Plan, implement, or maintain procedures for mixing, packaging, or labeling pharmaceuticals, according to policy and legal requirements, to ensure quality, security, and proper disposal. · 0.6% of measured AI use · directive
All 21 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.
O*NET importance rating, from 1 (not important) to 5 (extremely important).
| Medicine and Dentistry | 4.6 | |
| Mathematics | 4.5 | |
| Customer and Personal Service | 4.2 | |
| English Language | 4.2 | |
| Chemistry | 4.1 | |
| Biology | 4.0 | |
| Psychology | 3.7 | |
| Computers and Electronics | 3.4 | |
| Education and Training | 3.3 | |
| Administrative | 3.3 |
| Oral Expression | 4.3 | |
| Oral Comprehension | 4.1 | |
| Written Comprehension | 4.1 | |
| Problem Sensitivity | 4.0 | |
| Near Vision | 4.0 | |
| Written Expression | 3.9 | |
| Deductive Reasoning | 3.9 | |
| Inductive Reasoning | 3.9 | |
| Category Flexibility | 3.9 | |
| Information Ordering | 3.8 | |
| Speech Recognition | 3.8 | |
| Speech Clarity | 3.8 | |
| Mathematical Reasoning | 3.3 |
| Reading Comprehension | 4.0 | |
| Active Listening | 4.0 | |
| Speaking | 4.0 | |
| Writing | 3.9 | |
| Critical Thinking | 3.9 | |
| Monitoring | 3.9 | |
| Active Learning | 3.6 | |
| Science | 3.4 | |
| Mathematics | 3.3 |
Skills employers ask for in job postings for this occupation (Lightcast), with whether each is a common or specialized skill.
How characteristic each condition is of the job, on O*NET's 1–5 context scale (higher = more present in day-to-day work). Each condition links to how it varies across all occupations.
What to study: Dental, Medical, and Veterinary Residency Programs , Health Professions and Related Programs . Fields of study crosswalked to this occupation (NCES CIP–SOC), not a requirement.
Share of people in this occupation at each level of education.
| Doctoral Degree | 78.4% | |
| Bachelor's Degree | 11.5% | |
| Post-Doctoral Training | 5.1% | |
| First Professional Degree | 3.4% | |
| High School Diploma | 1.8% |
The interests and personal qualities O*NET associates with people who do this work.
| Dependability | 10.0 | |
| Attention to Detail | 9.0 | |
| Integrity | 8.0 | |
| Cautiousness | 7.0 | |
| Intellectual Curiosity | 6.0 | |
| Cooperation | 5.0 | |
| Achievement Orientation | 4.0 |
| Health Care Service | 6.3 | |
| Life Science | 4.9 | |
| Medical Science | 4.8 | |
| Mathematics/Statistics | 3.6 | |
| Teaching/Education | 3.6 | |
| Social Service | 3.6 |
| Investigative | 5.7 | |
| Social | 4.9 | |
| Conventional | 4.6 |
U.S. · annual wages (BLS OEWS)
| 10th percentile | $86,930 |
| 25th percentile | $127,250 |
| Median (50th) | $137,480 |
| 75th percentile | $158,620 |
| 90th percentile | $172,040 |
| People employed | 328,870 |
Where these workers are employed, by number of jobs (national, BLS OEWS). Pay shown is the occupation's national median, not industry-specific.
| Industry | Workers | National median pay |
|---|---|---|
| Retail Trade · Sector | 171,400 | $133,250 |
| Pharmacies and Drug Retailers · National industry | 125,310 | $131,640 |
| Health Care and Social Assistance · Sector | 118,920 | $149,830 |
| Wholesale Trade · Sector | 6,780 | $135,550 |
| Finance and Insurance · Sector | 6,130 | $134,210 |
| Management of Companies and Enterprises · Sector | 5,880 | $138,480 |
| Direct Health and Medical Insurance Carriers · National industry | 3,590 | $134,630 |
| Administrative and Support and Waste Management and Remediation Services · Sector | 3,560 | $131,020 |
| Professional, Scientific, and Technical Services · Sector | 2,380 | $137,610 |
| Temporary Help Services · National industry | 1,950 | $130,720 |
| Educational Services · Sector | 1,880 | $142,560 |
| Manufacturing · Sector | 1,600 | $133,470 |
Industries where this occupation is far more common than in the economy as a whole. The location quotient is how many times more concentrated it is here (a value of 5 means five times its economy-wide share).
| Industry | Concentration | Workers |
|---|---|---|
| Pharmacies and Drug Retailers · National industry | 82.92× | 125,310 |
| Retail Trade · Sector | 5.15× | 171,400 |
| Direct Health and Medical Insurance Carriers · National industry | 3.75× | 3,590 |
| Health Care and Social Assistance · Sector | 2.41× | 118,920 |
| Management of Companies and Enterprises · Sector | 0.98× | 5,880 |
| Outpatient Mental Health and Substance Abuse Centers · National industry | 0.76× | 500 |
| Wholesale Trade · Sector | 0.53× | 6,780 |
| Finance and Insurance · Sector | 0.46× | 6,130 |
Part of the Healthcare & Human Services career cluster.
Side-by-side comparisons place two occupations’ pay, preparation, skills, and AI exposure on the same page — same data, same scale, no forecast.
Options the data surfaces for Pharmacists — not advice or a forecast. Each is a real cross-link you can follow into the evidence.
Capabilities this work builds that are used across many other occupations.
Occupations O*NET rates as related — the nearby moves on the map.
How people typically prepare for this work.
On the global GenAI exposure gradient this work sits around the 62nd percentile of 427 international occupations.
Pharmacists show 69th-percentile AI task overlap — and about 14,200 annual U.S. openings
Pharmacists show 69th-percentile AI task overlap — and about 14,200 annual U.S. openings • Pharmacists rank in the 69th percentile (High band) for AI task overlap across U.S. occupations — a measure of how much of the work today's AI can attempt, not how much is automated. (Eloundou et al. (GPTs are GPTs) + Felten AIOE) • The occupation is projected to see about 14,200 U.S. job openings per year (2024–34), counting growth and replacement — a labor-demand projection made independently of AI. (BLS Employment Projections 2024–34) • BLS projects employment to be about average (+4.6%) from 2024 to 2034. (BLS Employment Projections 2024–34) • Median annual pay is $137,480, across about 328,870 U.S. workers. (BLS OEWS (May 2024)) • Of the AI use actually observed for this work, 74% looks like augmentation (drafting, iterating, checking) rather than hands-off automation — from a Claude.ai usage sample, not a census. (2026-01-15-v4-plus-2025-03-27-v2) Source: Singulariki — "Pharmacists". https://singulariki.com/roles/role-29-1051-00 Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.
AssetsShare imageMethodology & sourcesPress & newsroomThe newsroom
Every line is built only from figures this page already shows and cites. AI task overlap means what today's AI can attempt — not automation, job loss, or a forecast.
Every figure above traces to a named public dataset and the exact release below — not hand-written opinion. See the full methodology for what each measure does and does not mean.
Data compiled June 2, 2026. Figures are estimates, not advice.
Singulariki. "Pharmacists." Singulariki: a source-backed encyclopedia of work. Built from O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); Microsoft “Working with AI” working-with-ai; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans; ILO / Gmyrek et al. GenAI exposure gradient 2025; IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022; Frey & Osborne (2013) frey-osborne-automation; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026. https://singulariki.com/roles/role-29-1051-00
Singulariki. (2026). Pharmacists. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-29-1051-00
@misc{singulariki-role-29-1051-00,
title = {Pharmacists},
author = {{Singulariki}},
year = {2026},
note = {O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); Microsoft “Working with AI” working-with-ai; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans; ILO / Gmyrek et al. GenAI exposure gradient 2025; IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022; Frey & Osborne (2013) frey-osborne-automation; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026},
url = {https://singulariki.com/roles/role-29-1051-00}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.