Often handed to AI
Task areas most often handled directively in observed AI conversations — candidates to delegate with light review.
- Monitor patients' progress and adjust treatments accordingly. · 0.4%
Occupation · SOC 29-1127.00
Assess and treat persons with speech, language, voice, and fluency disorders. May select alternative communication systems and teach their use. May perform research related to speech and language problems.
Also called: Bilingual Speech-Language Pathologist (Bilingual SLP) · Speech Pathologist · Speech and Language Specialist · Speech-Language Pathologist (SLP) · Pediatric Speech-Language Pathologist (Pediatric SLP) · Speech Clinician · Speech Therapist · Speech and Language Clinician · Speech and Language Teacher · Speech and Language Therapist · Home Health SLP (Home Health Speech Language Pathologist) · Language Pathologist
Job family: Healthcare Practitioners and Technical Occupations
A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch
/roles/role-29-1127-00/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 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.
60th-percentile task overlap — yet about 13,300 openings a year (+15% projected, BLS) . 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.) High | 81st | 1.1 | |
| LLM task exposure, γ (OpenAI / Eloundou) Moderate | 58th | 0.7 | |
| AI assistant applicability (Microsoft) Moderate | 45th | 0.1 |
OpenAI's exposure study scores tasks three ways: with a language model alone (α 0.2), with simple added tooling (β 0.5), 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.
Most of this job's tasks can be done remotely (Dingel–Neiman), which tends to track with higher digital and AI exposure.
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 · 4th 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.
| Monitor patients' progress and adjust treatments accordingly. | 0.4% | |
| Write reports and maintain proper documentation of information, such as client Medicaid or billing records or caseload activities, including the initial evaluation, treatment, progress, and discharge of clients. | 0.4% | |
| Provide communication instruction to dialect speakers or students with limited English proficiency. | 0.3% | |
| Conduct or direct research on speech or hearing topics and report findings for use in developing procedures, technologies, or treatments. | 0.2% | |
| Develop or implement treatment plans for problems such as stuttering, delayed language, swallowing disorders, or inappropriate pitch or harsh voice problems, based on own assessments and recommendations of physicians, psychologists, or social workers. | 0.2% |
Independent U.S. Bureau of Labor Statistics employment projection for 2024–2034 — a labor-market forecast, not an AI-impact forecast.
| Outlook | Growing fast · +15.0% by 2034 |
| Projected annual openings | 13,300 |
| Employment 2024 → 2034 | 187,400 → 215,500 |
“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 |
|---|---|---|
| Audiologists and Speech Therapists · 2266 | 24% | Not exposed |
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.
| Most common way people use AI here | Feedback loop · AI does it, then adjusts from your feedback |
| Typical AI autonomy | 4.0 / 5 · higher = AI acts more independently |
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 |
|---|---|---|
| Monitor patients' progress and adjust treatments accordingly. | Feedback loop | 0.4% |
Tasks where the model most often judged that a person remained necessary — a useful read on the current boundary, not a guarantee.
| Monitor patients' progress and adjust treatments accordingly. | 73.7% |
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 monitor patients' progress and adjust treatments accordingly. From: Monitor patients' progress and adjust treatments accordingly. · 0.4% of measured AI use · feedback loop
All 24 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).
| Oral Comprehension | 4.5 | |
| Oral Expression | 4.3 | |
| Written Expression | 4.3 | |
| Speech Recognition | 4.3 | |
| Written Comprehension | 4.1 | |
| Speech Clarity | 4.1 | |
| Problem Sensitivity | 4.0 | |
| Deductive Reasoning | 4.0 | |
| Inductive Reasoning | 4.0 | |
| Fluency of Ideas | 3.8 | |
| Information Ordering | 3.8 | |
| Category Flexibility | 3.8 | |
| Near Vision | 3.6 | |
| Hearing Sensitivity | 3.6 | |
| Originality | 3.3 | |
| Flexibility of Closure | 3.3 |
| Reading Comprehension | 4.1 | |
| Active Listening | 4.1 | |
| Critical Thinking | 4.1 | |
| Writing | 4.0 | |
| Speaking | 4.0 | |
| Learning Strategies | 4.0 | |
| Active Learning | 3.9 | |
| Monitoring | 3.9 |
| Social Perceptiveness | 4.1 | |
| Instructing | 3.9 | |
| Complex Problem Solving | 3.9 | |
| Service Orientation | 3.8 | |
| Judgment and Decision Making | 3.8 | |
| Coordination | 3.3 | |
| Time Management | 3.3 | |
| Systems Analysis | 3.1 |
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: 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.
| Master's Degree | 88.5% | |
| Post-Master's Certificate | 11.5% |
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 | |
| Cooperation | 6.0 | |
| Social Orientation | 5.0 | |
| Self-Control | 4.0 |
| Health Care Service | 6.4 | |
| Social Service | 6.0 | |
| Teaching/Education | 5.1 | |
| Professional Advising | 4.4 | |
| Social Science | 4.0 | |
| Medical Science | 3.7 |
| Social | 6.1 | |
| Investigative | 5.6 | |
| Conventional | 4.0 |
U.S. · annual wages (BLS OEWS)
| 10th percentile | $60,480 |
| 25th percentile | $75,310 |
| Median (50th) | $95,410 |
| 75th percentile | $112,510 |
| 90th percentile | $132,850 |
| People employed | 178,790 |
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 |
|---|---|---|
| Health Care and Social Assistance · Sector | 95,310 | $101,230 |
| Educational Services · Sector | 75,020 | $80,280 |
| Offices of Physical, Occupational and Speech Therapists, and Audiologists · National industry | 47,050 | $98,470 |
| Administrative and Support and Waste Management and Remediation Services · Sector | 2,990 | $101,190 |
| Temporary Help Services · National industry | 2,760 | $100,140 |
| Services for the Elderly and Persons with Disabilities · National industry | 1,850 | $85,060 |
| Management of Companies and Enterprises · Sector | 930 | $75,990 |
| Offices of Mental Health Practitioners (except Physicians) · National industry | 900 | $114,050 |
| Residential Intellectual and Developmental Disability Facilities · National industry | 430 | $93,780 |
| Outpatient Mental Health and Substance Abuse Centers · National industry | 220 | $79,130 |
| Residential Mental Health and Substance Abuse Facilities · National industry | 120 | $75,000 |
| Other Services (except Public Administration) · Sector | 100 | $86,700 |
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 |
|---|---|---|
| Offices of Physical, Occupational and Speech Therapists, and Audiologists · National industry | 85.14× | 47,050 |
| Educational Services · Sector | 4.74× | 75,020 |
| Health Care and Social Assistance · Sector | 3.56× | 95,310 |
| Offices of Mental Health Practitioners (except Physicians) · National industry | 3.21× | 900 |
| Residential Intellectual and Developmental Disability Facilities · National industry | 0.95× | 430 |
| Temporary Help Services · National industry | 0.9× | 2,760 |
| Services for the Elderly and Persons with Disabilities · National industry | 0.66× | 1,850 |
| Outpatient Mental Health and Substance Abuse Centers · National industry | 0.61× | 220 |
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 Speech-Language Pathologists — 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 43rd percentile of 427 international occupations.
Speech-Language Pathologists show 60th-percentile AI task overlap — and about 13,300 annual U.S. openings
Speech-Language Pathologists show 60th-percentile AI task overlap — and about 13,300 annual U.S. openings • Speech-Language Pathologists rank in the 60th percentile (Moderate 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 13,300 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 growing fast (+15%) from 2024 to 2034. (BLS Employment Projections 2024–34) • Median annual pay is $95,410, across about 178,790 U.S. workers. (BLS OEWS (May 2024)) Source: Singulariki — "Speech-Language Pathologists". https://singulariki.com/roles/role-29-1127-00 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. "Speech-Language Pathologists." 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-29-1127-00
Singulariki. (2026). Speech-Language Pathologists. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-29-1127-00
@misc{singulariki-role-29-1127-00,
title = {Speech-Language Pathologists},
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-29-1127-00}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.