AI exposure by occupation, O*NET 31-9099.01

Will AI replace Speech-Language Pathology Assistants?

Speech-Language Pathology Assistants: AI can already handle 2 of 11 tasks; the work mostly needs an efficient-tier model.

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Every task, scored

The 11 tasks O*NET 30.3 lists for Speech-Language Pathology Assistants, from most to least exposed. 2 reach 60 or more, the level at which AI already handles a task.

Task AI exposure Evidence Model tier Importance
Collect and compile data to document clients' performance or assess program quality. 80 Estimated Efficient 4.8
Assist speech-language pathologists in the conduct of client screenings or assessments of language, voice, fluency, articulation, or hearing. 65 Estimated Standard 3.8
Implement treatment plans or protocols as directed by speech-language pathologists. 50 Estimated Efficient 4.9
Assist speech-language pathologists in the remediation or development of speech and language skills. 50 Estimated Efficient 4.7
Conduct in-service training sessions, or family and community education programs. 35 Estimated Efficient 3.4
Document clients' progress toward meeting established treatment objectives. 30 Estimated Efficient 4.9
Select or prepare speech-language instructional materials. 30 Estimated Standard 4.5
Prepare charts, graphs, or other visual displays to communicate clients' performance information. 30 Estimated Efficient 3.8
Assist speech-language pathologists in the conduct of speech-language research projects. 30 Estimated Efficient 2.6
Perform support duties, such as preparing materials, keeping records, maintaining supplies, and scheduling activities. 20 Estimated Efficient 4.7
Test or maintain equipment to ensure correct performance. 20 Estimated Efficient 3.6

Observed: scored from AI use recorded in the Anthropic Economic Index (June 2026 release), 0 of 11 tasks. Estimated: scored from the task's O*NET 30.3 work activity, 11 of 11. Importance is O*NET's 1 to 5 rating of how central the task is. Model tier is the lowest tier that can do the task under the published rubric; "No tier" marks hands-on work.

The model tier this role needs

An efficient-tier model or lower covers 82% of the role's importance-weighted task work. 100% of the work is something AI can address at some tier.

Efficient, standard and frontier tiers come from the JobRoute model tier reference. The recommended tier is the lowest one that covers 80% of the work AI can address. How the method works.

Wages, employment and outlook

US employment
109,740
Median annual wage
$48,430
Middle half of earners
$39,470 to $59,710
Projected change, 2024 to 2034
+3.5%

Employment and wages: BLS Occupational Employment and Wage Statistics, May 2025, national. Projection: BLS Employment Projections 2024 to 2034. BLS publishes these figures by SOC code, so O*NET occupations that share a SOC code show the same figures.

Adjacent roles

The occupations that reuse the most of this role's skills, with the usual time to move. These are the first places to look when you plan to redeploy or retrain people in this role.

Skill overlap and transition time from the JobRoute role adjacency graph on O*NET 30.3 skills.

Questions about Speech-Language Pathology Assistants and AI

Will AI replace Speech-Language Pathology Assistants?

AI already handles 2 of the 11 tasks O*NET lists for this occupation, at a task exposure of 60 or more, and the role's importance-weighted exposure is 41 out of 100. JobRoute scores tasks, not whole jobs, so the score shows how much of the work changes rather than whether the job disappears. BLS projects employment to change by +3.5% from 2024 to 2034.

What is the AI exposure of Speech-Language Pathology Assistants?

41 out of 100 on JobRoute's task exposure measure, the importance-weighted average of the role's O*NET task scores. Higher means more of the work is AI-doable today. 0 of the 11 task scores are observed in the Anthropic Economic Index (June 2026 release), and the other 11 are estimated from each task's O*NET work activity.

Which Speech-Language Pathology Assistants tasks can AI already do?

The tasks with the highest exposure are: Collect and compile data to document clients' performance or assess program quality; Assist speech-language pathologists in the conduct of client screenings or assessments of language, voice, fluency, articulation, or hearing. They are the tasks that reach 60 or more.

What AI model tier does this role need?

An efficient-tier model or lower covers 82% of the role's importance-weighted task work. JobRoute assigns each task the lowest tier that can do it under a published rubric and recommends the lowest tier that covers 80% of the work AI can address.

How many people work as Speech-Language Pathology Assistants, and what do they earn?

109,740 people in the United States, with a median annual wage of $48,430 (BLS Occupational Employment and Wage Statistics, May 2025). BLS Employment Projections expect a change of +3.5% from 2024 to 2034.

How to cite

Data version 2026-11-02, JobRoute method v1.0.0. Download all occupations or this occupation as JSON. Methodology.

JobRoute (2026). AI exposure: Speech-Language Pathology Assistants. Data version 2026-11-02, method v1.0.0. Built on O*NET 30.3, BLS OEWS May 2025 and the Anthropic Economic Index (June 2026). CC BY 4.0. https://www.jobroute.ai/jobs/speech-language-pathology-assistants

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