Health Education Specialists
In short: today's best AI models could do about 31% of this job's working time (projected from METR's April 2026 measurement and Epoch's November 2026 index) if the work were set up for them, and about 75% by the end of 2028 if progress keeps its long-run pace. The conversations, in-person and hands-on work, about 24% of the time, stays with people.
Provide and manage health education programs that help individuals, families, and their communities maximize and maintain healthy lifestyles. Use data to identify community needs prior to planning, implementing, monitoring, and evaluating programs designed to encourage healthy lifestyles, policies, and environments. May link health systems, health providers, insurers, and patients to address individual and population health needs. May serve as resource to assist individuals, other health professionals, or the community, and may administer fiscal resources for health education programs.
65,690 people do this job in the US. $64,070 a year.
Reviewed on October 2, 2026: what each task is made of, and what handing it over would ask.
A typical 40-hour week
- AI could take on3 h
- A person checks AI's work9 h
- Desk work AI can't do yet18 h
- Stays with people10 h
Health Education Specialists, now: of a 40-hour week, AI could take on 3 hours, 9 hours become checking its work, 18 hours are desk work it can't do yet, and 10 hours stay with people.
The largest pieces: Maintain program databases and lists (about 1 h); Prepare and distribute health materials (about 1 h, a person checks); Develop materials for agencies (about 1 h, a person checks).
Estimates for a typical week of this job, if progress keeps its long-run pace, counting work the best models finish four times in five. Every task is below.
of the working time. Now is projected from METR's April 2026 measurement and Epoch's November 2026 index.
- 68%
- 8%
- 10%
- 11%
- 2%
of the work: Anthropic's measure of what people already bring to Claude at work (2025). It counts help with part of a task, so it can be higher than the share within reach.
On the chosen pace and reliability. Estimate.
Share of the working time within reach, now to 2030
Change assumptionsHide assumptionsLong-run pace, four in five
What each choice means: , , , , . Every pace starts from .
At this date and pace, models finish tasks up to 2.4 work days long four times in five.
What handing it over would take, now
The 31% within reach splits by what a model would need. The dates, pace and reliability follow the controls above. Estimates.
of the working time. The material can be handed to a model and the result handed back.
of the working time. The model has to be connected to the system the work lives in.
is conversation short enough by length. This site leaves conversation with people, so it is not in the total.
How far this has come
With GPT-4, measured in March 2023, 0% of this job's working time was within reach at . With Claude 3.7 Sonnet, measured in February 2025, 0%. With Claude Mythos Preview (early), measured in April 2026, 7%. Today's estimate: 31%.
A backcast: today's task data with the best model METR had measured by each date. It shows how fast the models have moved, not what anyone forecast at the time.
Measured use over time
Of the Claude.ai conversations Anthropic sampled and tied to a work task, no reportable share went to this job's tasks in May 2026; 0 of its 16 tasks showed up. Within each of Anthropic's methods, never across a change: 0.041% to 0.047% (released February and March 2025); 0.038% to 0.032% (August 2025 to February 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.041% | 304 of 708 | 6 of 16 |
| Released March 2025 | 0.047% | 277 of 703 | 3 of 16 |
| The week of Aug 4, 2025 (released September 2025) | 0.038% | 276 of 655 | 4 of 16 |
| The week of Nov 13, 2025 (released January 2026) | 0.038% | 277 of 672 | 6 of 16 |
| The week of Feb 5, 2026 (released March 2026) | 0.032% | 320 of 677 | 7 of 16 |
| April 2026 (released June 2026) | none | n/a | 0 of 16 |
| May 2026 (released June 2026) | none | n/a | 0 of 16 |
Measured, not estimated: Anthropic's samples of Claude.ai conversations, each tied by a model to an O*NET task, from the Anthropic Economic Index. It says where Claude's use goes, not how much of this job's working time it covers, so it is not on the same scale as the reach above. The releases differ in their sample, their classifier and the smallest share they report (the June 2026 file rounds each task to a hundredth of a percent, so a smaller task reads as none), which is why a change of method starts a new line. At least 96% of each older release's task-tied use matched this site's tasks, and all of the newest. Claude.ai only, so use through other tools and other companies' models is not in it. Every job ranked.
Robots and the physical work
Anthropic rates almost none of this job's working time as physical work, so robots do not reach it.
Anthropic's rating, not this site's estimate: Claude Opus 5, searching the web, rated each physical O*NET task by the kind of setting in which a robot it could cite (deployed, sold or demonstrated) does most of the task, weighted by its own estimate of each task's share of the time (What work can robots do?, September 30, 2026, data CC BY 4.0; every job ranked). A robot shown somewhere is not a robot in your building: cost, setup and safety decide that. The share within reach on this page still counts no body work. The robot behind each rated task is under the task below.
What changes for the people in this job
From the task-by-task review, by the end of 2028 on the long-run pace at four in five. It says which parts of the work stay with people and which change, not whether anyone keeps a job: that depends on decisions no data set can see.
What stays with people
23% of the working time: the conversation, in-person and hands-on parts of the tasks.
- Develop and present health programs, the in-person work, 6%
- Work with groups on community health needs, the conversation, 4%
- Build relationships with agencies, the conversation, 3%
- Supervise program staff, the conversation, 2%
- Design and run staff training, the in-person work, 2%
- Prepare grant applications, the conversation, 2%
What becomes checking the machine
66% of the working time: desk work a model could do by then, in tasks where a mistake costs something or a licensed person signs. A person checks it. Another 8% is desk work that is small if wrong, which can be handed over with lighter checks.
- Evaluate health education programs, costly if wrong, 15%
- Develop materials for agencies, costly if wrong, 12%
- Develop program plans and policies, costly if wrong, 9%
- Prepare grant applications, costly if wrong, 7%
- Conduct health needs assessments, costly if wrong, 7%
- Prepare and distribute health materials, costly if wrong, 5%
What to learn
- Reviewing work you did not do yourself. The tasks under What becomes checking the machine, where a mistake costs something, stay a person's to check: spotting what a draft gets wrong is a skill of its own.
- Briefing a model and checking its drafts. About 68% of the time is documents and data, the part models reach first: writing a clear brief, giving the right material, and checking what comes back.
- Dealing with people outside the organization. Customers, patients, suppliers or the public: trust with them is built by a person.
- The conversations. About 22% of the time is conversation and in-person work, which this site leaves with people: listening, explaining, persuading, calming.
Your own version of this job: read it against your job description. The headline is free; the full personal report, every task with its timeline and what to learn, is $19 (a sample).
The tasks
Sorted by . 16 tasks from .
| Task | ||||
|---|---|---|---|---|
| Design and conduct evaluations and diagnostic studies to assess the quality and performance of health education programs.Designing the evaluation and analyzing the program's results.Done more than yearly by most who do it. | 15% | 2.1 work days5 h to 1.7 work weeks | Documents 100% | 19%Half by Jul 2027 |
| Develop educational materials and programs for community agencies, local government, and state government.Writing the education materials and program designs for the agencies.Done yearly or less by most who do it. AI observed on this task. | 12% | 1.7 work days3.3 h to 1.3 work weeks | Documents 100% | 24%Half by May 2027 |
| Develop and present health education and promotion programs, such as training workshops, conferences, and school or community presentations.Building the workshop and giving it in the school or community room.Done more than yearly by most who do it. | 10% | 6.7 h1.7 h to 2.1 work days | In person 60%, documents 40% | 25%Desk part half by now |
| Develop, prepare, and coordinate grant applications and grant-related activities to obtain funding for health education programs and related work.Writing the grant applications and keeping the grant's reporting in order, with calls to the funder.Done more than yearly by most who do it. | 10% | 2.1 work days5 h to 1.7 work weeks | Documents 80%, conversation 20% | 16%Desk part half by Jul 2027 |
| Develop operational plans and policies necessary to achieve health education objectives and services.Writing the plans and policies the program runs by.Done more than yearly by most who do it. | 9% | 1.7 work days3.3 h to 1 work week | Documents 100% | 28%Half by Apr 2027 |
| Develop, conduct, or coordinate health needs assessments and other public health surveys.Designing the survey, running it and analyzing what comes back.Done yearly or less by most who do it. | 9% | 1.7 work days6.7 h to 1.7 work weeks | Documents 80%, conversation 20% | 25%Desk part half by Mar 2027 |
| Prepare and distribute health education materials, such as reports, bulletins, and visual aids, to address smoking, vaccines, and other public health concerns.Writing and designing the bulletins and visual aids, and getting them out.Done more than weekly by most who do it. AI observed on this task. | 6% | 3.3 h50 min to 1.7 work days | Documents 80%, hands-on 20% | 57%Desk part half by now |
| Design and administer training programs for new employees and continuing education for existing employees.Designing the training and delivering it to the staff.Done yearly or less by most who do it. | 4% | 1.3 work days2.5 h to 4.2 work days | Documents 50%, in person 50% | 18%Desk part half by Feb 2027 |
| Supervise professional and technical staff in implementing health programs, objectives, and goals.Directing the program staff in meetings and one to one, with the plans and reviews behind it.Done daily by most who do it. | 4% | 1.7 h50 min to 3.3 h | Conversation 60%, documents 40% | 40%Desk part half by now |
| Develop and maintain health education libraries to provide resources for staff and community agencies.Choosing and cataloging the materials and keeping the collection in order.Done more than monthly by most who do it. | 4% | 3.3 h50 min to 6.7 h | Systems 40%, documents 30%, hands-on 30% | 64%Desk part half by now |
| Collaborate with health specialists and civic groups to determine community health needs and the availability of services and to develop goals for meeting needs.Meetings with health specialists and civic groups, some in the community, to agree on needs and goals.Done yearly or less by most who do it. | 4% | 3.3 h1.7 h to 1.3 work days | Conversation 50%, in person 50% | Stays with people |
| Maintain databases, mailing lists, telephone networks, and other information to facilitate the functioning of health education programs.Keeping the mailing lists and contact databases current.Done more than weekly by most who do it. | 3% | 1.3 h25 min to 2.5 h | Systems 100% | 100%Half by now |
Within reach, per task: the share of the task's time whose instances are short enough for a model to finish at the chosen date, pace and reliability. Half by: the date half of that time comes within reach. Made of: how the task's time splits among five kinds of doing. Only the documents and systems parts can count as within reach, so a task that is 30% documents can be at most 30% within reach.
Jobs that share skills with this one
From O*NET's related occupations. Within reach now and by the end of 2028, long-run pace, four in five.
- Community Health Workers21% now, 21% by 2028
- Nursing Instructors and Teachers, Postsecondary20% now, 37% by 2028
- Rehabilitation Counselors64% now, 64% by 2028
- Health Informatics Specialists40% now, 95% by 2028
- Healthcare Social Workers32% now, 50% by 2028
- Health Specialties Teachers, Postsecondary26% now, 49% by 2028
Where this job works
The industry groups that employ the most of it (BLS, May 2025).
Where the most of these jobs are
The metro areas with the most people in it (BLS, May 2025).
Questions about this job
- How much of the work of Health Education Specialists is within reach of AI now?
- An estimated 31% of the working time is within reach of AI models now and 75% by the end of 2028, on METR's long-run pace at four in five (64% to 76% across the three paces the site shows). Within reach means a model could finish work that long at that reliability. It is not a forecast of jobs lost or of savings.
- Which tasks of Health Education Specialists come within reach first?
- Weighted by the time each takes, the tasks with the most within reach now (projected from METR's April 2026 measurement and Epoch's November 2026 index) are: Maintain program databases and lists (100% of the task's time now); Prepare and distribute health materials (57% of the task's time now, 80% by the end of 2028); and Develop materials for agencies (24% of the task's time now, 98% by the end of 2028).
- Which tasks of Health Education Specialists stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Work with groups on community health needs; and Build relationships with agencies. Together such tasks are about 7% of the working time, and the people and body parts of the other tasks stay with people too.
- What should Health Education Specialists learn as AI takes on more of the work?
- By the job's own task-by-task review, the first things to learn are reviewing work you did not do yourself; briefing a model and checking its drafts; and dealing with people outside the organization. By the end of 2028 on the long-run pace at four in five, about 23% of the working time stays with people, 66% becomes checking a model's work and 8% could be handed over with lighter checks. It says which parts of the work change, never whether anyone keeps a job.
- Do people already use AI for the work of Health Education Specialists?
- In the Claude.ai conversations Anthropic sampled for May 2026, no reportable share went to this job's tasks. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 14%. These are measures of use, not of how much of the work AI could finish, and they cover Claude only.
- Can robots do the physical work of Health Education Specialists?
- Anthropic's robot exposure rating (September 2026) finds almost none of the working time is physical work, so robots do not reach it.
- How is this estimated?
- From the 16 tasks O*NET lists for the occupation, each with an estimated length checked against GDPval and a share of the working time, reviewed one task at a time on October 2, 2026 for what each is made of (documents, business systems, conversation, in person, hands-on), and METR's measurements of how long a task the best AI models can finish, carried forward to the date from the latest, Claude Mythos Preview (early) in April 2026. Data checked November 10, 2026.
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