Coaches and Scouts
In short: today's best AI models could do about 33% 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 34% by the end of 2028 if progress keeps its long-run pace. The conversations, in-person and hands-on work, about 66% of the time, stays with people.
Instruct or coach groups or individuals in the fundamentals of sports for the primary purpose of competition. Demonstrate techniques and methods of participation. May evaluate athletes' strengths and weaknesses as possible recruits or to improve the athletes' technique to prepare them for competition. Those required to hold teaching certifications should be reported in the appropriate teaching category.
248,950 people do this job in the US. $47,320 a year.
Reviewed on September 30, 2026: what each task is made of, and what handing it over would ask.
A typical 40-hour week
- AI could take on1 h
- A person checks AI's work12 h
- Desk work AI can't do yet1 h
- Stays with people26 h
Coaches and Scouts, now: of a 40-hour week, AI could take on 1 hours, 12 hours become checking its work, 1 hours are desk work it can't do yet, and 26 hours stay with people.
The largest pieces: Analyze opponents (about 3 h, a person checks); Set strategy and pick the team (about 2 h, a person checks); Run camps and tryouts (under an hour, 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.
- 32%
- 2%
- 12%
- 51%
- 3%
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 33% 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, 14%. Today's estimate: 33%.
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, 0.042% went to this job's tasks in May 2026, the 239th largest of the 447 jobs that showed up at all; 1 of its 27 tasks showed up. Within each of Anthropic's methods, never across a change: 0.028% to 0.02% (released February and March 2025); 0.027% to 0.086% (August 2025 to February 2026); 0.045% to 0.042% (April to May 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.028% | 380 of 708 | 5 of 27 |
| Released March 2025 | 0.02% | 426 of 703 | 5 of 27 |
| The week of Aug 4, 2025 (released September 2025) | 0.027% | 331 of 655 | 6 of 27 |
| The week of Nov 13, 2025 (released January 2026) | 0.076% | 190 of 672 | 10 of 27 |
| The week of Feb 5, 2026 (released March 2026) | 0.086% | 180 of 677 | 11 of 27 |
| April 2026 (released June 2026) | 0.045% | 227 of 434 | 1 of 27 |
| May 2026 (released June 2026) | 0.042% | 239 of 447 | 1 of 27 |
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 16% of this job's working time as physical work. For 0% of the working time, a robot has been shown doing most of the task somewhere. 0.00 of 3.
- Not physical 84%
- No robot shown 16%
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
65% of the working time: the conversation, in-person and hands-on parts of the tasks.
- Run camps and tryouts, the in-person work, 9%
- Teach skills and strategy, the in-person work, 6%
- Run and referee games, the in-person work, 6%
- Direct and motivate athletes, the in-person work, 5%
- Run practices, the in-person work, 4%
- Hire and lead coaching staff, the conversation, 4%
What becomes checking the machine
31% 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 3% is desk work that is small if wrong, which can be handed over with lighter checks.
- Analyze opponents, costly if wrong, 8%
- Set strategy and pick the team, costly if wrong, 6%
- Run camps and tryouts, costly if wrong, 2%
- Run practices, costly if wrong, 2%
- Run conditioning programs, costly if wrong, 2%
- Evaluate athletes' potential, costly if wrong, 2%
What to learn
- The conversations. About 63% of the time is conversation and in-person work, which this site leaves with people: listening, explaining, persuading, calming.
- 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.
- Dealing with people outside the organization. Customers, patients, suppliers or the public: trust with them is built by a person.
- Briefing a model and checking its drafts. About 32% 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.
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 . 27 tasks from .
| Task | ||||
|---|---|---|---|---|
| Arrange and conduct sports-related activities, such as training camps, skill-improvement courses, clinics, and pre-season try-outs.Running the event, with the planning and the calls.Done more than yearly by most who do it. Robots: no robot shown. Anthropic's rating. | 12% | 6.7 h3.3 h to 2.1 work days | In person 60%, documents 20%, conversation 20% | 17%Desk part half by now |
| Plan strategies and choose team members for individual games or sports seasons.Planning at the desk, with the staff.Done daily by most who do it. | 9% | 2.5 h50 min to 5 h | Documents 70%, conversation 30% | 69%Desk part half by now |
| Analyze the strengths and weaknesses of opposing teams to develop game strategies.Film and analysis at the desk.Done more than weekly by most who do it. | 8% | 2.5 h50 min to 6.7 h | Documents 100% | 96%Half by now |
| Instruct individuals or groups in sports rules, game strategies, and performance principles, such as specific ways of moving the body, hands, or feet, to achieve desired results.Instruction on the field.Done daily by most who do it. | 6% | 1.1 h25 min to 2.1 h | In person 100% | Stays with people |
| Plan, organize, and conduct practice sessions.Practice on the field, with the plan written.Done daily by most who do it. | 6% | 1.7 h50 min to 3.3 h | In person 70%, documents 30% | 30%Desk part half by now |
| Serve as organizer, leader, instructor, or referee for outdoor and indoor games, such as volleyball, football, and soccer.On the field running the game.Done more than yearly by most who do it.Robots: no robot shown. Anthropic's rating. | 6% | 2.5 h50 min to 4.2 h | In person 100% | Stays with people |
| Hire, supervise, and work with extended coaching staff.Direction in conversation and on the field, with the hiring.Done yearly or less by most who do it. | 5% | 2.5 h50 min to 6.7 h | Conversation 50%, in person 30%, documents 20% | 19%Desk part half by now |
| Identify and recruit potential athletes by sending recruitment letters, meeting with recruits, and arranging and offering incentives, such as athletic scholarships.Letters, calls and visits with recruits.Done daily by most who do it. | 5% | 2.5 h50 min to 1 work day | Conversation 40%, in person 40%, documents 20% | 18%Desk part half by now |
| Provide training direction, encouragement, motivation, and nutritional advice to prepare athletes for games, competitive events, or tours.Coaching in person.Done daily by most who do it. | 5% | 50 min25 min to 2.5 h | In person 100% | Stays with people |
| Plan and direct physical conditioning programs that will enable athletes to achieve maximum performance.The program written and run in the gym.Done daily by most who do it. | 5% | 2.5 h50 min to 6.7 h | In person 60%, documents 40% | 38%Desk part half by now |
| Evaluate athletes' skills and review performance records to determine their fitness and potential in a particular area of athletics.Watching the athlete and reading the records.Done daily by most who do it. | 4% | 1.3 h38 min to 3.3 h | In person 60%, documents 40% | 40%Desk part half by now |
| Adjust coaching techniques, based on the strengths and weaknesses of athletes.Coaching in person, with the plan reworked.Done daily by most who do it. | 4% | 50 min17 min to 1.7 h | In person 80%, documents 20% | 20%Desk part 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.
- Umpires, Referees, and Other Sports Officials15% now, 15% by 2028
- Athletes and Sports Competitors12% now, 12% by 2028
- Exercise Trainers and Group Fitness Instructors48% now, 48% by 2028
- Athletic Trainers45% now, 46% by 2028
- Self-Enrichment Teachers40% now, 40% by 2028
- Training and Development Specialists43% now, 64% 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 Coaches and Scouts is within reach of AI now?
- An estimated 33% of the working time is within reach of AI models now and 34% by the end of 2028, on METR's long-run pace at four in five. 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 Coaches and Scouts 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: Analyze opponents (96% of the task's time now); Set strategy and pick the team (69% of the task's time now); and Run camps and tryouts (17% of the task's time now).
- Which tasks of Coaches and Scouts stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Teach skills and strategy; Run and referee games; and Direct and motivate athletes. Together such tasks are about 28% of the working time, and the people and body parts of the other tasks stay with people too.
- What should Coaches and Scouts learn as AI takes on more of the work?
- By the job's own task-by-task review, the first things to learn are the conversations; reviewing work you did not do yourself; and dealing with people outside the organization. By the end of 2028 on the long-run pace at four in five, about 65% of the working time stays with people, 31% becomes checking a model's work and 3% 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 Coaches and Scouts?
- In the Claude.ai conversations Anthropic sampled for May 2026 and tied to a work task, 0.042% went to this job's tasks, the 239th largest share of the 447 jobs that showed up; 1 of its 27 tasks appeared. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 0%. 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 Coaches and Scouts?
- Anthropic's robot exposure rating (September 2026) finds 16% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 0% of the working time. Its index is 0.00 of 3. A robot shown somewhere is not one in every workplace; this site's own estimates still count no physical work as within reach.
- How is this estimated?
- From the 27 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 September 30, 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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