Astronomers
In short: today's best AI models could do about 24% 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 60% by the end of 2028 if progress keeps its long-run pace. The people and hands-on work, about 35% of the time, stays with people.
Observe, research, and interpret astronomical phenomena to increase basic knowledge or apply such information to practical problems.
2,120 people do this job in the US. $128,820 a year.
A typical 40-hour week
Not yet reviewed task by task- AI could take on10 h
- A person checks AI's work0 h
- Desk work AI can't do yet16 h
- Stays with people14 h
Astronomers, now: of a 40-hour week, AI could take on 10 hours, 0 hours become checking its work, 16 hours are desk work it can't do yet, and 14 hours stay with people.
The largest pieces: Analyze research data to determine its significance, using computers (about 5 h); Study celestial phenomena, using a variety of ground-based and space-borne telescopes and scientific instruments (about 3 h); Develop theories based on personal observations or on observations and theories of other astronomers (under an hour).
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.
- 65%
- 15%
- 20%
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.
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, 2%. Today's estimate: 24%.
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, 0.095% went to this job's tasks in May 2026, the 165th largest of the 447 jobs that showed up at all; 2 of its 17 tasks showed up. Within each of Anthropic's methods, never across a change: 0.17% to 0.31% (released February and March 2025); 0.12% to 0.083% (August 2025 to February 2026); 0.1% to 0.095% (April to May 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.17% | 106 of 708 | 9 of 17 |
| Released March 2025 | 0.31% | 59 of 703 | 9 of 17 |
| The week of Aug 4, 2025 (released September 2025) | 0.12% | 143 of 655 | 7 of 17 |
| The week of Nov 13, 2025 (released January 2026) | 0.097% | 158 of 672 | 8 of 17 |
| The week of Feb 5, 2026 (released March 2026) | 0.083% | 188 of 677 | 8 of 17 |
| April 2026 (released June 2026) | 0.1% | 158 of 434 | 2 of 17 |
| May 2026 (released June 2026) | 0.095% | 165 of 447 | 2 of 17 |
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 7% 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 93%
- No robot shown 7%
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.
The tasks
Sorted by . 17 tasks from .
| Task | Kind | |||
|---|---|---|---|---|
| Develop theories based on personal observations or on observations and theories of other astronomers.Done more than yearly by most who do it. | 23% | 4.2 work days6.7 h to 3.3 work weeks | 5%Half by Apr 2028 | |
| Analyze research data to determine its significance, using computers.Done more than weekly by most who do it. AI observed on this task. | 22% | 6.7 h1.7 h to 2.5 work days | 55%Half by now | |
| Develop instrumentation and software for astronomical observation and analysis.Done more than monthly by most who do it. AI observed on this task.Robots: no robot shown. Anthropic's rating. | 19% | 4.2 work days6.7 h to 4.2 work weeks | Stays with people | |
| Study celestial phenomena, using a variety of ground-based and space-borne telescopes and scientific instruments.Done more than monthly by most who do it. AI observed on this task. | 14% | 1 work day2.5 h to 2.5 work days | 59%Half by now | |
| Collaborate with other astronomers to carry out research projects.Done more than weekly by most who do it. | 4% | 3.3 h50 min to 1.7 work days | Stays with people | |
| Supervise students' research on celestial and astronomical phenomena.Done more than weekly by most who do it. | 4% | 2.5 h1.3 h to 1 work day | Stays with people | |
| Teach astronomy or astrophysics.Done more than weekly by most who do it. | 4% | 3.3 h1.7 h to 1 work day | Stays with people | |
| Present research findings at scientific conferences and in papers written for scientific journals.Done more than yearly by most who do it. | 2% | 2.5 work days6.7 h to 4.2 work days | Stays with people | |
| Direct the operations of a planetarium.Done yearly or less by most who do it. | 2% | 2.5 work days6.7 h to 4.2 work days | Stays with people | |
| Develop and modify astronomy-related programs for public presentation.Done more than monthly by most who do it. | 1% | 1 work day2.5 h to 4.2 work days | 43%Half by Dec 2026 | |
| Mentor graduate students and junior colleagues.Done more than weekly by most who do it. | 1% | 1.3 h25 min to 3.3 h | Stays with people | |
| Measure radio, infrared, gamma, and x-ray emissions from extraterrestrial sources.Done more than yearly by most who do it. | 1% | 6.7 h1.7 h to 4.2 work days | 40%Half by Jan 2027 |
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.
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.
- Physicists23% now, 68% by 2028
- Mathematicians18% now, 68% by 2028
- Physics Teachers, Postsecondary46% now, 73% by 2028
- Geoscientists, Except Hydrologists and Geographers20% now, 80% by 2028
- Biochemists and Biophysicists11% now, 61% by 2028
- Atmospheric, Earth, Marine, and Space Sciences Teachers, Postsecondary46% now, 74% 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 Astronomers is within reach of AI now?
- An estimated 24% of the working time is within reach of AI models now and 60% by the end of 2028, on METR's long-run pace at four in five (48% to 64% 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 Astronomers 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 research data to determine its significance, using computers (55% of the task's time now, 100% by the end of 2028); Study celestial phenomena, using a variety of ground-based and space-borne telescopes and scientific instruments (59% of the task's time now, 100% by the end of 2028); and Develop theories based on personal observations or on observations and theories of other astronomers (5% of the task's time now, 80% by the end of 2028).
- Which tasks of Astronomers stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Develop instrumentation and software for astronomical observation and analysis; Collaborate with other astronomers to carry out research projects; and Supervise students' research on celestial and astronomical phenomena. Together such tasks are about 35% of the working time.
- Do people already use AI for the work of Astronomers?
- In the Claude.ai conversations Anthropic sampled for May 2026 and tied to a work task, 0.095% went to this job's tasks, the 165th largest share of the 447 jobs that showed up; 2 of its 17 tasks appeared. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 38%. 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 Astronomers?
- Anthropic's robot exposure rating (September 2026) finds 7% 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 17 tasks O*NET lists for the occupation, each with an estimated length checked against GDPval and a share of the working time, each classed as desk, people or body work, 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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