Mathematicians
In short: today's best AI models could do about 18% 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 68% by the end of 2028 if progress keeps its long-run pace. The people and hands-on work, about 1% of the time, stays with people.
Conduct research in fundamental mathematics or in application of mathematical techniques to science, management, and other fields. Solve problems in various fields using mathematical methods.
2,030 people do this job in the US. $126,710 a year.
A typical 40-hour week
Not yet reviewed task by task- AI could take on7 h
- A person checks AI's work0 h
- Desk work AI can't do yet33 h
- Stays with people0 h
Mathematicians, now: of a 40-hour week, AI could take on 7 hours, 0 hours become checking its work, 33 hours are desk work it can't do yet, and 0 hours stay with people.
The largest pieces: Address the relationships of quantities, magnitudes, and forms through the use of numbers and symbols (about 2 h); Perform computations and apply methods of numerical analysis to data (about 2 h); Assemble sets of assumptions, and explore the consequences of each set (about 1 h).
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.
- 99%
- 1%
- 0%
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, 3%. Today's estimate: 18%.
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, 1% went to this job's tasks in May 2026, the 24th largest of the 447 jobs that showed up at all; 6 of its 12 tasks showed up. Within each of Anthropic's methods, never across a change: 0.36% to 0.4% (released February and March 2025); 0.24% to 0.18% (August 2025 to February 2026); 0.97% to 1% (April to May 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.36% | 54 of 708 | 9 of 12 |
| Released March 2025 | 0.4% | 43 of 703 | 9 of 12 |
| The week of Aug 4, 2025 (released September 2025) | 0.24% | 76 of 655 | 6 of 12 |
| The week of Nov 13, 2025 (released January 2026) | 0.24% | 68 of 672 | 7 of 12 |
| The week of Feb 5, 2026 (released March 2026) | 0.18% | 100 of 677 | 6 of 12 |
| April 2026 (released June 2026) | 0.97% | 26 of 434 | 5 of 12 |
| May 2026 (released June 2026) | 1% | 24 of 447 | 6 of 12 |
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.
The tasks
Sorted by . 12 tasks from .
| Task | Kind | |||
|---|---|---|---|---|
| Apply mathematical theories and techniques to the solution of practical problems in business, engineering, the sciences, or other fields.Done more than monthly by most who do it. | 12% | 2.1 work days3.3 h to 2.1 work weeks | 13%Half by Nov 2027 | |
| Develop mathematical or statistical models of phenomena to be used for analysis or for computational simulation.Done more than weekly by most who do it. AI observed on this task. | 12% | 4.2 work days6.7 h to 3.3 work weeks | 5%Half by Apr 2028 | |
| Develop computational methods for solving problems that occur in areas of science and engineering or that come from applications in business or industry.Done more than weekly by most who do it. | 12% | 4.2 work days6.7 h to 3.3 work weeks | 5%Half by Apr 2028 | |
| Design, analyze, and decipher encryption systems designed to transmit military, political, financial, or law-enforcement-related information in code.Done yearly or less by most who do it. | 12% | 1.7 work weeks1.7 work days to 1.6 work months | 1%Half by Oct 2028 | |
| Develop new principles and new relationships between existing mathematical principles to advance mathematical science.Done daily by most who do it. AI observed on this task. | 12% | 3.5 work weeks1.7 work days to 3.2 work months | 0%Half by Nov 2029 | |
| Conduct research to extend mathematical knowledge in traditional areas, such as algebra, geometry, probability, and logic.Done daily by most who do it. AI observed on this task. | 12% | 3.5 work weeks1.7 work days to 4 work months | 0%Half by Jan 2030 | |
| Assemble sets of assumptions, and explore the consequences of each set.Done more than monthly by most who do it. | 8% | 6.7 h1.7 h to 4.2 work days | 40%Half by Jan 2027 | |
| Address the relationships of quantities, magnitudes, and forms through the use of numbers and symbols.Done daily by most who do it. AI observed on this task. | 8% | 3.3 h50 min to 2.1 work days | 63%Half by now | |
| Perform computations and apply methods of numerical analysis to data.Done more than weekly by most who do it. | 5% | 3.3 h1.3 h to 1.7 work days | 84%Half by now | |
| Disseminate research by writing reports, publishing papers, or presenting at professional conferences.Done more than yearly by most who do it. | 4% | 2.1 work days3.3 h to 1.7 work weeks | 14%Half by Oct 2027 | |
| Maintain knowledge in the field by reading professional journals, talking with other mathematicians, and attending professional conferences.Done daily by most who do it. | 2% | 2.5 h50 min to 6.7 h | 96%Half by now | |
| Mentor others on mathematical techniques.Done more than monthly by most who do it. | 0.9% | 50 min25 min to 2.5 h | Stays with people |
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.
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 Mathematicians is within reach of AI now?
- An estimated 18% of the working time is within reach of AI models now and 68% by the end of 2028, on METR's long-run pace at four in five (41% to 86% 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 Mathematicians 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: Address the relationships of quantities, magnitudes, and forms through the use of numbers and symbols (63% of the task's time now, 100% by the end of 2028); Perform computations and apply methods of numerical analysis to data (84% of the task's time now, 100% by the end of 2028); and Assemble sets of assumptions, and explore the consequences of each set (40% of the task's time now, 99% by the end of 2028).
- Which tasks of Mathematicians stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Mentor others on mathematical techniques. Together such tasks are about 1% of the working time.
- Do people already use AI for the work of Mathematicians?
- In the Claude.ai conversations Anthropic sampled for May 2026 and tied to a work task, 1% went to this job's tasks, the 24th largest share of the 447 jobs that showed up; 6 of its 12 tasks appeared. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 42%. 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 Mathematicians?
- 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 12 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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