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AI Automation Index
Will AI Replace Mathematicians?
Task-level automation exposure for Mathematicians: 12 O*NET tasks scored against their work activities, plus the simulator.
E-E-A-T Verified
Developed & audited by Gini Loh Automation Exposure
72%
weighted task index
12 of 12 tasks scored
Median Salary
$126,710 / year
BLS OEWS, May 2025 — this exact occupation
Employment Level
Low
2,030 people hold this job — size, not growth
Projected 2025–35
+0.6%
employment change
100 openings a year · BLS line item
Pay by state
BLS OEWS publishes 12 state estimates for this occupation. Each is its own survey estimate, not the national median adjusted for local prices.
$65,510 – $162,280
Highest medians
Washington $162,280
Virginia $148,030
Maryland $131,810
Illinois $130,970
New York $126,950
Lowest medians
Michigan $65,510
Colorado $86,020
Indiana $88,050
Nevada $102,890
Massachusetts $104,190
State figures come from the 15-2021 row in the May 2025 state panel. States where the estimate was suppressed or too small to publish are absent.
What the score is made of
Each task is mapped to its work activities, scored for AI automation potential, and weighted by how important those activities are to the job. These are the components.
Automation potential 72%
Importance-weighted mean of the scored tasks. This is the headline index.
Physical work 0%
Share of weighted tasks in hands-on or machine-operating work activities.
Judgment & influence 92%
Share in analysis, decisions, teaching, directing, advising, or caring for others.
Routine administration 8%
Share in documenting, recording, and administrative activities.
Rewritten by O*NET 0%
Share of weighted tasks O*NET rewrote in a recent update. Reported, not folded into the score.
Consequence of error 5/100
Low
O*NET's own rating of how serious an uncorrectable mistake would be here — respondents, not us. Deliberately not in the index: the score measures what AI can do with the task content, and multiplying it by stakes would be our judgment dressed as data.
Constituent Task Mix
12 tasks for this occupation, weighted by work-activity importance. Shares below are of total task weight, not task count.
High exposure (≥ 60% of the task is automatable) 82%
10 tasks
Medium exposure (≥ 35%) 18%
2 tasks
Low exposure (below 35%) 0%
0 tasks
How would you survive?
Move your week away from the high-exposure tasks and toward the ones that need judgment. The simulator recalculates the index as you shift the mix.
Simulate Upskilling →Constituent Tasks
#24002 · Core · 55% automatable
Mentor others on mathematical techniques.
decision support — Technical guidance needs context-specific human judgment
Collaborate on research activities with scientists or technical specialists. Provide technical guidance to other personnel.
#7369 · Core · 80% automatable
Maintain knowledge in the field by reading professional journals, talking with other mathematicians, and attending professional conferences.
information retrieval — AI scans trend sources; human weighs relevance
Update knowledge about emerging industry or technology trends.
#7374 · Core · 50% automatable
Develop new principles and new relationships between existing mathematical principles to advance mathematical science.
data analysis — Model formulation aided; validation human-owned
Develop scientific or mathematical models.
#20191 · Core · 65% automatable
Disseminate research by writing reports, publishing papers, or presenting at professional conferences.
data analysis — Analytical reports drafted; human validates analysis
Present research results to others. Prepare analytical reports.
#7372 · Core · 82% automatable
Assemble sets of assumptions, and explore the consequences of each set.
data analysis — Trend and relationship detection in data
Analyze data to identify trends or relationships among variables.
#7370 · Core · 82% automatable
Perform computations and apply methods of numerical analysis to data.
data analysis — Trend and relationship detection in data
Analyze data to identify trends or relationships among variables.
#7373 · Core · 82% automatable
Address the relationships of quantities, magnitudes, and forms through the use of numbers and symbols.
data analysis — Trend and relationship detection in data
Analyze data to identify trends or relationships among variables.
#7376 · Core · 80% automatable
Conduct research to extend mathematical knowledge in traditional areas, such as algebra, geometry, probability, and logic.
information retrieval — AI can search and summarize literature, human curates
Review professional literature to maintain professional knowledge. Update professional knowledge.
#7371 · Core · 60% automatable
Develop mathematical or statistical models of phenomena to be used for analysis or for computational simulation.
text generation — Modeling code drafted; validation and domain framing human
Design computer modeling or simulation programs.
#7367 · Core · 80% automatable
Apply mathematical theories and techniques to the solution of practical problems in business, engineering, the sciences, or other fields.
data analysis — Applies math/statistics to problems; human validates
Apply mathematical principles or statistical approaches to solve problems in scientific or applied fields.
#7368 · Core · 72% automatable
Develop computational methods for solving problems that occur in areas of science and engineering or that come from applications in business or industry.
data analysis — Recommends analysis methods; human selects
Determine appropriate methods for data analysis.
#7375 · Supplemental · 70% automatable
Design, analyze, and decipher encryption systems designed to transmit military, political, financial, or law-enforcement-related information in code.
data analysis — Security analysis aided; human validates findings
Analyze security of systems, network, or data. Develop computer or information security policies or procedures.
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How this was scored
- 1. Tasks. O*NET task statements for this occupation, from a release whose newest record is dated 08/2026.
- 2. Work activities. Each task maps to 1–5 Detailed Work Activities; each activity belongs to one of 41 Generalized Work Activities that O*NET rates for importance (1–5) in this occupation.
- 3. Automation potential. Every work activity carries one score for how far current AI can perform it end-to-end. Tasks inherit the mean of their activities.
- 4. Weighting. Task weight = 0.35 + 0.65 × (importance − 1)/4, scaled by how often the task is performed and by 0.7 for Supplemental tasks. Importance is the task's own O*NET rating where it exists (18,369 of 18,838 tasks); the rest inherit their work activities' importance. The index is the weighted mean.
Check: across the 910 occupations where O*NET also rates how far machine speed sets the pace, this index moves opposite to it (Spearman ρ = -0.49). The more a job is paced by equipment, the less of its task content AI can address — the relationship you would expect if the scoring is working.
Sources · O*NET 31.0 (task records to 08/2026) · BLS OEWS May 2025 · BLS projections 2025-2035 · rubric v2.1 · tasks for O*NET, not a forecast
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