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Technology & Data · Updated Aug 2026

Mathematicians

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.

JVS 2.0.0-phase4b
AI Exposure
74/100
High

How much of this occupation’s work can be materially affected by current AI systems.

Replacement Risk
71/100
High

How likely exposure is to translate into reduced human demand.

Includes provisional estimates for AI adoption pressure and labour-market resilience. How this is measured

Evidence quality
Confidence83/100
Task coverage86%

Confidence reflects task coverage, mapping and capability-evidence quality, and how much of the score rests on provisional inputs.

Task-level evidence

What is driving the score?

Occupation scores are built from the task mix—not a single prediction about a job title.

JVS 2.0.0-phase4b
TaskImportanceAI impactExposure
Address the relationships of quantities, magnitudes, and forms through the use of numbers and symbols.Medium
82
Perform computations and apply methods of numerical analysis to data.Medium
82
Maintain knowledge in the field by reading professional journals, talking with other mathematicians, and attending professional conferences.High
82
Conduct research to extend mathematical knowledge in traditional areas, such as algebra, geometry, probability, and logic.Medium
80
Develop new principles and new relationships between existing mathematical principles to advance mathematical science.High
80
Develop mathematical or statistical models of phenomena to be used for analysis or for computational simulation.Medium
80
Apply mathematical theories and techniques to the solution of practical problems in business, engineering, the sciences, or other fields.Medium
82
Disseminate research by writing reports, publishing papers, or presenting at professional conferences.High
80
Develop computational methods for solving problems that occur in areas of science and engineering or that come from applications in business or industry.Medium
81
Assemble sets of assumptions, and explore the consequences of each set.High
21
Most exposed

Where AI can do more

Routine, digitized, and highly repeatable tasks face the greatest pressure.

  1. Address the relationships of quantities, magnitudes, and forms through the use of numbers and symbols.82
  2. Perform computations and apply methods of numerical analysis to data.82
  3. Maintain knowledge in the field by reading professional journals, talking with other mathematicians, and attending professional conferences.82
  4. Apply mathematical theories and techniques to the solution of practical problems in business, engineering, the sciences, or other fields.82
Hardest to automate

Where people still matter

These tasks score lowest on automation feasibility—physical presence, judgement, accountability and real-world variability all resist end-to-end automation.

  1. Assemble sets of assumptions, and explore the consequences of each set.01
  2. Conduct research to extend mathematical knowledge in traditional areas, such as algebra, geometry, probability, and logic.02
  3. Develop new principles and new relationships between existing mathematical principles to advance mathematical science.03
  4. Develop mathematical or statistical models of phenomena to be used for analysis or for computational simulation.04
  5. Disseminate research by writing reports, publishing papers, or presenting at professional conferences.05
Where else this work leads

Related occupations

Occupations O*NET links to this one. Relatedness reflects shared work, not a claim that these roles are safer.

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Beyond AI capability

Adoption and labour-market outlook

Structural factors are kept separate from raw capability so you can see what actually resists automation. Adoption pressure and labour-market resilience are still provisional models—25% of this occupation’s replacement-risk weight rests on them.

Human dependency49
Physical dependency16
Adoption pressure53
Labour-market resilience46
Methodology & sources

O*NET 30.3 occupational data interpreted through the JobsVsAI capability, automation and structural-constraint models.

Confidence83/100
CalculatedAug 21, 2026
Read methodology →