AI Delegation Index

What work could you hand off to an AI agent?

Statisticians

Strong

AI agents could handle several recurring digital workflows in this job, while people remain responsible for judgment and final decisions.

Where agents can help most

  1. 1

    Build models and check reproducibility

    Use an agent to process data files, run your modeling scripts, generate charts and tables, and compare the results across a test subset and a fresh run.

  2. 2

    Analyze trends and test relationships

    Use an agent to summarize variable relationships, run your chosen tests, compare groups, and organize notes about patterns that may affect the results.

  3. 3

    Choose methods for a study

    Use an agent to compare possible statistical methods against the study question, sample size, missing data, and variable types, then draft a recommendation memo with the main pros and cons.

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O*NET-SOC 15-2041.00 · #5 of 923

Result context

How to read this result

Develop or apply mathematical or statistical theory and methods to collect, organize, interpret, and summarize numerical data to provide usable information. May specialize in fields such as biostatistics, agricultural statistics, business statistics, or economic statistics. Includes mathematical and survey statisticians.

National position
#5 of 923 occupations
Top 1% of occupations
Overall AI delegation potential
Strong
Potential of score-contributing workflows
Strong · 86/100
Meaningful work covered
83%

The overall rating combines how useful the best agent workflows are with how much of the occupation they address. It is not an estimate of job automation or replacement.

Recommended agent uses

3 workflows you could delegate to AI

1

Build models and check reproducibility

How you could use an agent

Use an agent to process data files, run your modeling scripts, generate charts and tables, and compare the results across a test subset and a fresh run. It helps you keep the analysis reproducible and quickly spot when a data change breaks the pipeline.

Where you stay involved

You choose the model approach, review the diagnostics, decide whether the results are sound, and handle any coding or release decisions yourself.

Review level: Medium

2

Analyze trends and test relationships

How you could use an agent

Use an agent to summarize variable relationships, run your chosen tests, compare groups, and organize notes about patterns that may affect the results. It helps you keep track of what was checked and which findings still need a deeper look.

Where you stay involved

You decide what the patterns mean, check whether the findings hold under additional tests, and choose whether anything is strong enough to share or act on.

Review level: High

3

Choose methods for a study

How you could use an agent

Use an agent to compare possible statistical methods against the study question, sample size, missing data, and variable types, then draft a recommendation memo with the main pros and cons. It helps you sort through method choices before you settle on the one to use.

Where you stay involved

You decide whether the method is suitable, adjust the plan if the study needs it, and make the final call on any tradeoff that affects the analysis design.

Review level: High

Supporting analysis

Why this occupation's AI delegation potential is Strong

Underlying methodology score

83 / 100

This technical score determines the qualitative rating; it is not an estimate of the share of the occupation that can be automated.

Importance & frequency80
AI capability89
Digital actionability93
End-to-end leverage88
Safety & reversibility81
Meaningful-work coverage
83%
Physical-work modifier
Limited
Safety modifier
Limited
Qualitative judgment
No material constraint
O*NET task evidence
19 tasks

O*NET 31.0 · methodology 3.3.0. Every workflow passes an action-level physical-execution and protected human-and-veterinary clinical-action gate. Documentation workflows must own a complete digital loop and use digital task evidence only; support-only workflows are disclosed separately and excluded from scoring. Artistic, editorial, normative, and policy-dependent work receives a transparent human-judgment constraint. National ranking within 923 scored O*NET occupations under methodology 3.3.0.

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