AI Delegation Index

AI Delegation Index

What work could you hand off to an AI agent?

Data Scientists

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

    Clean data and check quality

    Use an agent to take a new dataset, the column names, and a short note about what the data should represent, then have it profile missing values, duplicates, outliers, and inconsistent formats in a spreadsheet or statistical notebook.

  2. 2

    Build analysis tools and test them

    Use an agent to take your analysis notes, sample data, and a description of the repeatable calculation you want, then have it draft or update a function in your programming language and run it against test files.

  3. 3

    Turn business questions into analysis plans

    Use an agent to take a business question, a few example tables, and any past notes on the metric you care about, then have it outline an analysis plan and run a first pass at comparing variables, trends, or groups.

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O*NET-SOC 15-2051.00 · #7 of 923

Result context

How to read this result

Develop and implement a set of techniques or analytics applications to transform raw data into meaningful information using data-oriented programming languages and visualization software. Apply data mining, data modeling, natural language processing, and machine learning to extract and analyze information from large structured and unstructured datasets. Visualize, interpret, and report data findings. May create dynamic data reports.

National position
#7 of 923 occupations
Top 1% of occupations
Overall AI delegation potential
Strong
Potential of score-contributing workflows
Strong · 86/100
Meaningful work covered
76%

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

Clean data and check quality

How you could use an agent

Use an agent to take a new dataset, the column names, and a short note about what the data should represent, then have it profile missing values, duplicates, outliers, and inconsistent formats in a spreadsheet or statistical notebook. It can draft cleaning steps and a short issue list so you can finish the hard judgment calls before analysis starts.

Where you stay involved

You decide which fields should be kept, how to treat odd records, and whether a mismatch is a real data problem or just an expected value. You also approve the final cleaned dataset before anyone models it.

Review level: Medium

2

Build analysis tools and test them

How you could use an agent

Use an agent to take your analysis notes, sample data, and a description of the repeatable calculation you want, then have it draft or update a function in your programming language and run it against test files. It can compare outputs to known examples and flag failures so you can decide whether the tool is ready to reuse.

Where you stay involved

You review the code, decide whether the results make sense, and fix or approve anything that looks off. You also decide when the tool is dependable enough for wider use.

Review level: Medium

3

Turn business questions into analysis plans

How you could use an agent

Use an agent to take a business question, a few example tables, and any past notes on the metric you care about, then have it outline an analysis plan and run a first pass at comparing variables, trends, or groups. It can summarize likely drivers and draft a plain-language recommendation for you to review.

Where you stay involved

You choose the question to answer, decide whether the evidence is strong enough, and make the final recommendation. You also decide when the findings are too mixed to support a staffing, budgeting, or policy change.

Review level: High

Documentation and coordination support

AI can assist without owning the physical outcome

These support steps are shown separately. They do not count as agentic workflows and do not increase this occupation's score.

Create charts and summary reports

Use an agent to take cleaned output tables, chart preferences, and any notes about the audience, then have it build draft graphs and a short summary report in your slide deck or document. It can check labels, titles, and numbers against the source tables so you can focus on the message and final wording.

Supporting analysis

Why this occupation's AI delegation potential is Strong

Underlying methodology score

82 / 100

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

Importance & frequency77
AI capability87
Digital actionability94
End-to-end leverage89
Safety & reversibility84
Meaningful-work coverage
76%
Physical-work modifier
Limited
Safety modifier
Limited
Qualitative judgment
No material constraint
O*NET task evidence
16 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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