AI Delegation Index

AI Delegation Index

What work could you hand off to an AI agent?

Software Developers

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

    Fix code and verify changes

    Use an agent to take a bug report or change request, pull the relevant code, make the requested fix, and run the tests and basic performance checks you point it to.

  2. 2

    Check requirements for implementation

    Use an agent to gather the user notes, project constraints, and related emails or specs, then turn them into a short requirements brief and an implementation outline.

  3. 3

    Write tests and track defects

    Use an agent to draft test cases, run the scripted checks or manual test steps you provide, and collect logs, screenshots, or failure notes into one place.

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O*NET-SOC 15-1252.00 · #26 of 923

Result context

How to read this result

Research, design, and develop computer and network software or specialized utility programs. Analyze user needs and develop software solutions, applying principles and techniques of computer science, engineering, and mathematical analysis. Update software or enhance existing software capabilities. May work with computer hardware engineers to integrate hardware and software systems, and develop specifications and performance requirements. May maintain databases within an application area, working individually or coordinating database development as part of a team.

National position
#26 of 923 occupations
Top 3% of occupations
Overall AI delegation potential
Strong
Potential of score-contributing workflows
Strong · 84/100
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

Fix code and verify changes

How you could use an agent

Use an agent to take a bug report or change request, pull the relevant code, make the requested fix, and run the tests and basic performance checks you point it to. It can package the changed files, test results, and notes so you can review whether the issue is really fixed before merge.

Where you stay involved

You decide whether the change is good enough to merge, whether it creates risk in sensitive code, and whether more work is needed. You also handle the release call when the problem is unclear or the fix is bigger than the request.

Review level: Medium

2

Check requirements for implementation

How you could use an agent

Use an agent to gather the user notes, project constraints, and related emails or specs, then turn them into a short requirements brief and an implementation outline. It can compare options against time, cost, and technical limits so you have a clear starting point for design discussions.

Where you stay involved

You decide whether the request is workable, what tradeoffs matter most, and what the team should build next. You also confirm the brief reflects the real needs before it is shared.

Review level: High

3

Write tests and track defects

How you could use an agent

Use an agent to draft test cases, run the scripted checks or manual test steps you provide, and collect logs, screenshots, or failure notes into one place. It can compare the new run to the last good build and prepare a defect list for your review.

Where you stay involved

You judge which failures matter, confirm whether a fix actually works, and decide what should block a release. You also decide if a bug needs deeper investigation or a different test approach.

Review level: Medium

Supporting analysis

Why this occupation's AI delegation potential is Strong

Underlying methodology score

80 / 100

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

Importance & frequency71
AI capability91
Digital actionability95
End-to-end leverage91
Safety & reversibility73
Meaningful-work coverage
76%
Physical-work modifier
Limited
Safety modifier
Limited
Qualitative judgment
No material constraint
O*NET task evidence
17 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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