AI Delegation Index

AI Delegation Index

What work could you hand off to an AI agent?

Craft Artists

Limited

AI agents could help with a focused set of planning and documentation tasks, while hands-on work and judgment remain human-led.

Where agents can help most

  1. 1

    Research trends and draft new designs

    Use an agent to sort your trend research, customer notes, and venue ideas into a few design directions for the next craft piece or product line.

  2. 2

    Create custom craft piece from brief

    Use an agent to turn a customer brief into a clear build sheet for a custom craft piece.

  3. 3

    Test materials and flag fabrication issues

    Use an agent to compare candidate materials and keep a running note of how they behave during a trial build.

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O*NET-SOC 27-1012.00 · #563 of 923

Result context

How to read this result

Create or reproduce handmade objects for sale and exhibition using a variety of techniques, such as welding, weaving, pottery, and needlecraft.

National position
#563 of 923 occupations
Top 61% of occupations
Overall AI delegation potential
Limited
Potential of score-contributing workflows
Limited · 64/100
Meaningful work covered
37%

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

Research trends and draft new designs

How you could use an agent

Use an agent to sort your trend research, customer notes, and venue ideas into a few design directions for the next craft piece or product line. It can pull together pattern ideas, color themes, and rough sketches so you have a starting point for your own design judgment and marketing choices.

Where you stay involved

You decide which concept feels right for your work, adapt it to your materials and technique, and choose how to price or present it. You approve the final direction before anything is made or sold.

Review level: Low

2

Create custom craft piece from brief

How you could use an agent

Use an agent to turn a customer brief into a clear build sheet for a custom craft piece. Give it the customer’s preferences, the needed size or finish, and any material notes, and it can draft a spec sheet and reminder list before you start making the object by hand.

Where you stay involved

You talk with the customer, choose the materials, set the final dimensions and finishes, and make the piece yourself. You also check the finished work and decide whether any adjustment is needed before handoff.

Review level: High

3

Test materials and flag fabrication issues

How you could use an agent

Use an agent to compare candidate materials and keep a running note of how they behave during a trial build. Feed it your material list, desired dimensions, and any test photos or notes, and it can help you track fit, warping, breakage, or other problems before you commit to the full piece.

Where you stay involved

You decide whether the material performs well enough, whether to change the process, or whether to stop and start over. You also handle the cutting, shaping, joining, or molding work yourself.

Review level: High

Supporting analysis

Why this occupation's AI delegation potential is Limited

Underlying methodology score

56 / 100

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

Importance & frequency75
AI capability67
Digital actionability56
End-to-end leverage51
Safety & reversibility71
Meaningful-work coverage
37%
Physical-work modifier
Moderate
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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