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Balam Labs
ISCO-08 7535

Pelt dressers, tanners and fellmongers

0.0%
ADI · 418th of 433 · 95% interval 0.0–0.0

An AI agent can at least partly carry out 0.0% of the task time of pelt dressers, tanners and fellmongers, and finish 0.0% alone. The barrier that holds most of the rest back is access to the systems the work runs on.

ADI · partial or full0.0%

418th of 433 · interval 0.0–0.0

ADI3 · full delegation0.0%

201st of 433 · interval 0.0–0.0

ADIs · share of time11.6%

392nd of 433 · interval 5.5–21.4

Evidence5

task statements rated by two models and weighted by importance and frequency. World employment: 0.2 million.

Task weight by level

How the tasks rate

83%
17%
L0No meaningful role · 82.6%L1Augmentation · 17.4%L2Partial delegation · 0.0%L3Full delegation · 0.0%
Barriers

What stops the agent

Physical presence100%
Accountability9%
Trust and care0%
Access to systems69%

Share of task weight flagged by each barrier; a task can carry several.

5 task statements, heaviest first
Task statement (O*NET occupation)WeightLevelSonnet · HaikuShareHuman timeBarriers
Place products in containers according to grade and mark grades on containers.Graders and Sorters, Agricultural Products20.9%L0L0L19%15 minPhysical presence, Access to systems
Grade and sort products according to factors such as color, species, length, width, appearance, feel, smell, and quality to ensure correct processing and usage.Graders and Sorters, Agricultural Products20.8%L0L0L110%4.3 hPhysical presence, Access to systems
Weigh products or estimate their weight, visually or by feel.Graders and Sorters, Agricultural Products20.5%L0L0L04%2 minPhysical presence, Access to systems
Discard inferior or defective products or foreign matter, and place acceptable products in containers for further processing.Graders and Sorters, Agricultural Products20.4%L0L0L16%12 minPhysical presence, Access to systems
Record grade or identification numbers on tags or on shipping, receiving, or sales sheets.Graders and Sorters, Agricultural Products · supplemental task17.4%L1L1L232%4 minPhysical presence, Accountability, Access to systems

Level: consensus of the two models (the lower level when they disagree). Share: part of the task’s working time an agent could take over. Human time: minutes a competent person needs for one instance, as estimated by the models.

Against other measures

Exposure is not delegation

MeasureValuePercentile
ADI (this index)0.0%4
Eloundou et al. (2024), GPT exposure β0.17430
Felten et al. (2021), AI occupational exposure-1.06218
Webb (2020), AI patent exposure82.576
Eisfeldt et al. (2026), generative AI exposure0.13444
Anthropic Economic Index, observed use016

Earlier indices measure whether AI can touch a task; ADI measures how much of it an agent can carry out from a goal. – : the source does not cover this occupation.

Same sub-major group (75)

Neighbouring occupations

Dashed line: pelt dressers, tanners and fellmongers (0.0%).

Cite this record
Text

Espinal Maya, Cristian, and Santiago Jiménez Londoño. 2026. ADI v2026.1: Agent Delegability Index data, code and MCP server. Zenodo. https://doi.org/10.5281/zenodo.23552918. Record: Pelt dressers, tanners and fellmongers (ISCO-08 7535), https://balamlabs.org/adi/occupations/7535

BibTeX
@misc{espinal2026adidata,
  title     = {{ADI} v2026.1: Agent Delegability Index data, code and {MCP} server},
  author    = {Espinal Maya, Cristian and Jim{\'e}nez Londo{\~n}o, Santiago},
  year      = {2026},
  publisher = {Zenodo},
  version   = {v2026.1},
  doi       = {10.5281/zenodo.23552918},
  url       = {https://doi.org/10.5281/zenodo.23552918},
  note      = {Record: Pelt dressers, tanners and fellmongers (ISCO-08 7535)}
}
Machine-readable

The same record as static JSON, with its citation: /adi/v2026.1/isco/7535.json.