Impact of Decisions on Co-workers or Company Results
Work context · O*NET
Impact of Decisions on Co-workers or Company Results is a work-context dimension in the O*NET database — one of the standardized conditions O*NET uses to describe the environment a job is done in , grouped under Structural Job Characteristics. O*NET defines it by asking workers: "What results do your decisions usually have on other people or the image or reputation or financial resources of your employer?." It is rated for 894 occupations, which average 3.78 out of 5 (high relative to other context dimensions).
How it's measured
O*NET rates each occupation on this dimension on a 1–5 context-importance scale (the CX scale), where higher means the condition is a more frequent or more central part of the work. The figures on this page are those occupation-level ratings — a description of working conditions as workers report them, not a judgment about pay, difficulty, or whether a job is "good."
| Economy-wide average | 3.78 / 5 | Mean across all 894 rated occupations |
| Range across occupations | 1.96–4.99 | Lowest to highest occupation rating (spread 3.03) |
| Intensity vs. other dimensions | 79th pct | Where this dimension's average ranks among all O*NET work-context dimensions |
Occupations where it's highest
The occupations that rate this condition strongest on the 1–5 scale.
Occupations where it's lowest
The occupations that rate this condition weakest — where it is rarely part of the work.
How AI is used by roles where impact of decisions on co-workers or company results is central
A working condition is not itself "being automated" — but we can look at the occupations where it is most central and ask how those people actually use AI. This rolls the Anthropic Economic Index per-role signal up across the roles that rate this condition 3 or higher (CX-rating-weighted). 57.5% of the 832 occupations where this condition is present carry observed AI-usage data (478 roles).
Across those roles, 45.7% of AI conversations are people working with AI and 31.1% hand a task to AI , with an average autonomy of 3.56 / 5.
| Collaboration pattern | Share | What it means |
|---|---|---|
| directive | 28.8% | AI does it; you give the instruction |
| task iteration | 23.3% | you and AI go back and forth |
| learning | 19.8% | you ask AI to explain or teach |
| validation | 2.6% | you do it; AI checks your work |
| feedback loop | 2.3% | AI does it, then adjusts from your feedback |
Roles behind this signal
The occupations where this condition is most central and that also have the most AEI data. "Works with AI" is the role's share of conversations that augment rather than automate.
| Occupation | Condition (1–5) | Works with AI | Autonomy |
|---|---|---|---|
| Biological Science Teachers, Postsecondary | 3.8 | 63.2% | 4.0/5 |
| English Language and Literature Teachers, Postsecondary | 3.2 | 63.2% | 4.0/5 |
| Editors | 4.2 | 68.2% | 4.0/5 |
| Educational, Guidance, School, and Vocational Counselors | 4.2 | 70.6% | 4.0/5 |
| Recreation and Fitness Studies Teachers, Postsecondary | 4.1 | 66.2% | 3.3/5 |
| Office Clerks, General | 3.8 | 36.5% | 3.0/5 |
| Foreign Language and Literature Teachers, Postsecondary | 3.0 | 65.2% | 3.0/5 |
| Criminal Justice and Law Enforcement Teachers, Postsecondary | 4.1 | 65.7% | 3.3/5 |
| Philosophy and Religion Teachers, Postsecondary | 3.8 | 66.8% | 3.3/5 |
| Education Teachers, Postsecondary | 4.0 | 65.3% | 3.5/5 |
| Technical Writers | 3.4 | 54.2% | 4.0/5 |
| Health Specialties Teachers, Postsecondary | 4.0 | 66.2% | 3.5/5 |
Source: Anthropic Economic Index (2026-01-15-v4-plus-2025-03-27-v2) over a sample of Claude.ai Free and Pro conversations — not all AI tools and not the whole workforce. This is a role-weighted projection from AEI-linked occupations where this condition is central, not a direct measurement of AI use for the condition itself. Shares are weighted by how central the condition is to each role; some conversations are left unclassified by Anthropic's taxonomy, so shares need not sum to 100.
Sources for this page
Every figure above traces to a named public dataset and the exact release below — not hand-written opinion. See the full methodology for what each measure does and does not mean.
- O*NET 30.3 U.S. Department of Labor / National Center for O*NET Development
- Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27) Anthropic
Data compiled June 2, 2026. Figures are estimates, not advice.
Cite this page
Singulariki. "Impact of Decisions on Co-workers or Company Results." Singulariki: a source-backed encyclopedia of work. Built from O*NET 30.3; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27). Accessed June 7, 2026. https://singulariki.com/work-context/impact-of-decisions-on-co-workers-or-company-results
Singulariki. (2026). Impact of Decisions on Co-workers or Company Results. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/work-context/impact-of-decisions-on-co-workers-or-company-results
@misc{singulariki-impact-of-decisions-on-co-workers-or-company-results,
title = {Impact of Decisions on Co-workers or Company Results},
author = {{Singulariki}},
year = {2026},
note = {O*NET 30.3; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27). Accessed June 7, 2026},
url = {https://singulariki.com/work-context/impact-of-decisions-on-co-workers-or-company-results}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.