As of August 2026,
Log Graders and Scalers has an AI-exposure score of 57/100
(Elevated exposure) on the AI-Safe Careers index. This is an estimate of task
exposure, not a prediction of job loss.
Score inputs for this role:
This role starts from O*NET 29.1 occupational descriptors and is empirically grounded by Penn/OpenAI GPTs are GPTs study, Felten, Raj and Seamans AIOE index. BLS labor-market figures are separate context, not score inputs.
Log Graders and Scalers
More exposed than 53% of the roles we track. Median pay ~US$46,330. About 600 projected openings a year (BLS 2024–34 - growth plus replacement).
Pay & demand figures are US medians (BLS, in USD) - your local figures will differ. Your exposure score applies broadly.
Will AI replace Log Graders and Scalers?
No exposure score can predict whether AI will replace this role. The 57/100 score means our current model estimates elevated task exposure from the sources listed on this page. It does not predict an employer decision, headcount, or an individual outcome. The task map below shows the work assessed and where human judgment remains important.
Early-career context (study ages 22-25)
This role's task mix is automation-heavy, but it sits in the Elevated exposure band rather than our highest-exposure bands. That is only a partial match to the study's cohort, so the headline figure is context rather than a direct forecast for this role.
The November 2025 revision reports a 16% relative employment decline for workers ages 22-25 in the most AI-exposed U.S. occupations, after firm-level controls, relative to workers in less-exposed fields and more experienced workers in the same occupations.
Use the task map to identify durable work and the skills worth building early.
Stanford Digital Economy Lab, Canaries in the Coal Mine - November 2025 revision
This is group-level U.S. payroll evidence, not a personal forecast. The authors do not claim that AI alone caused the change, and this context does not alter the exposure score.
How this role compares to similar Farming & Forestry roles
What this role usually involves
Grade logs or estimate the marketable content or value of logs or pulpwood in sorting yards, millpond, log deck, or similar locations. Inspect logs for defects or measure logs to determine volume.
Broad guidance for this preparation level; exact requirements vary by role and employer.
Source: O*NET 29.1 exact occupation - Log Graders and Scalers, SOC 45-4023.00. Context describes the role; the AI-exposure score remains a separate task-exposure estimate.
Log Graders and Scalers tasks, by AI exposure
- Weigh log trucks before and after unloading, and record load weights and supplier identities.
- Measure felled logs or loads of pulpwood to calculate volume, weight, dimensions, and marketable value, using measuring devices and conversion tables.
- Communicate with coworkers by signals to direct log movement.
- Saw felled trees into lengths.
- Jab logs with metal ends of scale sticks, and inspect logs to ascertain characteristics or defects such as water damage, splits, knots, broken ends, rotten areas, twists, and curves.
No durable tasks identified for this role - its individually-assessed tasks split 75% automatable / 25% augmentable.
We analyzed all 12 Log Graders and Scalers tasks - 9 automatable and 3 augmentable. The full task map - every task with exactly what to do about each - is in your Career Report.
Your report unlocks three concrete artifacts
Every task scored with what to automate, augment, or protect.
Related roles with exposure deltas, salary, demand, and reachability. Lower-exposure options appear only when the data supports them.
A keepable roadmap plus resume and LinkedIn repositioning.
Grounded in O*NET-linked or curated role data, with Penn, Anthropic Economic Index, and AIOE signals where matched. BLS labor-market context is separate - not generic advice.
Adjacent career paths
Relatedness shows how reachable a move may be. A path is labeled lower exposure only when its score is at least 6 points lower; every row shows the measured difference.
Weigh log trucks before and after unloading, and record load weights and supplier identities.
Your AI-Safe Career Report
Every task scored with what to do about it; adjacent paths with honest exposure deltas, salary, demand, and reachability; a skill-gap map; a 30/60/90-day roadmap; Agent Reality Check; plus a résumé and LinkedIn rewrite and professional PDF.
Grounded in O*NET-linked or curated role data, with Penn, Anthropic Economic Index, and AIOE signals where matched. BLS labor-market context is separate.
Workers with AI skills earn a roughly 62% wage premium - adapting pays. - PwC Global AI Jobs Barometer, 2026
Generation starts after checkout; reports are typically ready within a few minutes.
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Log Graders and Scalers - median pay by US state (BLS OEWS, USD)
Median annual wage, in USD. US national: US$46,330. More states are being added.