Log Graders and Scalers
In short: today's best AI models could do about 6% of this job's working time (projected from METR's April 2026 measurement and Epoch's November 2026 index) if the work were set up for them, and about the same by the end of 2028 if progress keeps its long-run pace. The people and hands-on work, about 94% of the time, stays with people.
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.
3,070 people do this job in the US. $46,330 a year.
A typical 40-hour week
Not yet reviewed task by task- AI could take on2 h
- A person checks AI's work0 h
- Desk work AI can't do yet0 h
- Stays with people38 h
Log Graders and Scalers, now: of a 40-hour week, AI could take on 2 hours, 0 hours become checking its work, 0 hours are desk work it can't do yet, and 38 hours stay with people.
The largest pieces: Arrange for hauling of logs to appropriate mill sites (about 2 h).
Estimates for a typical week of this job, if progress keeps its long-run pace, counting work the best models finish four times in five. Every task is below.
of the working time. Now is projected from METR's April 2026 measurement and Epoch's November 2026 index.
- 6%
- 0%
- 94%
of the work: Anthropic's measure of what people already bring to Claude at work (2025). It counts help with part of a task, so it can be higher than the share within reach.
On the chosen pace and reliability. Estimate.
Share of the working time within reach, now to 2030
Change assumptionsHide assumptionsLong-run pace, four in five
What each choice means: , , , , . Every pace starts from .
At this date and pace, models finish tasks up to 2.4 work days long four times in five.
How far this has come
With GPT-4, measured in March 2023, 0% of this job's working time was within reach at . With Claude 3.7 Sonnet, measured in February 2025, 0%. With Claude Mythos Preview (early), measured in April 2026, 6%. Today's estimate: 6%.
A backcast: today's task data with the best model METR had measured by each date. It shows how fast the models have moved, not what anyone forecast at the time.
Measured use over time
None of this job's 12 tasks showed up in the Claude.ai conversations Anthropic sampled in any of its 7 releases, from February 2025 to May 2026.
Measured, not estimated: Anthropic's samples of Claude.ai conversations, each tied by a model to an O*NET task, from the Anthropic Economic Index. It says where Claude's use goes, not how much of this job's working time it covers, so it is not on the same scale as the reach above. The releases differ in their sample, their classifier and the smallest share they report (the June 2026 file rounds each task to a hundredth of a percent, so a smaller task reads as none), which is why a change of method starts a new line. At least 96% of each older release's task-tied use matched this site's tasks, and all of the newest. Claude.ai only, so use through other tools and other companies' models is not in it. Every job ranked.
Robots and the physical work
Anthropic rates 75% of this job's working time as physical work. For 75% of the working time, a robot has been shown doing most of the task somewhere: 55% in a purpose-built cell, 20% in a structured facility. 0.95 of 3, the 146th highest of the 923 jobs.
- Not physical 25%
- In a purpose-built cell 55%
- In a structured facility 20%
Anthropic's rating, not this site's estimate: Claude Opus 5, searching the web, rated each physical O*NET task by the kind of setting in which a robot it could cite (deployed, sold or demonstrated) does most of the task, weighted by its own estimate of each task's share of the time (What work can robots do?, September 30, 2026, data CC BY 4.0; every job ranked). A robot shown somewhere is not a robot in your building: cost, setup and safety decide that. The share within reach on this page still counts no body work. The robot behind each rated task is under the task below.
The tasks
Sorted by . 12 tasks from .
| Task | Kind | |||
|---|---|---|---|---|
| Evaluate log characteristics and determine grades, using established criteria.Done hourly or more by most who do it. Robots: in a purpose-built cell, MiCROTEC CT Log / Logeye scanners with AI grading (SCA Bollstabruk log sorting line) (deployed). Anthropic's rating. | 19% | 17 min8 min to 38 min | Stays with people | |
| Measure felled logs or loads of pulpwood to calculate volume, weight, dimensions, and marketable value, using measuring devices and conversion tables.Done hourly or more by most who do it. Robots: in a structured facility, Woodtech Logmeter (Logmeter 4000) (deployed). Anthropic's rating. | 14% | 17 min8 min to 38 min | Stays with people | |
| 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.Done hourly or more by most who do it. Robots: in a purpose-built cell, MiCROTEC CT Log (with Logeye 900 Stereo) at Cascade Hardwoods, Chehalis, WA (deployed). Anthropic's rating. | 13% | 15 min8 min to 33 min | Stays with people | |
| Record data about individual trees or load volumes into tally books or hand-held collection terminals.Done hourly or more by most who do it. | 11% | 13 min4 min to 25 min | Stays with people | |
| Identify logs of substandard or special grade so that they can be returned to shippers, regraded, recut, or transferred for other processing.Done hourly or more by most who do it. Robots: in a purpose-built cell, MiCROTEC CT Log (sold). Anthropic's rating. | 10% | 13 min7 min to 25 min | Stays with people | |
| Paint identification marks of specified colors on logs to identify grades or species, using spray cans, or call out grades to log markers.Done hourly or more by most who do it. Robots: in a purpose-built cell, ABB PixelPaint robotic painting system (deployed). Anthropic's rating. | 7% | 10 min4 min to 25 min | Stays with people | |
| Measure log lengths and mark boles for bucking into logs, according to specifications.Done daily by most who do it.Robots: in a purpose-built cell, Comact Log Merchandiser Optimizer (sold). Anthropic's rating. | 6% | 21 min8 min to 50 min | Stays with people | |
| Arrange for hauling of logs to appropriate mill sites.Done more than weekly by most who do it. | 6% | 25 min13 min to 50 min | 100%Half by now | |
| Drive to sawmills, wharfs, or skids to inspect logs or pulpwood.Done daily by most who do it.Robots: in a purpose-built cell, Logeye 301 / 600 log scanner (MiCROTEC) (sold). Anthropic's rating. | 6% | 50 min25 min to 1.7 h | Stays with people | |
| Saw felled trees into lengths.Done more than weekly by most who do it.Robots: in a purpose-built cell, USNR LogPro merchandiser / Comact Optimized Log Merchandiser (USNR; Comact; FiberPro) (sold). Anthropic's rating. | 4% | 25 min13 min to 1.3 h | Stays with people | |
| Weigh log trucks before and after unloading, and record load weights and supplier identities.Done hourly or more by most who do it. | 3% | 10 min4 min to 17 min | Stays with people | |
| Communicate with coworkers by signals to direct log movement.Done hourly or more by most who do it. | 2% | 4 min2 min to 13 min | Stays with people |
Within reach, per task: the share of the task's time whose instances are short enough for a model to finish at the chosen date, pace and reliability. Half by: the date half of that time comes within reach.
Jobs that share skills with this one
From O*NET's related occupations. Within reach now and by the end of 2028, long-run pace, four in five.
- Weighers, Measurers, Checkers, and Samplers, Recordkeeping30% now, 30% by 2028
- Inspectors, Testers, Sorters, Samplers, and Weighers27% now, 27% by 2028
- Graders and Sorters, Agricultural Products7% now, 7% by 2028
- Logging Equipment Operators2% now, 2% by 2028
- Laborers and Freight, Stock, and Material Movers, Hand9% now, 9% by 2028
- Milling and Planing Machine Setters, Operators, and Tenders, Metal and Plastic18% now, 18% by 2028
Where this job works
The industry groups that employ the most of it (BLS, May 2025).
Where the most of these jobs are
The metro areas with the most people in it (BLS, May 2025).
Questions about this job
- How much of the work of Log Graders and Scalers is within reach of AI now?
- An estimated 6% of the working time is within reach of AI models now and 6% by the end of 2028, on METR's long-run pace at four in five. Within reach means a model could finish work that long at that reliability. It is not a forecast of jobs lost or of savings.
- Which tasks of Log Graders and Scalers come within reach first?
- Weighted by the time each takes, the tasks with the most within reach now (projected from METR's April 2026 measurement and Epoch's November 2026 index) are: Arrange for hauling of logs to appropriate mill sites (100% of the task's time now).
- Which tasks of Log Graders and Scalers stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Evaluate log characteristics and determine grades, using established criteria; Measure felled logs or loads of pulpwood to calculate volume, weight, dimensions, and marketable value, using measuring devices and conversion tables; and 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. Together such tasks are about 94% of the working time.
- Do people already use AI for the work of Log Graders and Scalers?
- In the Claude.ai conversations Anthropic sampled for May 2026, no reportable share went to this job's tasks. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 0%. These are measures of use, not of how much of the work AI could finish, and they cover Claude only.
- Can robots do the physical work of Log Graders and Scalers?
- Anthropic's robot exposure rating (September 2026) finds 75% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 75% of the working time, 20% in a structured facility. Its index is 0.95 of 3. One example: Woodtech Logmeter (Logmeter 4000) for "measure felled logs or loads of pulpwood to calculate volume, weight, dimensions, and marketable value, using measuring devices and conversion tables". A robot shown somewhere is not one in every workplace; this site's own estimates still count no physical work as within reach.
- How is this estimated?
- From the 12 tasks O*NET lists for the occupation, each with an estimated length checked against GDPval and a share of the working time, each classed as desk, people or body work, and METR's measurements of how long a task the best AI models can finish, carried forward to the date from the latest, Claude Mythos Preview (early) in April 2026. Data checked November 10, 2026.
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