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STRATUSWORKFORCE SCAN

Industry group, 3345

Navigational, Measuring, Electromedical, and Control Instruments Manufacturing

412,110 people work in this industry in the US, at mean pay of $102,650 a year (BLS, May 2025). What follows is how much of their working time the best AI models could finish, when, and in which jobs and tasks. Estimates.

now
36%

of the paid hours. Now is projected from METR's April 2026 measurement and Epoch's November 2026 index.

$23B

a year: 305 million hours at what they cost. Not a forecast of savings.

Kinds of work
  • 54%
  • 18%
  • 28%
9%

of the paid hours are within reach now in tasks people already bring to Claude. Another 27% is within reach in tasks not yet seen there.

Across the US: 30% within reach now and 36% by the end of 2028, on the long-run pace at four in five. Now is projected from METR's April 2026 measurement and Epoch's November 2026 index.

Share of the paid hours within reach, now to 2030

0%25%50%75%100%2027202820292030NowDesk work: 54% of the time
Chosen to Ceiling: the share
DateNow
NowEnd of 2030
Change assumptionsLong-run pace, four in five

What each choice means: , , , , . Every pace starts from .

What handing the work over would take

For the 381,547 people in jobs so far, 93% of the industry's people; the others are in the totals above and join this split as the review reaches their jobs. Shares of their working time within reach now, at the pace and reliability chosen above. Estimates. Now is projected from METR's April 2026 measurement and Epoch's November 2026 index.

29%

about 228 million hours a year. The material can be handed to a model and the result handed back.

7%

about 58 million hours a year. The model has to be connected to the system the work lives in.

, not counted
10%

about 79 million hours a year. Short enough by length. This site leaves conversation with people, so it is not in the totals.

What their work is made of

  • 45%
  • 8%
  • 12%
  • 7%
  • 28%

Each task's time split among five kinds of doing, judged one task at a time; only documents and systems can count as within reach.

What changes for the people

For the 381,547 people in jobs reviewed task by task so far, by the end of 2028 on the long-run pace at four in five: the shares of their working time, from each job page's own map, weighted by how many people here do that job. It says which parts of the work change, never whether anyone keeps a job. Estimates.

Stays with people
46%

Conversation, in-person and hands-on work.

Becomes checking
47%

Desk work within reach in tasks where a mistake costs something or a licensed person signs.

Handed over
5%

Desk work within reach that is small if wrong, with lighter checks.

What most people here would learn first

How many of them have each skill among the first two things to learn on their job's page. Every state, and the US

  • Reviewing work you did not do yourself262,140 (69%)
  • Briefing a model and checking its drafts209,240 (55%)
  • The hands-on craft133,607 (35%)
  • The conversations64,997 (17%)
  • Judgment where errors are severe50,580 (13%)
  • Running AI inside the business systems20,560 (5%)
  • Dealing with people outside the organization12,000 (3%)
  • Signing off under your license2,790 (1%)
  • Handling protected records210 (under 1%)

How far this has come

With GPT-4, measured in March 2023, 0% of this industry's paid hours were within reach at . With Claude 3.7 Sonnet, measured in February 2025, 1%. With Claude Mythos Preview (early), measured in April 2026, 14%. Today's estimate: 36%.

0%10%20%30%40%50%2023202420252026GPT-4, March 2023: 0% within reachGPT-4 Turbo (Nov 2023), November 2023: 0% within reachGPT-4o, May 2024: 0% within reachClaude 3.5 Sonnet (June 2024), June 2024: 0% within reacho1-preview, September 2024: 0% within reachClaude 3.5 Sonnet (Oct 2024), October 2024: 0% within reacho1, December 2024: 0% within reachClaude 3.7 Sonnet, February 2025: 1% within reacho3, April 2025: 3% within reachGPT-5, August 2025: 4% within reachGemini 3 Pro, November 2025: 6% within reachClaude Opus 4.5, November 2025: 6% within reachGPT-5.2, December 2025: 7% within reachClaude Opus 4.6, February 2026: 7% within reachClaude Mythos Preview (early), April 2026: 14% within reachToday (estimate), November 2026: 36% within reach
Each step is a new best model measured by METR, four in five; the dashed end is today's estimate. Point at a dot for the model.

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.

Robots and the physical work

Anthropic rates 31% of the working time of the people in this industry as physical work. For 28% of the working time, a robot has been shown doing most of the task somewhere: 25% in a purpose-built cell, 3% in a structured facility. 0.30 of 3.

  • Not physical 69%
  • No robot shown 4%
  • In a purpose-built cell 25%
  • In a structured facility 3%

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. Weighted by the people in each occupation; each job's page names the robot behind each rated task.

Where the hours are

Jobs by hours within reach now. Now is projected from METR's April 2026 measurement and Epoch's November 2026 index. The 40 largest jobs hold 75% of the people.

People: BLS counts for this industry, May 2025. Pay here: the median paid for the job in this industry, else its mean, else the national median. 187 smaller jobs (102,170 people) count in every total but are not listed. Task data covers 99% of the industry's people; the rest are in BLS "all other" groups with no task list, or in counts BLS does not publish.

The tasks with the most hours within reach by the end of 2028

Across the whole industry, on the chosen pace and reliability.

  1. Design, develop and modify software systems, using scientific analysis and mathematical models to predict and measure outcomes and consequences of design.Software Developers
    11 million hours80% of the task within reach
  2. Modify existing software to correct errors, adapt it to new hardware, or upgrade interfaces and improve performance.Software Developers
    9.2 million hours100% of the task within reach
  3. Analyze user needs and software requirements to determine feasibility of design within time and cost constraints.Software Developers
    6.4 million hours70% of the task within reach
  4. Develop or direct software system testing or validation procedures, programming, or documentation.Software Developers
    6 million hours80% of the task within reach
  5. Plan and establish sequence of operations to fabricate and assemble parts or products and to promote efficient utilization.Industrial Engineers
    5.7 million hours100% of the task within reach
  6. Determine system performance standards.Software Developers
    5 million hours100% of the task within reach
  7. Analyze information to determine, recommend, and plan installation of a new system or modification of an existing system.Software Developers
    4.5 million hours100% of the task within reach
  8. Recommend methods for improving utilization of personnel, material, and utilities.Industrial Engineers
    4.3 million hours100% of the task within reach
  9. Develop or implement policies, standards, or procedures for engineering and technical work.Architectural and Engineering Managers
    4.2 million hours99% of the task within reach
  10. Develop manufacturing methods, labor utilization standards, and cost analysis systems to promote efficient staff and facility utilization.Industrial Engineers
    4.2 million hours100% of the task within reach

Scan a typical company in this industry

The industry's largest jobs, in the proportions BLS counts across the whole industry, at the pay it pays, run through the company scan. A starting point before you have a roster, or a benchmark for the one you have. Or choose the whole industry: every occupation BLS publishes for it with task data, at its nationwide headcount, the sector report ($249 for the full report, or included in Pro).

Scan a typical companyOr paste your own roles

Next to this industry

Within reach now and by the end of 2028, long-run pace, four in five. Now is projected from METR's April 2026 measurement and Epoch's November 2026 index.

How it is built: BLS counts the people in each job in this industry; each job's tasks and their lengths give its share within reach at a date; the industry's share is those shares weighted by people. Value is pay times 1.43 for benefits and payroll costs. Seen in Claude use splits today's share by whether Anthropic saw people bring each task to Claude in 2025; other AI tools are not counted. How it works

Questions about this industry

How much of the work in Navigational, Measuring, Electromedical, and Control Instruments Manufacturing is within reach of AI now?
An estimated 36% of the paid hours in Navigational, Measuring, Electromedical, and Control Instruments Manufacturing are within reach of AI models now and 53% by the end of 2028, on METR's long-run pace at four in five (49% to 54% across the three paces the site shows). 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 jobs in Navigational, Measuring, Electromedical, and Control Instruments Manufacturing carry the most hours within reach?
By hours within reach now (projected from METR's April 2026 measurement and Epoch's November 2026 index): Software Developers (33,020 people, 48% of their time, about 33 million hours a year); Industrial Engineers (16,880 people, 60% of their time, about 21 million hours a year); and Customer Service Representatives (6,920 people, 64% of their time, about 9.3 million hours a year).
Which tasks in Navigational, Measuring, Electromedical, and Control Instruments Manufacturing carry the most hours within reach by the end of 2028?
Design, develop and modify software systems, using scientific analysis and mathematical models to predict and measure outcomes and consequences of design (Software Developers, about 11 million hours a year); Modify existing software to correct errors, adapt it to new hardware, or upgrade interfaces and improve performance (Software Developers, about 9.2 million hours a year); and Analyze user needs and software requirements to determine feasibility of design within time and cost constraints (Software Developers, about 6.4 million hours a year).
What would people working in Navigational, Measuring, Electromedical, and Control Instruments Manufacturing learn first?
Among the 381,547 people in jobs reviewed task by task, the skills most often among the first two things to learn on their job's page are reviewing work you did not do yourself (262,140 people); briefing a model and checking its drafts (209,240 people); and the hands-on craft (133,607 people). By the end of 2028 on the long-run pace at four in five, about 46% of their working time stays with people, 47% becomes checking a model's work and 5% can be handed over with lighter checks. It says which parts of the work change, never whether anyone keeps a job.
How is this estimated?
BLS counts the people in each occupation in Navigational, Measuring, Electromedical, and Control Instruments Manufacturing (May 2025); each occupation's share of working time within reach comes from its O*NET tasks, each with an estimated length checked against GDPval, 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. The industry's share is those shares weighted by people. Task data covers 99% of its people, and 93% are in occupations reviewed task by task. Data checked November 10, 2026.

How the estimates are made

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