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The AI Resilience Report helps you understand how AI is likely to impact your current or future career. Drawing on data from over 1,500 occupations, it provides a clear snapshot to support informed career decisions.
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Last Update: 5/19/2026
Your role’s AI Resilience Score is
Median Score
Meaningful human contribution
Measures the parts of the occupation that still require a human touch. This score averages data from up to four AI exposure datasets, focusing on the role’s resilience against automation.
Med
Long-term employer demand
Predicts the health of the job market for this role through 2034. Using Bureau of Labor Statistics data, it balances projected annual job openings (60%) with overall employment growth (40%).
Low
Sustained economic opportunity
Measures future earning potential and career flexibility. This score is a blend of total projected labor income (67%) and the role’s inherent ability to adapt to economic and technological shifts (33%).
Low
This reflects the reliability of your score based on the number of data sources available for this career and how closely those sources agree on the outlook. A higher confidence means more consistent evidence from labor experts and AI models.
There are a reasonable number of sources for this result, but there is some disagreement between them.
Contributing sources
Timing Device Assemblers and Adjusters are less resilient to AI impacts than most occupations, according to our analysis of 7 sources.
This career lands in "Not Very Resilient" territory because a large chunk of the repetitive, high-volume work — like component inspection, defect detection, and timing tests — is already being handled by AI-powered computer vision and automated test rigs, shrinking the number of entry-level tasks that humans used to own. On top of that, major manufacturers are on track to more than double their automation by 2030, meaning the factory floor will keep changing fast.
Read full analysisLearn more about how you can thrive in this position
Learn more about how you can thrive in this position
This role is not very resilient
This career lands in "Not Very Resilient" territory because a large chunk of the repetitive, high-volume work — like component inspection, defect detection, and timing tests — is already being handled by AI-powered computer vision and automated test rigs, shrinking the number of entry-level tasks that humans used to own. On top of that, major manufacturers are on track to more than double their automation by 2030, meaning the factory floor will keep changing fast.
Read full analysisAnalysis of Current AI Resilience
Timing Device Assemblers
Updated Quarterly • Last Update: 5/14/2026

If you love the idea of making clocks and watches tick perfectly, here's the honest picture: the factory side of timepiece assembly is already deeply automated, while the human side of skilled assembly and adjustment is being augmented by AI rather than replaced. Rolex CEO Jean-Frédéric Dufour openly says "We already use AI in many areas," adding that the company invests roughly CHF 100 million a year to refresh its machine tools, and that "AI helps program and maintain the machines. It enhances human capability." Industry coverage notes that Rolex is one of the most advanced precision manufacturing operations in Europe, with CNC machines and AI helping produce components, while "Final assembly is all done by our craftsmen," meaning assemblers and adjusters still do the most delicate human work.
Computer vision now inspects components for defects, and automated test rigs check timing—jobs that used to rely only on loupes and tweezers. As one trade article on technology in watchmaking explains, "Automation does not eliminate craftsmanship, it reallocates it. The human role shifts from repetition to oversight, from muscle memory to problem-solving." You can read more in WatchPro's industry feature [1] and WatchPro's coverage of Rolex's tech spending [1].

AI adoption is moving fast on the factory floor but slowly at the bench. PwC's 2026 Global Industrial Manufacturing Sector Outlook [2] reports that the share of industrial manufacturers who expect to highly automate key processes by 2030 will more than double, from 18% to 50%, and Manufacturing Dive's reporting on the study [3] shows that high-volume producers have strong economic reasons to invest. Robotic polishing only makes sense at scale, though—as one watch executive notes, "A robotic polishing line only makes economic sense if you're producing over 2,000 identical components per run.
Below that, you're better off with a skilled polisher at a wheel." Cultural and brand factors also slow full automation: luxury buyers expect human craftsmanship, and the British Horological Institute reports [4] that the art of watchmaking has been classed as "critically endangered" by Heritage Crafts, fueling a push to train more humans, not fewer. Meanwhile, CNN reports [5] that for decades the industry has warned of a labor shortage as older watchmakers retire, yet experts report promising levels of interest in the profession, and the Deloitte Swiss Watch Industry Study 2025 [6] underscores that quality, heritage, and human touch remain key selling points. The takeaway for young people: AI is taking over the repetitive grinding and inspection, but steady hands, sharp eyes, and judgment under a loupe are still in real demand.

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They put together and fine-tune clocks and timers to make sure they work accurately and keep the correct time.
Median Wage
$40,790
Jobs (2024)
200
Growth (2024-34)
-17.5%
Education
High school diploma or equivalent
Experience
None
Source: Bureau of Labor Statistics, Employment Projections 2024-2034
AI-generated estimates of task resilience over the next 3 years
Estimate spaces between collets and first inner coils to determine if spaces are within acceptable limits.
Replace specified parts to repair malfunctioning timepieces, using watchmakers' tools, loupes, and holding fixtures.
Review blueprints, sketches, or work orders to gather information about tasks to be completed.
Mount hairsprings and balance wheel assemblies between jaws of truing calipers.
Disassemble timepieces such as watches, clocks, and chronometers so that repairs can be made.
Observe operation of timepiece parts and subassemblies to determine accuracy of movement, and to diagnose causes of defects.
Test operation and fit of timepiece parts and subassemblies, using electronic testing equipment, tweezers, watchmakers' tools, and loupes.
Tasks are ranked by their AI resilience, with the most resilient tasks shown first. Core tasks are essential functions of this occupation, while supplemental tasks provide additional context.

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