Will AI replace First-Line Supervisors of Production and Operating Workers?
Work in First-Line Supervisors of Production and Operating Workers sits in the in-between: AI reaches some of it (~40% in theory) but is only measured doing about 0% today — part human, part machine.
O*NET-SOC 51-1011
How your 20 core tasks split
Top = what GPT-4 judged AI could speed up. Bottom = how much AI was actually used for these tasks (Anthropic's March 2026 report, usage from Aug & Nov 2025). The gap is the real story.
Back in 2023, GPT-4 judged AI could, in theory, assist with a moderate share of this job's tasks (~40%). By late 2025, real-world AI use had reached about 0% of its task activity (still rare). The gap between that 2023 forecast and today is the real story.
Where this job sits among 738 jobs
Each dot is one of 738 U.S. jobs. Right = AI can do more of it. Up = AI is actually used more.
The signals here line up
Theoretical reach (~40%), real-world use (~0%) and the task-level picture mostly agree — so this read is more reliable than for jobs where the signals contradict each other. Even so, AI-risk estimates shift by model (a 2026 study saw the "high-risk" share swing 2.7%–51.5%), so treat these as directional, not destiny.
See all 20 tasks, ratedBased on real task-level AI scores — click to collapse
- Keep records of employees' attendance and hours worked.
- Interpret specifications, blueprints, job orders, and company policies and procedures for workers.
- Calculate labor and equipment requirements and production specifications, using standard formulas.
- Read and analyze charts, work orders, production schedules, and other records and reports to determine production requirements and to evaluate current production estimates and outputs.
- Plan and establish work schedules, assignments, and production sequences to meet production goals.
- Confer with other supervisors to coordinate operations and activities within or between departments.
- Evaluate employee performance.
- Determine standards, budgets, production goals, and rates, based on company policies, equipment and labor availability, and workloads.
- Recommend or implement measures to motivate employees and to improve production methods, equipment performance, product quality, or efficiency.
- Maintain operations data, such as time, production, and cost records, and prepare management reports of production results.
- Requisition materials, supplies, equipment parts, or repair services.
- Recommend or execute personnel actions, such as hirings, evaluations, or promotions.
- Plan and develop new products and production processes.
- Enforce safety and sanitation regulations.
- Inspect materials, products, or equipment to detect defects or malfunctions.
- Observe work and monitor gauges, dials, and other indicators to ensure that operators conform to production or processing standards.
- Direct and coordinate the activities of employees engaged in the production or processing of goods, such as inspectors, machine setters, or fabricators.
- Conduct employee training in equipment operations or work and safety procedures, or assign employee training to experienced workers.
- Confer with management or subordinates to resolve worker problems, complaints, or grievances.
- Set up and adjust machines and equipment.
How we measured this — and how fresh it is
AI's theoretical reach data: 2023
From GPTs-are-GPTs (Eloundou et al.), where GPT-4 rated how much of each task an AI tool could meaningfully speed up. This is the most recent open, commercially-usable occupation-level potential dataset — it dates to 2023. Newer multi-model re-runs exist but swing wildly (one 2026 study saw "high-risk" jobs range 2.7%–51.5% by model) and aren't openly licensed, so we show the stable 2023 baseline and pair it with newer real-world data.
Real-world AI use 2026 report
From the Anthropic Economic Index, which observes how real Claude conversations map onto each occupation's tasks. Published in Anthropic's March 2026 labor-market report, based on usage measured in Aug & Nov 2025 (Sonnet 4 / 4.5).
Task list & ratings O*NET 30.3
Tasks come from O*NET 30.3. Each task's "AI can do / speeds up / still on you" tier uses the real task-level exposure scores from GPTs-are-GPTs (E1 / E2 / E0) — not a guess from keywords.
Sources: O*NET 30.3 (CC BY 4.0) · GPTs-are-GPTs (MIT, 2023) · Anthropic Economic Index (CC BY, Aug & Nov 2025). Page compiled June 2026. "O*NET" is a trademark of the U.S. Department of Labor.
This page is for general informational purposes only and is not career, financial, or employment advice. AI exposure reflects research estimates of task overlap, not predictions about any individual's job, employer, or future employment.