JobRiskAI

Chemical Equipment Operators and Tenders

SOC 51-9011ProductionData vintage 2026-07
Low exposure AI applicability score 0.090, higher than 30% of the 785 occupations measured · #47 most exposed of 100 in Production

The core of this work stays human, for now.

Most of this occupation's activities don't appear in measured AI usage. The paperwork fringe can be accelerated, but the core of the work stays human for now.

Where this occupation sits among all 785 measured. Bands are quintiles of the real distribution. Applicability measures task overlap with observed AI usage. It is not a probability of job loss.

What this job involves

Operate or tend equipment to control chemical changes or reactions in the processing of industrial or consumer products. Equipment used includes devulcanizers, steam-jacketed kettles, and reactor vessels.

Where AI overlaps this work, activity by activity

The occupation's most important work activities (O*NET weights, normalized to this set), each with its measured AI performance across 200,000 real conversations: how often AI is used for it, how well it completes it, and how much of the activity it covers.

Work activityShare of roleAI performance
Operate industrial processing or production equipment.13.3%Not observed 0.00
Monitor equipment operation.13.3%Not observed 0.00
Clean tools, equipment, facilities, or work areas.12.0%Not observed 0.00
Direct organizational operations, activities, or procedures.8.5%Not observed 0.00
Maintain safety or security.7.5%Moderate 0.56
Maintain operational records.7.4%Not observed 0.00
Adjust equipment to ensure adequate performance.6.9%High overlap 0.67
Collect samples of products or materials.6.7%Not observed 0.00
Operate pumping systems or equipment.6.3%Not observed 0.00
Test characteristics of materials or products.6.3%Not observed 0.00
Inspect commercial, industrial, or production systems or equipment.6.1%Not observed 0.00
Read documents or materials to inform work processes.5.6%Moderate 0.55

"Not observed" is a measurement, not missing data: that activity does not meaningfully appear in the usage sample. AI performance = completion × scope × coverage (user-goal view), 0–1.

What drives this score: the biggest AI-overlapped activity in this role is maintain safety or security; the most important activity AI is not observed doing is operate industrial processing or production equipment. The plan below is built around exactly that split.

Protect the core, automate the fringe.

Next 30 days

  • Automate the fringe. The small text-and-paperwork layer of this job, Maintain safety or security, is worth handing to AI now; it's the least valuable part of your week anyway.
  • Confirm your reality. If your actual role involves far more screen work than the occupation average, the personalization above will say so.

Next 90 days

  • Convert resilience into rate. Work like Operate industrial processing or production equipment is measured as beyond current AI: supply of it doesn't scale with software. Skill up and price accordingly.
  • Let AI carry your admin. Quotes, scheduling, follow-ups, records: the overhead around the core work is where the tools pay off for you.

The longer game

  • Watch robotics, not chatbots. For low-exposure occupations the relevant automation frontier is usually physical or regulatory, which this dataset deliberately doesn't measure. Track your industry, not AI headlines.
  • Build the customer asset. Reputation and repeat relationships are the moat generative AI cannot cross. Invest there.

Compare this occupation with another

Sources for this page:
  • AI applicability score and per-activity metrics: Tomlinson, Jaffe, Wang, Counts & Suri, Working with AI: Measuring the Applicability of Generative AI to Occupations, Microsoft Research 2025 (arXiv:2507.07935), data CC BY 4.0.
  • Occupation description and activity structure: O*NET 30.0 Database, USDOL/ETA, CC BY 4.0.
  • Bands, personalization weights and action plans are JobRiskAI editorial layers; method and limitations on the methodology page.