JobRiskAI

Crematory Operators

SOC 39-4012Personal Care & ServiceData vintage 2026-07
Moderate exposure AI applicability score 0.128, higher than 45% of the 785 occupations measured · #18 most exposed of 29 in Personal Care & Service

AI touches this job. It does not define it.

AI meaningfully touches parts of this work, yet the majority of its activities remain outside observed AI usage. That's balanced exposure: real efficiency gains are available without wholesale overlap.

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 crematory equipment to reduce human or animal remains to bone fragments in accordance with state and local regulations. Duties may include preparing the body for cremation and performing general maintenance on crematory equipment. May use traditional flame-based cremation, calcination, or alkaline hydrolysis.

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
Clean tools, equipment, facilities, or work areas.15.4%Not observed 0.00
Operate transportation equipment or vehicles.7.7%Not observed 0.00
Operate cutting or grinding equipment.7.7%Not observed 0.00
Maintain operational records.7.7%Not observed 0.00
Counsel others about personal matters.7.7%Moderate 0.56
Explain technical details of products or services.7.7%High overlap 0.81
Embalm corpses.7.7%Not observed 0.00
Load products, materials, or equipment for transportation or further processing.7.7%Not observed 0.00
Evaluate the quality or accuracy of data.7.7%Moderate 0.45
Move materials, equipment, or supplies.7.7%Not observed 0.00
Apply hygienic or cosmetic agents to skin or hair.7.7%Not observed 0.00
Adjust equipment to ensure adequate performance.7.7%High overlap 0.67

"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 counsel others about personal matters; the most important activity AI is not observed doing is clean tools, equipment, facilities, or work areas. The plan below is built around exactly that split.

Balanced exposure: take the gains, deepen the moat.

Next 30 days

  • Harvest the easy wins. Parts of this role, led by Counsel others about personal matters, are already AI-assistable. Claim those hours back this month.
  • Map your own mix. Your split may differ from the occupation average. Run the six-question personalization above and read your range, not the headline.

Next 90 days

  • Invest saved time in the human core. The majority of this occupation's activities show no observed AI usage. Deepen exactly those, starting with Clean tools, equipment, facilities, or work areas.
  • Stay current, lightly. A monthly hour trying new tools on your real tasks beats panic-learning later.

The longer game

  • Own a niche. Moderate exposure means AI will not define this occupation, but specialists who pair domain depth with tool fluency will out-earn generalists in it.
  • Watch the boundary activities. If the 'Emerging' rows in your table above turn 'High' in a future data update, revisit the plan. No countdown clocks, just recheck.

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.