Explosives Workers, Ordnance Handling Experts, and Blasters
AI is not doing this work today.
This occupation's activities barely register in measured AI usage. Generative AI is not doing this work today. The pressures that matter here are more likely economic or robotic than linguistic.
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
Place and detonate explosives to demolish structures or to loosen, remove, or displace earth, rock, or other materials. May perform specialized handling, storage, and accounting procedures.
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 activity | Share of role | AI performance |
|---|---|---|
| Prepare industrial materials for processing or use. | 31.8% | Not observed 0.00 |
| Position tools or equipment. | 10.8% | Not observed 0.00 |
| Operate construction or excavation equipment. | 9.1% | Not observed 0.00 |
| Select materials or equipment for operations or projects. | 6.7% | High overlap 0.63 |
| Monitor operations to ensure compliance with regulations or standards. | 6.7% | Not observed 0.00 |
| Direct construction or extraction activities. | 5.5% | Not observed 0.00 |
| Assemble equipment or components. | 5.3% | Not observed 0.00 |
| Perform general construction or extraction activities. | 5.2% | Not observed 0.00 |
| Position materials or components for assembly. | 5.0% | Not observed 0.00 |
| Assess characteristics of land or property. | 4.9% | Not observed 0.00 |
| Maintain operational records. | 4.5% | Not observed 0.00 |
| Stock supplies or products. | 4.5% | Not observed 0.00 |
"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 select materials or equipment for operations or projects; the most important activity AI is not observed doing is prepare industrial materials for processing or use. The plan below is built around exactly that split.
Low exposure is an asset. Spend it deliberately.
Next 30 days
- Don't buy the panic. This occupation's activities barely appear in AI usage data. Your near-term exposure is other people's headlines, not your tasks.
- Skim the gains anyway. Even here, an assistant helps with the thin admin layer: Select materials or equipment for operations or projects is the one place the data shows any overlap.
Next 90 days
- Deepen the human core. Activities like Prepare industrial materials for processing or use are measured as fully outside current AI. Mastery there is compounding, defensible value.
- Mentor the exposed. Colleagues in adjacent office-heavy roles are the ones facing redesign; understanding their tools makes you a better coordinator and leader.
The longer game
- Watch the actual frontier for this work: usually physical automation, demographics or regulation rather than language models. This dataset intentionally measures only generative AI.
- Revisit after major data updates. If this page's vintage changes and your band moves, the plan moves with it.
- 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.