Last Update: 3/13/2026
Your role’s AI Resilience Score is
Median Score
Changing Fast
Evolving
Stable
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.
What does this resilience result mean?
These roles are shifting as AI becomes part of everyday workflows. Expect new responsibilities and new opportunities.
AI Resilience Report for
They safely get rid of dangerous materials like asbestos or lead to keep people and the environment safe.
This role is evolving
This career is labeled as "Evolving" because while AI and robots are starting to be used in some hazardous material cleanup tasks, most of the work still relies on skilled human workers. AI tools, like drones and robots, are being tested to make dangerous jobs safer and more efficient, but they haven't replaced people yet.
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 evolving
This career is labeled as "Evolving" because while AI and robots are starting to be used in some hazardous material cleanup tasks, most of the work still relies on skilled human workers. AI tools, like drones and robots, are being tested to make dangerous jobs safer and more efficient, but they haven't replaced people yet.
Read full analysisContributing Sources
We aggregate scores from multiple models and supplement with employment projections for a more accurate picture of this occupation’s resilience. Expand to view all sources.
AI Resilience
AI Resilience Model v1.0
AI Task Resilience
CareerVillage's proprietary model that estimates how resilient each occupation's tasks are to AI automation and augmentation
Microsoft's Working with AI
AI Applicability
Measures how applicable AI tools (like Bing Copilot) are to each occupation based on real usage patterns
Will Robots Take My Job
Automation Resilience
Estimates the probability of automation for each occupation based on research from Oxford University and other academic sources
Althoff & Reichardt
Economic Growth
Measured as "Wage bill" which is a long term projection for average wage × employment. It's the total labor income flowing to an occupation
Medium Demand
We use BLS employment projections to complement the AI-focused assessments from other sources.
Learn about this scoreGrowth Rate (2024-34):
Growth Percentile:
Annual Openings:
Annual Openings Pct:
Analysis of Current AI Resilience
Hazmat Removal Workers
Updated Quarterly • Last Update: 2/17/2026

What's changing and what's not
Hazmat removal work still relies mostly on people. For example, the U.S. Bureau of Labor Statistics describes tasks like using forklifts and heavy trucks to haul contaminated materials [1]. In warehouse settings, self-driving forklifts and AGVs with AI are already common (one survey found 90% of warehouses using some AI tools [2]).
But dangerous cleanup sites are harder. Research shows only a few robots exist for really hazardous jobs – mostly in nuclear plants or lab demos. Robots have been used to sample and vacuum radioactive sites [3], and some teams are testing AI-guided drones or robots to spot and scrub chemical spills [4].
These tools can help “keep humans safe” in extreme cases, but on everyday jobsites the hands-on cleanup is still done by trained crews. Tasks like building containment tents or preparing toxic waste for drums remain manual. In short, parts of this job have seen early automation in controlled settings, but most core hazmat tasks are still done by people [3] [4].

AI in the real world
Artificial intelligence might speed up adoption mainly where it boosts safety or efficiency. In general industry, automated systems have cut injuries and costs [5], so companies are interested in similar gains here. However, hazmat work is unpredictable and tightly regulated.
Dedicated robots and AI must be very reliable, so developing them is expensive. Studies note that “manual operations still make up the bulk of the clean-up effort” in radioactive and chemical spills [3]. Labor costs in this field are moderate (about $48K/year) and the work requires skilled judgment, so there’s less financial pressure than in, say, unsupervised factories.
Social trust and strict safety laws also slow change; many firms remain cautious about new tech. In summary, AI tools can help (for example, drones might quickly map a spill), but machines won’t replace workers soon. Human skills like judgment, problem-solving, and hands-on care are still key – technology is more likely to assist people rather than take over these jobs [3] [5].

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Median Wage
$48,490
Jobs (2024)
51,300
Growth (2024-34)
+1.0%
Annual Openings
5,000
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
Prepare hazardous material for removal or storage.
Build containment areas prior to beginning abatement or decontamination work.
Apply bioremediation techniques to hazardous wastes to allow naturally occurring bacteria to break down toxic substances.
Remove or limit contamination following emergencies involving hazardous substances.
Organize or track the locations of hazardous items in landfills.
Comply with prescribed safety procedures or federal laws regulating waste disposal methods.
Clean mold-contaminated sites by removing damaged porous materials or thoroughly cleaning all contaminated nonporous materials.
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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