Occupational health and safety specialists and technicians

AI Overlap Index
39.7 / 100
Selectively Exposed

Physical, social, or oversight-heavy work that AI augments rather than replaces.

SOC 19-5000 · Healthcare

Bureau of Labor Statistics
Median pay
$78,900/yr
Hourly
$38/hr
Jobs 2024
163,700
Projected 2034
183,000
10-yr outlook
+12% · Much faster than average
Employment change
19,200
Entry education
See How to Become One
SOC code
19-5000

Signal composition

how the 0-100 score is assembled

Task Automation Impact weight 60%
41.6
contribution to AOI: 25.0
Automation Potential weight 10%
50.0
contribution to AOI: 5.0
Market Pressure weight 15%
30.0
contribution to AOI: 4.5
Entry Barrier Erosion weight 15%
35.0
contribution to AOI: 5.2

By seniority

multiplicative adjustment from category curve

Entry
43.7
mult 1.10x
Mid
39.7
mult 1.00x
Senior
32.6
mult 0.82x

Entry-level roles carry the brunt because they concentrate the most automatable subset of tasks. Senior work is insulated by judgment, relationships, and accountability.

Task-level analysis

scored 0-100 for current-generation AI feasibility, weighted by BLS-stated importance

9 tasks · model: claude-sonnet-4-5-20250929
Supporting t9

Prepare written reports documenting findings and recommendations

AI can synthesize inspection findings, regulatory requirements, and best practices into well-structured reports with recommendations. Given documented observations and data, current LLMs can produce professional safety reports that meet industry standards, though human review ensures accuracy and appropriate emphasis.

BLS evidence: Specialists and technicians 'prepare written reports of their findings.'

72
automation
Important t8

Collect data on work environments for analysis and improvement

AI excels at collecting, organizing, and analyzing structured environmental data from sensors, surveys, and monitoring systems. While some physical data collection requires human presence, much can be automated through IoT devices and digital systems, with AI performing sophisticated pattern analysis and trend identification.

BLS evidence: Technicians 'assist specialists by collecting data on work environments and implementing the worksite improvements that specialists plan.'

68
automation
Core t2

Design and implement workplace programs to control or prevent worker risks

AI can generate program frameworks, policy templates, and control recommendations based on hazard data and regulatory requirements. However, implementation requires stakeholder buy-in, customization to specific workplace cultures, and iterative refinement based on worker feedback that demands human facilitation and judgment.

BLS evidence: They 'design and implement workplace programs and procedures that control or prevent chemical, physical, or other risks to workers.'

52
automation
Important t4

Develop and conduct employee safety training programs

AI can generate training content, slides, and assessment materials based on safety standards and best practices. However, effective delivery requires reading the room, adapting to learner questions in real-time, demonstrating physical techniques, and building safety culture through human connection that AI cannot replicate.

BLS evidence: They 'may develop and conduct employee training programs' covering topics 'such as how to use safety equipment correctly and how to respond in an emergency.'

48
automation
Important t5

Educate employers and workers about maintaining workplace safety

AI can produce educational materials, safety bulletins, and guidance documents efficiently. However, education in workplace settings requires persuasion, addressing resistance to change, adapting messaging to different organizational levels, and building trust relationships that are fundamentally human activities.

BLS evidence: Specialists and technicians 'educate employers and workers about maintaining workplace safety.'

42
automation
Core t3

Investigate workplace incidents to determine causes and recommend prevention measures

Investigation requires physical site examination, witness interviews requiring interpersonal trust, reconstruction of events from incomplete information, and causal analysis in complex sociotechnical systems. AI can help analyze patterns and draft reports but cannot conduct the core investigative fieldwork or sensitive interviews.

BLS evidence: Specialists and technicians 'investigate incidents to determine the cause and possible prevention' and 'analyze data from the incident' to 'recommend improvements to prevent future incidents.'

35
automation
Important t7

Examine worksites to identify environmental or physical hazards affecting employee health

Requires physical presence to assess noise levels, air quality, ergonomic setups, and other environmental factors across diverse worksites. While AI can analyze sensor data and flag potential issues, the examination itself demands mobility through unpredictable industrial environments and contextual assessment of hazards.

BLS evidence: Specialists 'examine worksites for environmental or physical factors that could harm employee health, safety, comfort, or performance' and 'find ways to improve potential risk factors.'

32
automation
Core t1

Inspect and evaluate workplace environments, equipment, and practices for safety compliance

Requires physical presence in diverse workplace environments to assess real-world conditions, spatial reasoning about hazards, and contextual judgment about compliance that varies by industry and setting. AI can assist with checklists and documentation but cannot perform the physical inspection or make nuanced on-site assessments.

BLS evidence: Specialists and technicians 'inspect, test, and evaluate workplace environments, programs, equipment, and practices to ensure that they follow government safety regulations.'

28
automation
Important t6

Demonstrate and ensure proper use of safety equipment by workers

Requires physical demonstration of equipment use, hands-on correction of improper techniques, fitting equipment to individual workers, and real-time feedback on physical performance. This is primarily a physical training task in variable environments that current AI+robotics cannot perform.

BLS evidence: They 'demonstrate use of safety equipment and ensure proper use by workers,' and technicians 'may check to make sure that workers are using required protective gear.'

18
automation

Task heatmap

automation score by task, sorted by weighted contribution

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External signals and sources

category-level priors and BLS fields that feed the four non-task signals

Automation Potential
50
karpathy 5/10
  • Karpathy/BLS Digital AI Exposure (0-10 scale rescaled to 0-100)
Market Pressure
30
outlook: Much faster than average
  • BLS projected outlook: Much faster than average (12%)
  • Indeed demand signal (monthly refresh pending)
Entry Barrier Erosion
35
ed: See How to Become One
  • BLS typical entry-level education: See How to Become One
  • Credential trend signal (annual refresh)

Related in Healthcare

closest AOI neighbors in the same category