π‘ Agricultural Workers have a composite risk score of 54/100 (Frey-Osborne probability: 87%, GenAI exposure: 35/100). With 373,730 workers in the US, this occupation faces moderate but manageable AI pressure. Full occupation profile β
π― The Verdict
Possible. Significant task automation is underway β workers should actively upskill.
With 373,730 workers and a median wage of $36K,agricultural workers represent a significant portion of the US workforce. Their GenAI exposure index is 35%, meaning a minority of their core tasks overlap with current generative AI capabilities.
Risk Score
54/100
Employment
373,730
Median Wage
$36K
GenAI Exposure
35%
β οΈ Top Risk Factors
Robotic sorting and packing of produce
Autonomous harvesting and planting machinery
Drone crop monitoring and precision spraying
AI-driven irrigation and soil analysis systems
π‘οΈ Tasks AI Can't Easily Replace
Assessing crop health through hands-on field inspection
Adapting to variable weather and terrain conditions
Managing livestock behavior and welfare
Sustainable land management judgment calls
π Career Transition Paths
Related occupations with lower AI risk and high skills overlap:
Social Scientists and Related Workers
51% skills overlap Β· $93K median wage
Occupational Health and Safety Specialists and Technicians
61% skills overlap Β· $79K median wage
Supervisors of Farming, Fishing, and Forestry Workers
83% skills overlap Β· $59K median wage
β Frequently Asked Questions
Will AI completely replace agricultural workers?
Possible. Significant task automation is underway β workers should actively upskill.
What is the AI risk score for agricultural workers?
Agricultural Workers have a composite AI automation risk score of 54 out of 100, classified as "Elevated".
How many agricultural workers are there in the US?
There are approximately 373,730 agricultural workers employed in the United States.
What do agricultural workers earn?
The median annual wage for agricultural workers is $36K.
What skills should agricultural workers develop?
Focus on tasks AI can't easily replicate: assessing crop health through hands-on field inspection, adapting to variable weather and terrain conditions, managing livestock behavior and welfare, sustainable land management judgment calls. These human-centric skills will become more valuable as routine tasks are automated.