π‘ Software Developers have a composite risk score of 34/100 (Frey-Osborne probability: 13%, GenAI exposure: 80/100). With 1,654,440 workers in the US, this occupation faces moderate but manageable AI pressure. Full occupation profile β
π― The Verdict
Partially. Some tasks will be automated, but the core role will likely adapt and evolve.
With 1,654,440 workers and a median wage of $133K,software developers represent a significant portion of the US workforce. Their GenAI exposure index is 80%, meaning a majority of their core tasks overlap with current generative AI capabilities.
Risk Score
34/100
Employment
1,654,440
Median Wage
$133K
GenAI Exposure
80%
β οΈ Top Risk Factors
Machine learning model auto-tuning displacing ML engineers
AI-powered research and literature review tools
AI-generated written content replacing manual drafting
π‘οΈ Tasks AI Can't Easily Replace
Architecting novel systems requiring creative problem-solving
Stakeholder negotiation and requirements elicitation
Mentoring junior developers and team leadership
Crisis debugging of complex production incidents
π Career Transition Paths
Related occupations with lower AI risk and high skills overlap:
Advertising, Marketing, Promotions, Public Relations, and Sales Managers
61% skills overlap Β· $145K median wage
Mathematicians
70% skills overlap Β· $122K median wage
Computer and Information Research Scientists
83% skills overlap Β· $141K median wage
β Frequently Asked Questions
Will AI completely replace software developers?
Partially. Some tasks will be automated, but the core role will likely adapt and evolve.
What is the AI risk score for software developers?
Software Developers have a composite AI automation risk score of 34 out of 100, classified as "Moderate".
How many software developers are there in the US?
There are approximately 1,654,440 software developers employed in the United States.
What do software developers earn?
The median annual wage for software developers is $133K.
What skills should software developers develop?
Focus on tasks AI can't easily replicate: architecting novel systems requiring creative problem-solving, stakeholder negotiation and requirements elicitation, mentoring junior developers and team leadership, crisis debugging of complex production incidents. These human-centric skills will become more valuable as routine tasks are automated.