π‘ Computer Programmers have a composite risk score of 53/100 (Frey-Osborne probability: 48%, GenAI exposure: 72/100). With 109,870 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 109,870 workers and a median wage of $99K,computer programmers represent a significant portion of the US workforce. Their GenAI exposure index is 72%, meaning a majority of their core tasks overlap with current generative AI capabilities.
Risk Score
53/100
Employment
109,870
Median Wage
$99K
GenAI Exposure
72%
β οΈ Top Risk Factors
Automated testing and CI/CD pipeline intelligence
Chatbot displacement of customer-facing interactions
AI coding assistants reducing developer demand
AI-driven cybersecurity threat detection replacing analysts
π‘οΈ Tasks AI Can't Easily Replace
Stakeholder negotiation and requirements elicitation
Ethical AI oversight and bias auditing
Architecting novel systems requiring creative problem-solving
Mentoring junior developers and team leadership
π Career Transition Paths
Related occupations with lower AI risk and high skills overlap:
Advertising, Marketing, Promotions, Public Relations, and Sales Managers
59% skills overlap Β· $145K median wage
Mathematicians
73% skills overlap Β· $122K median wage
Computer Occupations
84% skills overlap Β· $106K median wage
β Frequently Asked Questions
Will AI completely replace computer programmers?
Possible. Significant task automation is underway β workers should actively upskill.
What is the AI risk score for computer programmers?
Computer Programmers have a composite AI automation risk score of 53 out of 100, classified as "Elevated".
How many computer programmers are there in the US?
There are approximately 109,870 computer programmers employed in the United States.
What do computer programmers earn?
The median annual wage for computer programmers is $99K.
What skills should computer programmers develop?
Focus on tasks AI can't easily replicate: stakeholder negotiation and requirements elicitation, ethical ai oversight and bias auditing, architecting novel systems requiring creative problem-solving, mentoring junior developers and team leadership. These human-centric skills will become more valuable as routine tasks are automated.