π‘ Computer Occupations have a composite risk score of 26/100 (Frey-Osborne probability: 22%, GenAI exposure: 35/100). With 4,786,660 workers in the US, this occupation remains well-protected against automation. Full occupation profile β
π― The Verdict
Partially. Some tasks will be automated, but the core role will likely adapt and evolve.
With 4,786,660 workers and a median wage of $106K,computer occupations 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
26/100
Employment
4,786,660
Median Wage
$106K
GenAI Exposure
35%
β οΈ Top Risk Factors
AI pair-programming and code generation tools
AI-driven cybersecurity threat detection replacing analysts
Machine learning model auto-tuning displacing ML engineers
π‘οΈ Tasks AI Can't Easily Replace
Mentoring junior developers and team leadership
Ethical AI oversight and bias auditing
Architecting novel systems requiring creative problem-solving
Stakeholder negotiation and requirements elicitation
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
65% skills overlap Β· $145K median wage
Mathematicians
79% skills overlap Β· $122K median wage
Engineers
57% skills overlap Β· $106K median wage
β Frequently Asked Questions
Will AI completely replace computer occupations?
Partially. Some tasks will be automated, but the core role will likely adapt and evolve.
What is the AI risk score for computer occupations?
Computer Occupations have a composite AI automation risk score of 26 out of 100, classified as "Moderate".
How many computer occupations are there in the US?
There are approximately 4,786,660 computer occupations employed in the United States.
What do computer occupations earn?
The median annual wage for computer occupations is $106K.
What skills should computer occupations develop?
Focus on tasks AI can't easily replicate: mentoring junior developers and team leadership, ethical ai oversight and bias auditing, architecting novel systems requiring creative problem-solving, stakeholder negotiation and requirements elicitation, crisis debugging of complex production incidents. These human-centric skills will become more valuable as routine tasks are automated.