Statistics and computer science bear the brunt! Goldman Sachs reveals the most vulnerable college majors in the AI era.

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The impact of AI on the job market is spreading from the workplace to university campuses, forcing students to reconsider their choice of majors.

Goldman's latest research shows that computer science and statistics rank as the two majors with the highest exposure risk to AI. As companies accelerate AI technology deployment, jobs such as administrative support and basic programming that are easily automated are facing significant employment pressure, reducing the attractiveness of related majors. Meanwhile, students are actively shifting toward fields such as healthcare and engineering with high barriers, strong demand, and difficult to replace by machines, marking the onset of a structural shift in major preferences.

Since the advent of ChatGPT, the job market for newly graduated college students in the U.S. has been noticeably weaker than the overall labor market. For many young people burdened with student loans, the uncertainty brought by AI has become an important factor affecting their choice of majors.

Computer Science and Statistics Lead the Risk List; Healthcare and Engineering in the Safe Zone

Goldman analyst Pierfrancesco Mei's team used American Community Survey (ACS) data to track the career flows of graduates from more than 180 college majors, and combined each occupation's AI replacement risk scores to construct an index quantifying the extent of AI's employment shock for different majors.

The results show that computer science and statistics rank among the highest in AI exposure risk. Graduates mostly move into jobs in software development, data analysis, and business services—precisely the fields where generative AI currently excels, putting structural pressure on these major's employment prospects.

On the other end of the risk spectrum are majors related to healthcare and education. These jobs are highly dependent on interpersonal interaction, professional judgment, and hands-on experience, making them difficult for AI to replace in the short term. Additionally, engineering majors also face relatively low risk, while many majors geared toward professional and business services still face high levels of AI risk.

Students Start “Voting with Their Feet”

The impact of AI on employment expectations is already visible in actual enrollment data.

Goldman cites registration data from the National Student Clearinghouse, which covers more than 95% of U.S. colleges, finding that before the 2024-25 academic year, there was no significant correlation between major choice and AI risk; but by the 2025-26 school year, a turning point appears.

Majors corresponding to professions facing high AI replacement risk and weak job growth saw overall enrollment drop by more than 1% year on year, with computer science and programming both declining by more than 10%.

Conversely, low AI risk and strong job growth industries clearly benefit; healthcare and engineering majors saw average enrollment rise by about 3%, making them obvious winners in this shifting trend. This reversal in data marks AI’s influence on education decisions moving from expectation to reality.

AI Shock Brings Back "Blue-Collar Premium"

Goldman believes the current trend is broadly consistent with historical experience. Over the past decades, students typically adjusted their majors based on changes in the job market, but such adjustments often lag by several years, as students observe graduates’ actual employment outcomes, and changing majors itself is costly.

However, this round of adjustments may be noticeably faster. As AI becomes a focal point of societal attention, students’ anxiety about future job prospects has significantly increased, and AI replacement risk has quickly become one of the core variables affecting major choice.

At the same time, AI infrastructure construction is creating a surge in demand for traditional blue-collar jobs. From data center building to power system expansion, as well as equipment installation and maintenance, related industries are absorbing large numbers of workers, forming a new growth pole distinct from white-collar knowledge jobs.

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