AI-Exposed College Majors Face Recession-Level Earnings Hits as Automation Reshapes Entry-Level Hiring

A September 2026 working paper from the U.S. Census Bureau's Center for Economic Studies documents a sharp post-ChatGPT deterioration in early-career outcomes for graduates in the most AI-exposed majors. Analyzing administrative records covering roughly 29% of U.S. bachelor's degrees from 2016–2024, economists Cody Orr, Lee C. Tucker, and Lawrence Warren found that the top decile of AI-exposed fields—led by computer science, computer and information systems, and computer engineering—saw initial employment rates drop 5 percentage points and full-quarter earnings fall 13% relative to less-exposed peers after late 2022. This decline matches the scale of losses for graduates entering during major recessions. Half the earnings drop stems from lower pay within traditional high-wage sectors; the other half reflects shifts into lower-paying industries like retail and food services. Effects attenuate after two years but remain notable, with elevated job-switching rates suggesting some recovery. A concurrent Study.com survey of 261 graduates found zero regret among computer science/IT respondents regarding AI's impact—contrasting with 43% regret among communications/journalism graduates—while 77% overall still viewed college as the right choice. Broader context from Federal Reserve analyses highlights that declining job openings, not just AI displacement, compound challenges for young workers, underscoring automation's uneven pressure on workforce pipelines and the need for adaptive education and reskilling strategies amid accelerating technological change.