Generative Artificial Intelligence (AI) is projected to transform labor markets faster than any prior technology, with estimates suggesting that 80% of United States workers may see at least 10% of tasks affected by large language models. Higher-income knowledge workers appear especially vulnerable. Generation Alpha will make post-secondary decisions during this transition, often under the same "college equals security" heuristic that contributed to Millennial misalignment: 52% underemployment among recent graduates and negative lifetime Return on Investment (ROI) in 23% of bachelor’s programs. This study conducts an integrative analysis of the forces behind adverse Millennial higher-education outcomes using federal labor data (Federal Reserve Bank of New York, Bureau of Labor Statistics, Census Bureau/American Community Survey), institutional datasets (Georgetown University Center on Education and the Workforce, Opportunity Insights), and behavioral economics literature. We identify overlapping domains including stigmatization of non-degree pathways, inflated credential assumptions, cognitive biases in adolescent decision-making, outdated parental mental models of work, and forecasting gaps within K-12 guidance programs. The paper proposes a practical decision framework to help Generation Alpha families evaluate ROI, incorporate AI task exposure, and consider alternative credentials to avoid repeating the errors that shaped Millennial outcomes.

Authors:
Will O'Kane, Auburn University, United States

About the Presenter(s)
Will O'Kane is an Affiliate Assistant Research Professor at Auburn University's Harbert College of Business. His research focuses on educational guidance and workforce resilience, currently developing "no-regrets" skill frameworks for Gen Alpha.

Connect on Linkedin
https://www.linkedin.com/in/willokane/

See this presentation on the full schedule – Saturday Schedule

Bookmark