# Cover Letter

Dear Editors-in-Chief of Technological Forecasting and Social Change,

Please consider our manuscript, "From Resting Youth to Entry Bottlenecks: Forecasting Generative AI's Effects on Korea's School-to-Work Transitions," for publication as a research article in Technological Forecasting and Social Change.

The manuscript addresses a technology and social-change problem that is central to TFSC's scope: how generative AI may reshape the institutional pathways through which young people enter work. Existing AI-and-employment research primarily measures exposure among incumbent workers. Our study shifts the forecasting lens to a pre-employment and re-entry margin: Korea's "resting" youth, an economically inactive group outside employment, active job search, formal education, care, and illness categories.

Using ten waves of Statistics Korea's May youth supplementary labor-force microdata for 2016-2025, we show that resting youth increased from 260.6 thousand to 395.7 thousand even as the youth population declined. The increase is concentrated around ages 22 and 25, school exit, first-job non-entry, short first-job tenure, and re-entry after prior work experience. We then develop an entry-bottleneck foresight framework that links these observed transition points to generative AI's likely effect on junior tasks, learning-by-doing, and entry-level hiring.

The paper makes three contributions. First, it provides a microdata-based profile of Korea's resting youth across ten years. Second, it reframes AI labor-market exposure as an entry-route problem, not only an incumbent-worker displacement problem. Third, it offers policy implications for redesigning first-work learning, occupationally embedded AI training, and early intervention for long-duration inactivity.

We believe the manuscript fits the Impact and Evaluation of Technology bureau because it evaluates the social consequences of AI diffusion for a vulnerable labor-market transition group. It is also relevant to Technology Governance and Public Policy because it develops concrete policy implications for preserving youth entry routes in AI-augmented labor markets.

The manuscript has not been published previously and is not under consideration elsewhere. All authors will approve the submitted version and agree to be accountable for the work. Any required conflict-of-interest, funding, data-availability, and generative-AI disclosure forms will be completed during submission.

Sincerely,

[Corresponding Author Name]

[Affiliation]

[Email]