Entry Barriers to the Labor Market in the Era of Generative Artificial Intelligence: A Critical Review of the Impact on Junior Profiles (2022–2026)

The emergence of generative artificial intelligence models has restructured the labor market in ways conventional analyses failed to anticipate: the adjustment falls disproportionately on entry-level workers. This literature review examines empirical evidence from 2022 to 2026 on how generative AI adoption has affected hiring, wages, and the organizational structure of junior positions in high-exposure sectors. Findings from Harvard, Stanford, IESE, the World Economic Forum, and the ILO converge on a central conclusion: companies are substituting entry-level roles not through mass layoffs, but through the systematic slowdown of new hiring — a trend termed seniority-biased technological change. This reduces social mobility, compresses starting wages, and threatens organizational human capital continuity in the medium term.