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Talent forward: Career decisions of high-achieving young women in the AI economy
Author(s)
Date Issued
2026
Publisher
University of Business and Technology
Citation
Cui, X., Choy, Y. T., Yuen, M. T. (2026). Talent forward: Career decisions of high-achieving young women in the AI economy. In University of Business and Technology (Ed.). Conference proceedings of 19th Asia Pacific conference on giftedness 2026. 19th Asia Pacific Conference on Giftedness 2026, University of Business and Technology, Jeddah, Saudi Arabia (pp. 219-220). University of Business and Technology.
Type
Conference Paper
Abstract
Artificial intelligence is reshaping labor markets worldwide, automating routine tasks while creating new, hybrid roles that demand a blend of technical and interpersonal skills. This poster presents a work-in-progress scoping review on the career interests, decisions, and transitions of young women (aged 18–35) in the AI era, with specific attention to implications for high-achieving and gifted learners. The review aims to identify how AI literacy, gendered social factors, and perceptions of job “substitutability” influence choices, and to highlight actionable directions for talent development aligned with a 2050 vision for gifted education. We are systematically searching literature published from 2020 to 2025 across Google Scholar, ERIC, PsycINFO, Scopus, and Web of Science. Inclusion criteria focus on empirical and review studies in English and Chinese addressing young women’s career
decision-making in AI-affected sectors; commentaries without an empirical basis are excluded. Data extraction examines AI literacy, career self-efficacy, perceived automation risk, and the valuation of human-centric skills like empathy and communication. Early indications suggest that young women may show a preference for roles perceived as less automatable or for hybrid positions that leverage collaboration with AI. There appear to be mismatches between market demand and women’s selfperceptions in AI-related fields, where AI literacy may mediate the link between self-efficacy and jobseeking anxiety. Human-centric competencies are frequently framed as differentiators, yet persistent
gender stereotypes and structural barriers continue to shape choices. Evidence gaps include limited longitudinal research and few studies focusing specifically on gifted women. Implications for gifted education include integrating AI literacy with advanced, human-centered competencies and applying CIP-informed career interventions. Also, expanding mentorship and experiential learning in hybrid human–AI. By partnering with industry to create agile pathways that reduce stereotype threat, targeted, evidence-informed interventions can help high-ability young women navigate future-proof career
trajectories and thrive in a technology-driven global economy.
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