A growing body of research shows that one’s socio-economic status (SES) shapes access to quality employment, with individuals from high-SES backgrounds being more likely to secure stable, well-paid, and professionally rewarding roles than those from low-SES backgrounds (Côté, 2022; Kish-Gephart et al., 2023). These disparities are not due to differences in ability or potential, but rather stem from unequal access to social and career resources (Burke et al., 2020; De Schepper et al., 2023; Tomlinson, 2017) and differences in communication and self-presentation during interviews (Sharps & Anderson, 2021).
As emerging technologies such as Generative AI (GenAI) continue to reshape hiring practices, they may offer new challenges for addressing SES-based inequities. Recent studies find that the use of GenAI can enhance applicants’ hireability by improving written materials and supporting more effective interview preparation (Canagasuriam & Lukacik, 2025; Hickman et al., 2024). However, access to and familiarity with GenAI tools appear to be unevenly distributed across socio-economic groups. A nationally representative U.S. survey indicates higher-SES individuals reporting greater awareness and higher adoption of these technologies (Angrisani et al., 2026). Drawing on Bourdieu’s (1984) theory of capital, we propose that GenAI may function as a differentiator, amplifying advantage for those who are able to use it more skillfully and strategically. Specifically, we expect that high-SES applicants are more likely to exhibit more skillful engagement with GenAI. They might use complex prompts, experiment with multiple drafts, and fine-tune the tone and structure of outputs to better align with employer expectations, improving the quality of their applications. Conversely, low-SES applicants may rely on GenAI for more surface-level assistance; for example, they may (on average) use more generic queries or rely heavily on default suggestions, resulting in content that is less tailored, persuasive, or professionally polished. These SES-linked differences in GenAI skills may influence the quality of application materials and, in turn, shape hiring outcomes.
We will recruit a socio-economically diverse sample of 190 university students in Australia (i.e., soon-to-be job seekers) to complete a 20-minute online survey. Participants will be asked to imagine that they would apply for the graduate program in a fictitious organization called CSA Supermarket. As part of the application process, they will then be asked to record a two-minute video résumé. To support their preparation, participants will be provided with access to a customized GenAI tool, which allows free-form interaction, enabling applicants to brainstorm, refine, and polish their responses.