TY  - RPRT
        AU  - Drydakis, Nick
        TI  - Artificial Intelligence-Related Digital Skills and Employment Outcomes for Underrepresented Women
        PY  - 2026/Sep/
        PB  - Institute of Labor Economics (IZA)
        CY  - Bonn
        T2  - IZA Discussion Paper
        IS  - 18964
        UR  - https://www.iza.org/publications/dp18964
        AB  - This study examines whether signalling AI-related digital skills improves employment outcomes for women from underrepresented groups in England, defined by race, age, sexual orientation, and autism-spectrum disclosure. The study finds that underrepresented women receive fewer interview invitations and are considered for lower-paid vacancies than majority-group women. In pooled analyses, signalling AI-related digital skills increases interview invitations for underrepresented applicants, but does not eliminate their disadvantage. These findings are consistent with AI Capital and productivity-signalling frameworks, as employers appear to value AI-related capabilities while the returns to such credentials remain constrained by persistent demographic inequalities. The study therefore demonstrates that positive returns to AI-related skills and labour-market disadvantage can coexist. Its broader implication is that digital upskilling can strengthen the recruitment prospects of underrepresented women, but cannot by itself deliver parity in employment outcomes. A dual policy response is therefore required, combining wider and more equitable access to AI education and training with stronger anti-discrimination enforcement.
        KW  - AI Capital
KW  - artificial intelligence
KW  - skills
KW  - discrimination
KW  - hiring
KW  - wages
KW  - sexual orientation
KW  - race
KW  - age
KW  - autism spectrum
        ER  -