Work-From-Home Revolution: Enhancing Women’s Participation in STEM Using AI and Machine Learning

Abstract

Abstract Organizational structures have been altered by the rapid transition to digitally enabled work patterns, especially in knowledge-intensive STEM fields. This study looks into how women's involvement, retention, and career advancement in STEM disciplines are affected by Work-From-Home (WFH) practices that are aided by AI and ML. Using an integrated conceptual model, the research explores the direct benefits of WFH and AI/ML adoption, as well as the mediating function of organizational support in improving women’s participation in STEM fields. Findings demonstrate that WFH considerably enhances women’s work–life balance, continuity, and professional visibility, while AI/ML tools support digital upskilling, minimize subjective biases, and promote merit-based development. Organizational support emerges as a vital enabler, boosting the positive impact of technological and remote work solutions. The study comes to the conclusion that women's representation and leadership in STEM can be significantly increased by combining gender-inclusive digital techniques with moral and encouraging organizational practices. The observations add to developing literature on gender equity, digital transformation, and the future of labor in technologically demanding sectors.

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