AI and Gender: Redefining Equity in the Future of Work

As Artificial Intelligence (AI) continues to reshape the future of work, a critical but often overlooked dimension is its potential to perpetuate, or even exacerbate, gender imbalances within the workforce. This paper delves into the deeper, less-explored implications of AI on gender inequity, focusing specifically on the reinforcement of gender stereotypes through biased algorithms, the undervaluation of women’s work, and the intersectionality of gender and technology in non-traditional roles. AI systems, frequently trained on historical data, risk amplifying biases that have long marginalized women in STEM fields and leadership positions. Yet, a more insidious challenge lies in how AI disproportionately assigns value to work typically performed by women, such as caregiving and education, which are less likely to benefit from AI-driven innovation and automation. This disparity threatens to deepen the existing gender imbalance, relegating women to lower-paying, lower-growth sectors while AI propels traditionally male-dominated industries into the future. Additionally, AI's role in shaping job evaluations and hiring practices may further entrench gendered labor divisions unless there is a deliberate effort to redesign AI systems with gender equity in mind. The paper proposes an integrated framework for addressing these challenges, focusing on bias-aware AI design, gender-responsive workforce policies, and rethinking the role of women in the AI-driven future of work.