Generative artificial intelligence (GenAI) is increasingly transforming the workplace, with potential benefits including enhanced productivity and improved job quality. However, a new report from the International Labour Organization (ILO) highlights significant disparities in how these changes affect men and women. According to the brief titled “Gen AI, occupational segregation and gender equality in the world of work,” women are far more likely to encounter risks associated with GenAI in their workplaces than men, largely due to their concentration in jobs susceptible to automation.
The research reveals that female-dominated occupations are nearly twice as exposed to GenAI as those dominated by men. Specifically, approximately 29 percent of jobs typically held by women are subject to GenAI influences, compared to just 16 percent of male-dominated roles. The situation is even more alarming in jobs at high risk for automation, where 16 percent of female-dominated roles fall into the highest exposure categories, versus only 3 percent for male-dominated occupations.
The report correlates these risks with occupational segregation, noting that women are often employed in clerical, administrative, and business support positions—such as secretaries and payroll clerks—where tasks are routine and easily automated. Conversely, jobs in construction, manufacturing, and manual trades, which are more prevalent among men, are generally less prone to automation.
At the national level, women are more exposed to GenAI in 88 percent of the countries analyzed. In several economies, including Switzerland, the United Kingdom, and the Philippines, more than 40 percent of women’s employment is at risk from GenAI. By contrast, only 11 percent of jobs in low-income countries are exposed, which reflects disparities in occupational structures and digital readiness across different economies.
“Generative AI is not entering a neutral labour market,” stated Anam Butt, co-author of the ILO research. “Discriminatory social norms and unequal economic policies shape who enters which occupations and under what terms. This leaves women highly concentrated in roles vulnerable to automation while remaining underrepresented in AI-related positions, leading to higher risks and fewer opportunities.”
Despite expectations that GenAI will spur job growth in technology sectors, women continue to be significantly underrepresented in these fields. In 2022, women made up only about 30 percent of the AI workforce, a figure that has only marginally improved over the last six years. This underrepresentation extends to broader STEM fields, especially in high-demand areas like engineering and software development.
The implications of this imbalance are profound. The absence of women in AI-related jobs and decision-making roles diminishes their chances for career advancement and skills development, while companies miss out on the benefits of diverse perspectives and innovation. The brief emphasizes that GenAI, similar to its predecessors, is not inherently neutral. Technologies are developed within existing social frameworks, which can perpetuate biases and discrimination.
AI systems that are trained on biased or incomplete data can adversely affect women in various contexts, including recruitment and pay decisions. These risks are further aggravated for women facing multiple forms of discrimination, such as those based on race, ethnicity, or disability. Without adequate safeguards, there is a real danger that GenAI could deepen existing inequalities.
According to the ILO, the predominant impact of GenAI may not be an increase in job quantity but rather a change in job quality. While GenAI has the potential to modify tasks, intensify workloads, and diminish autonomy, it can also, if implemented responsibly, enhance working conditions and contribute to better work-life balance. “The choices made today will determine whether GenAI becomes a force for greater equality or one that entrenches existing gaps,” the report warns.
Janine Berg, a senior economist at the ILO, emphasized that the effects of generative AI on women’s employment are not predetermined. “With the right policies and inclusive design, we can prevent reinforcing existing discrimination,” she said. The importance of strong labor market institutions and social dialogue cannot be overstated. Engaging governments, employers, and workers in discussions about how GenAI is implemented may help steer technological advances toward supporting decent work and fostering a more inclusive labor market for everyone.
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