How AI is making workplace gender gaps worse

Generative AI is radically reshaping the job market—creating new roles, changing some, and phasing out others. But here’s one effect of the transformative technology that’s not as widely talked about: It’s deepening long-standing workplace gender gaps. 

A double disadvantage

According to a recent report from the World Economic Forum and LinkedIn, women systematically face a two-part problem in the ongoing AI transformation. Relatively fewer women are currently in jobs that are being augmented by generative AI, and relatively more are in roles that are being disrupted.

According to LinkedIn data for the US, 24.1% of men work in augmented occupations, while 20.5% of women do. At the same time, 33.7% of women work in occupations that are being disrupted, compared to 25.5% of men. Related research by LinkedIn shows that the pattern of men’s higher representation in augmented roles holds for 95% of the 74 countries with available data. Examples of occupations that look set to be disrupted in the US include medical administrative assistant (91% female) and office manager (88% female). Augmented fields, meanwhile, include electrical engineer (94% male) and mechanical engineer (89% male).

The STEM Gap

The data align with broader AI-related disparities in STEM education and employment. Already, too many women are lost in the transition from STEM degrees to their first job in the STEM workforce. Women who graduated in 2021 accounted for 38.5% of STEM graduates, but only 31.6% of STEM job entrants in 2022. This decline in representation continues across the hierarchy once women are in the workforce: in 2024, women held 29% of STEM entry-level positions and 24.4% of STEM managerial positions in STEM, but only 12.2% of STEM C-suite level roles. Women are also underrepresented in AI-related academic and leadership roles.

To ensure that those who have the right skills have a fair chance to succeed and advance in the workplace, regardless of their gender, business leaders need to review and rethink their hiring practices, performance evaluation methods, and promotion processes. Generative AI itself can both help and hinder efforts to create a more level playing field. Relying on historical employment patterns to make predictions about future performance has too often overlooked women’s potential to succeed in jobs where they have not traditionally been represented. On the other hand, using generative AI to predict future success based on current skills is a powerful way to deploy the latest technology to debias hiring processes and create a more level playing field.

Some positive news

When it comes to AI skills, there are encouraging signs that women are catching up on both AI literacy and AI engineering skills. In 2018, 23.5% of AI engineering skill-listers on LinkedIn were women; in early 2025, this number had risen to 29.4%. Over the past five years, the gap narrowed in 74 of the 75 economies with available data. At the same time, research by LinkedIn suggests that women are more likely to underreport AI skills in their professional profiles.

Disparity among inventors

Currently, no economy is fully leveraging all of the available talent to drive innovation, but some are doing better than others. In a race where every competitive edge counts, this is significant. High-level data on the gender breakdown among inventors, named as such on patent applications, reveals that East Asian economies are drawing on a more extensive talent pool, with more than 25% of inventors being women in China (26.8% in 2019) and South Korea (28.3% in 2019), which is around 10 percentage points higher than in the European Union (EU) and the United States.

Around the world, the generative AI boom is being shaped in ways that don’t fully reflect the diversity of society, leaving women underrepresented in the jobs and leadership roles of the future. Yet this moment offers a rare opportunity to course-correct. By investing in skills, using AI in a way that makes hiring and promotions more equitable, and ensuring technology is built by and for a broader range of people, we can create a more competitive future that expands economic opportunity and promotes fairness. Without such action, generative AI will reinforce inequality instead of driving meaningful progress.

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