Is AI for All? Tackling the gender gap in Generative AI adoption

Generative AI has revolutionised productivity and innovation, offering tools that can transform industries and create new opportunities. However, a persistent and significant gender gap in AI usage threatens to undermine its potential as a tool for equity.

A recent global study from Harvard Business School reveals the depth of this disparity, examining the causes, implications, and steps needed to bridge the divide.

The study analysed data from over 100,000 individuals across 26 countries, highlighting a consistent trend: women are less likely than men to use generative AI tools.

Even in regions where access to AI technology is equalised, the gap persists, emphasising the need for targeted interventions that address deeper structural and behavioural barriers.

GenAI driving equity

Generative AI is unlike previous waves of automation. While traditional automation often displaced jobs, AI promises to enhance productivity while reducing inequality. For women, particularly in the workforce, AI could be transformative. It offers solutions to longstanding challenges such as lack of mentorship, disproportionate household burdens, and barriers to STEM careers by automating repetitive tasks, providing accessible learning tools, and enabling skill-building.

In theory, AI’s accessibility makes it a universal equaliser. Its tools are inexpensive, require basic literacy, and are easily accessible via smartphones. Yet, the study found that women are 25% less likely to use these tools than men, indicating that low barriers to entry alone are not sufficient.

The study’s analysis reveals that the gender gap in AI usage is nearly universal, affecting diverse demographics and sectors.

• Global data: women are consistently underrepresented in AI usage across 16 studies, spanning occupations from Kenyan entrepreneurs to U.S. college students. For example, in the United States, 50% of men reported using AI compared to only 33% of women.

• Platform-specific trends: data from major AI platforms like ChatGPT, Anthropic’s Claude, and Midjourney show that women account for only 31% to 42% of users globally, with similar patterns across high-income and low-income countries.

• Persistent gaps despite equal access: even when women were given the same opportunities as men to engage with AI tools, as in field experiments in Kenya, they were 12-14% less likely to use the technology. This highlights that access alone does not eliminate the gap.

  
  

These findings underscore that the issue is not limited to underrepresentation in specific industries or regions; it reflects broader structural and cultural barriers.

Why women use AI less: structural and behavioural barriers

The gender gap in AI usage stems from a mix of entrenched structural inequities and behavioural tendencies:

1. Cultural norms: social expectations often discourage women from engaging with new technologies, particularly in male-dominated fields like AI.

2. Skill gaps: women’s underrepresentation in STEM fields contributes to a lack of confidence and proficiency with advanced technologies.

3. Trust and awareness: women may approach new technologies with caution, especially if they perceive potential biases or risks.

4. Lack of exposure: women are less likely to encounter AI tools through professional networks or educational programs.

These barriers are compounded by systemic issues such as unequal access to mentorship, limited time due to caregiving responsibilities, and societal biases that shape career trajectories.

Addressing the gender gap in generative AI is not just a matter of fairness; it has profound implications for businesses, economies, and societies.

• Economic growth: closing the gap could unleash untapped talent, driving innovation and productivity across industries.

• Business benefits: organisations with diverse teams tend to outperform their peers. Encouraging women’s participation in AI can lead to more inclusive and creative solutions.

• Social impact: Generative AI can empower women in underserved communities, offering tools for education, entrepreneurship, and career advancement.

Bridging the divide through various strategies

To close the gender gap in generative AI, targeted interventions are essential.

Here are some strategies:

1. Awareness and education

   • Develop AI literacy programs tailored to women, emphasising practical applications and career benefits.

   • Highlight stories of women successfully using AI to inspire confidence and interest.

2. Inclusive design

   • Create AI tools that prioritise user diversity, reducing implicit biases.

   • Incorporate features that address women’s unique needs and challenges, such as accessibility for caregivers.

3. Mentorship and role models

   • Establish mentorship programs connecting women with leaders in AI.

   • Showcase successful women in tech to challenge stereotypes and inspire participation.

4. Corporate accountability

   • Integrate AI adoption into Diversity, Equity, and Inclusion (DEI) strategies.

   • Set measurable goals for gender representation in AI usage and training initiatives.

5. Policy support

   • Governments and organisations should fund initiatives that promote gender equity in AI.

   • Introduce subsidies or incentives for training programs aimed at women in AI and STEM fields.

The global gender gap in generative AI usage is not inevitable, it can be addressed through deliberate and collaborative efforts. Businesses, policymakers, educators, and technologists must work together to ensure that AI’s transformative potential is accessible to all.