As artificial intelligence (AI) continues to reshape economies and workplaces across the world, one urgent question is coming into sharper focus: where do women stand in the AI revolution? At a key session on Women in AI: A South Asia Perspective, at the AI Impact Summit New Delhi, global and regional experts came together to examine gender equity, leadership, and the future of women workforce in the age of AI.

The discussion brought together voices from UNESCO and UN Women, offering a data-driven look at how AI and digital transformation are affecting women across South Asia—and what must change to ensure this technological shift does not deepen existing inequalities.

Women and AI: A Hard Reality Across the Lifecycle

Opening the session, Tim Curtis, director and UNESCO representative for the UNESCO Regional Office in New Delhi, highlighted a difficult but unavoidable truth: women remain unevenly represented across the entire AI lifecycle—from data collection and system design to development, deployment, and leadership.

Despite growing attention on inclusion, AI systems are still largely shaped by male-dominated teams. This imbalance increases the risk of bias and exclusion resulting in a technology that fails to reflect the realities of half the population.

The session also marked the launch of a gender and AI outlook study for South Asia, which paints a sobering picture of women’s participation in the AI ecosystem.

Women in AI: Numbers Tell the Dismal Story

According to data discussed during the panel, women make up only around 30% of AI engineers globally, based on LinkedIn figures. In South Asia, the numbers are even more concerning. Women account for about 20% of AI professionals in Nepal and just 15% in Bangladesh. Research and academic landscapes across the region show similar patterns, with women underrepresented in technical roles and knowledge production.

The gap becomes even wider when leadership is considered. While women are present in education and entry-level roles, they remain largely absent from decision-making positions that shape AI research agendas, funding priorities, and product direction. This leadership gap means women’s voices are missing where it matters most.

South Asia’s Gender Gap in Focus

Adding detail to the regional picture, Eunsong Kim, Chief of Social and Human Sciences Sector at the UNESCO South Asia Regional Office, presented findings from the South Asia chapter of the Gender in AI Outlook study. The data shows stark gender disparities across AI and related digital sectors.

In India, for example, women account for roughly 30% of the AI workforce, while men dominate at around 74%. Similar gaps appear across education, professional services, financial technology, and manufacturing. No matter the sector, the story repeats: women enter the pipeline in smaller numbers and drop out before reaching senior or technical leadership roles.

Kim noted that while access to education has improved, this has not translated into equal participation in advanced AI roles. Structural barriers, workplace cultures, and lack of mentorship continue to limit women’s progression.

Making Women’s Work in AI Visible: Insights from Africa

Adding a powerful global perspective to the discussion on women and artificial intelligence, Dr. Shikoh Gitau, Chief Executive Officer of Qhala Limited, highlighted how deeply women are already embedded in the AI economy—often without recognition, protection, or visibility.

Globally, women account for only around 22% of the AI workforce, and the number is even smaller when leadership roles are considered. In many African contexts, the gap is wider still. Yet, as Dr. Gitau pointed out, this does not mean women are absent from AI.

“Women are already part of the AI economy, but often invisibly,” said Dr Gitau.

A major concern she raised is the issue of invisible data labour. Across the AI value chain, many women contribute through data preparation, labeling, and moderation—work that is essential to making AI systems function but rarely acknowledged. When this labour remains unseen, it creates serious accountability gaps.

“If we don’t know who produced the data, under what conditions, and with what protections, claims of ‘ethical’ or ‘trustworthy’ AI remain incomplete. If we want responsible AI, we have to look beyond algorithms and into the lives of the people who build them,” added Dr Gitau.

Speaking to AI FrontPage, Chido Dzinotyiwei, Co founder, Vambo AI-African Language AI, opined that lack of technical experience might serve as an illusionary barrier for women to become leaders in AI.

“I believe the reason there are fewer female AI founders and CEOs is that we often feel we must have technical experience to start AI companies, which is not the truth. It’s really about tying your passions or specialties to AI. This could be industries such as healthcare, beauty, fitness, agriculture, or even government in my case, I studied political science and hired someone to build our model,” said Chido.

AI, Jobs, and the Risk to Women’s Work

Perhaps the most urgent warning came from the speaker from UN Women Emad Karim, who focused on how AI-driven job disruption is likely to affect women across South Asia.

Karim explained that women are entering the AI era with inherited inequalities from previous industrial and digital transitions. Historically, women have been concentrated in lower-paid, less secure jobs, while men have dominated higher-paid and more protected roles. AI threatens to intensify this divide.

In 2016, around 40% of women’s jobs globally were considered at risk due to automation and digital change. By 2023, that figure had crossed 50%. With the rapid spread of AI tools, especially generative AI, the number has now surged to over 70% in certain job categories.

Women are also heavily represented in sectors such as content creation, clerical work, and service roles—areas that are likely to be disrupted or augmented by AI. In countries like India, Bangladesh, and Pakistan, Karim warned that up to 80% of women’s jobs could be affected in some form.

Why Transition is Riskier for Women

One of the key concerns raised during the discussion was that women are less able to safely transition from one job to another during periods of disruption. Unlike men, women are often constrained by unpaid care work, lack of social protection, and limited access to reskilling opportunities.

Women are also less likely to move from one insecure or disruptive job to another, especially when transitions involve technical fields like AI engineering. This makes periods of rapid technological change particularly dangerous for women’s economic security.

Speaking to AI FrontPage, Botshelo “Kaykay” Baloyi, CEO | Founder | UmkhoAI | Pushing African Nations Forward, said, “Women are underrepresented in AI leadership not because of lack of skill, but because access to capital, infrastructure, and decision-making power has historically been unequal. As a woman building AI products in and for emerging markets, I have seen firsthand how funding networks, technical credibility, and leadership visibility are far harder to access for women – especially outside the Global North.

Baloyi also added that to increase women’s participation in AI, we need earlier exposure to technical pathways, more capital directed to women-led AI companies, and intentional visibility of women as founders, technical leaders, and policymakers – not just contributors.

“If women are not shaping AI systems, they will remain users of technologies designed without their realities in mind”, said Baloyi.

The Urgent Need for Skills and Policy Action

Across the panel, speakers agreed on one point: upskilling and reskilling women is no longer optional. There is a massive need to equip women with AI-relevant skills, from data literacy and digital fluency to advanced engineering and leadership capabilities.

However, skills alone are not enough. Governments must step in with strong policies that support women through this transition. This includes affordable childcare, social protection during job shifts, incentives for companies to hire and promote women in AI roles, and education systems aligned with future skills. 

From Margins to Leadership

Despite the challenges, the tone of the session was not pessimistic. South Asia has a young population, expanding digital infrastructure, and a growing technology ecosystem. With the right choices, the region can turn its gender gap into a leadership opportunity.

As speakers noted, the goal is not symbolic representation, but meaningful participation and leadership. Women must be creators of AI, not just users affected by it.

The panel closed with a powerful message: the AI future of South Asia is still being written. Whether it becomes a story of deeper inequality or inclusive innovation depends on the actions taken today—to ensure women are not left behind, but instead lead the way.