The gender test for India’s AI Mission

This article is authored by Nupur Khanter, research associate and Angelina Chamuah, deputy director, Transitions Research.

With World Youth Skills Day this year focusing on youth empowerment through Artificial Intelligence (AI) and digital skills this year, this is a timely opportunity to spotlight how India's AI revolution risks leaving half its population behind. Gender and AI debates have largely focussed on women’s under-representation in the industry. But as AI’s reach expands across sectors, it is equally critical to examine how women are excluded within the broader AI skilling ecosystem. 

AI(Getty Images/iStockphoto)

Despite their role in the economy, women contribute just 18% to India’s GDP - a stark indicator of unequal access to quality work and skills. Outside AI and data science, they face the twin challenge of automation and systemic barriers to digital upskilling. Globally, women are also 1.5 times more likely than men to lose their jobs to AI. In India, this risk is compounded by a persistent digital divide. According to the National Family Health Survey of 2019-2021, only 51.8% of women have ever used the internet in urban India and that number drops down to 24.6% in rural India. More than half of rural women in India do not have a mobile phone that they themselves use.

Take agriculture for instance, where AI tools are increasingly deployed, women make up a large part of the workforce yet remain structurally disadvantaged. They have limited access to land, credit, digital tools, and decision-making roles. As AI reshapes farming, the real question is who will benefit. Without targeted support, women risk being left further behind.

India’s AI disruption offers an opportunity to reset the rules and build systems that are gender-just and inclusive from the start. But simply increasing women’s participation in skilling programmes is not enough. What matters is the quality and orientation of that participation. Are they moving into leadership, design, and governance roles, or just serving the back end of the AI value chain? Outside the AI industry, are women across sectors being equipped with future-ready skills?

India’s AI push is more than a tech agenda, it’s a nation-building one. From the Prime Minister’s call to make AI work for India to the IndiaAI Mission and new ed-tech partnerships, digital and AI skills are positioned as key levers of youth empowerment and economic growth. Yet, access remains unequal and gender is one of the sharpest fault lines. Large-scale skilling programmes often fail to account for the lived realities of women. They assume a generic youth learner, rarely imagining a woman from a low-income or rural background - let alone someone balancing care work, navigating caste or disability barriers, or lacking digital confidence. Women are not a monolithic group - caste, region, disability, income, and language shape their realities. Skilling programmes often miss those at the intersections of multiple disadvantages.  

Even when women do enroll in AI courses, participation patterns reveal deeper inequities. Women are six times more likely to enroll in beginner-level courses than intermediate ones. Few make the leap to advanced AI or machine learning modules. This isn’t about capacity, it’s about confidence, exposure, and structural barriers over years. An AI and equity report by Randstad found that while 71% of men say they have AI skills, only 29% of women report having the same abilities. This leaves women underrepresented in specialist AI roles. Many end up in the lowest-paid, least-visible roles in the AI value chain, like data annotation or content moderation, work that’s essential but disempowering. Women comprise only 22% of AI talent globally, with even lower representation at senior levels, occupying less than 14% of senior executive roles in AI.  

The numbers alone don’t tell the whole story: Where and how women participate in AI matters.

A lack of women’s participation creates a self-reinforcing cycle resulting in biased AI systems. In one study tracking 133 publicly available instances of bias in AI systems across industries since 1988, researchers found that 44.2 percent demonstrate gender bias. AI systems are shaped by the data they are fed and by the people who design, label, and interpret that data. A skilling ecosystem that excludes women from meaningful participation contributes to AI systems that are blind to their needs, biased in their assumptions, and harmful in their impacts.

Efforts to upskill women are underway. The ministry of skill development and entrepreneurship (MSDE) and Microsoft have launched a skilling initiative aimed at empowering women in higher education institutions to pursue careers in AI in Tier-II and Tier-III towns across six states. The Yashoda AI Abhiyan led by the National Commission for Women (NCW) is an effort to empower women especially from rural and semi-urban communities with essential skills in AI, cybersecurity, and digital safety.  Digital Green in the agriculture sector trains women farmers to use its AI-powered platform to boost public extension systems and provide climate-smart gender advisory. In the healthcare sector, the SMARThealth Pregnancy program equips female ASHA community health workers with screening tools and an LLM chatbot to identify and manage high-risk conditions during pregnancy and postpartum care. Myna Mahila upskills local women in generative AI to power a text-based AI platform designed to dispel misconceptions about women’s sexual and reproductive health.

These are welcome steps, but the real challenge lies not just in scale, but in ensuring these efforts are inclusive and transformative. Meaningful skilling today means ensuring women, especially those from marginalised communities, gain AI and digital capabilities that enhance their roles across diverse sectors. Skilling initiatives must also actively build women’s confidence, equip them to navigate AI transitions in their fields and ensure their voices shape how these technologies are designed and trained. If India wants its AI revolution to be truly transformative, it must centre women, not just as learners, but as leaders, designers, and decision-makers. 

This article is authored by Nupur Khanter, research associate and Angelina Chamuah, deputy director, Transitions Research.