Every year, the fourth Thursday of April marks International Girls in ICT (Information and Communication Technology) Day, a global call to action led by the International Telecommunication Union (ITU). This year, the celebration falls on April 23, 2026, and the theme, "Girls in ICT for inclusive digital transformation," could not be better. It is not just about encouraging girls to use technology. It is about ensuring they help build it, govern it, and shape the direction it takes in the world.
The numbers tell a story worth pausing on. According to 2026 data from Kepios, only 70.7% of women globally are online, compared to 75.7% of men, a gap that translates to roughly 240 million more men than women using the internet. While these figures might seem abstract, they represent something far more concrete: missed opportunities in education, income, and participation in a world that increasingly runs on data. When a girl cannot access the internet reliably, she is not just offline. She is excluded from the very spaces where the digital future is being built.
This exclusion becomes more pressing when you consider how rapidly AI and data science are redefining what skills will matter most in the coming decades.
Why Data Science Specifically Matters for Girls in ICT
The conversation around women in technology has often centered on broader representation metrics. What gets less attention is the specific pipeline problem in data science and AI, fields that are not just growing, but actively reshaping healthcare, agriculture, education, and governance. These are the sectors that determine quality of life, especially in developing economies, and the people who design them will decide whose needs get prioritized.
According to Women in Tech Network, In AI just 30% of professionals are women, reinforcing the urgency of addressing gender gaps in fast-developing technologies. In senior leadership, the picture is even more uneven. Cisco data shows only 12.4% of women hold Vice President or C-suite roles in tech. When women are absent from these positions, AI systems end up reflecting a narrow slice of human experience. They get trained on incomplete data, designed for default users, and deployed without accounting for the lives of half the global population.
The challenge, then, is not only about fairness. It is about the quality and reach of AI for development itself.
The Barriers Are Specific, Not Abstract
It is easy to talk about "closing the gap" without naming what the gap actually looks like in practice. In India, women form 31% of the technology workforce as of 2026, a figure that remains relatively low despite visible progress. More telling is the access problem upstream: women and girls in India have less access to mobile phones and the internet, which directly reduces the number of girls who enroll in computer science programs, and fewer still who complete them.
The barriers compound across layers:
- Rural and government schools often lack resources for robotics, coding labs, or even reliable internet access, meaning girls who grow up outside urban centers rarely encounter these tools during the years when curiosity is most easily sparked.
- Social norms in many communities still position technology as a masculine domain, which shapes girls’ beliefs about their potential before they engage with technology.
- Affordability constraints and online spaces that too often exclude or endanger women and girls make even the act of going online feel unsafe or financially out of reach for many.
- The absence of visible role models in data science and AI means that even girls with the aptitude and interest often cannot picture themselves in the field.
These are not insurmountable problems, but they require intentional responses, not passive hope that representation will improve on its own.
Despite these barriers, early and targeted interventions in ICT education can effectively break this cycle and open pathways into AI and data science careers.
From ICT Exposure to Data Science Careers: The Connection Is Direct
There is growing evidence that early exposure to technology shapes long-term career choices. A girl who builds a simple app in a school tinkering lab, or who writes her first line of code in a government-funded program, does not just gain a technical skill. She gains a self-concept: that she belongs in this space, that she is capable of creating, not just consuming.
This is the logic behind programs like the ITU’s EQUALS Global Partnership, which aims to equip 100 million women and girls with digital skills by 2035. It is also why initiatives like Capgemini’s STEM and Tinkering programs in Indian government schools focus on introducing girls to robotics, AI, and electronics as early as possible. The goal, as they put it, is to move girls from consuming content to expressing their own perspectives through creation.
At the next level, Capgemini’s Digital Academy program trains young women in digital and future skills, with many graduates going on to join the company after completing their assessments. This kind of pathway matters because it bridges the gap between education and employment, a loop that too often breaks down for women in STEM.
There is also the economic argument, and it is a substantial one. According to the United Nations, closing the gender gap in mobile internet adoption in low and middle income countries could add more than $1 trillion in gross domestic product to the global economy. Mobile money (digital financial services that allow users to send, receive, and save money using mobile phones) alone has already lifted millions out of poverty, with women-led households seeing some of the largest gains. A comparable increase in girls’ participation in data science could yield significant economic benefits.
Communities That Are Moving the Needle
The importance of mentorship and visible role models becomes real when communities actively create spaces for girls and women to connect, learn, and thrive. Progress rarely comes from policy alone. Much of the real change happens at the community level, through people who build spaces where girls and women can learn, connect, and grow.
Ana Cidre, Head of International Developer Relations at Okta and founder of GalsTech, described the motivation behind creating her community in 2017 this way: in the UK, women make up 47% of the overall workforce but only 21% of IT specialists. That gap is the result of accumulated structural choices, from how computer science is taught in schools to how tech companies recruit and retain talent. GalsTech was built to counter that by connecting women in the developer community, creating mentorship pathways, and showing younger generations that this field has a place for them.
The ITU itself shared a striking example from one of its programs: a 12-year-old girl who participated in the "Her Digital Skills" initiative and built an app to teach children about horses. It is a small story with large implications. With the right support, that same girl might go on to build tools that improve education systems or reshape digital health delivery.
These are not exceptional cases. They are what becomes normal when access and encouragement are provided consistently.
What the Digital Future with Data Science Actually Requires
The phrase "digital future" gets used often enough that it risks becoming meaningless. What it actually means, in practical terms, is a world where decisions about people are increasingly made by systems built on data, whether that is a credit scoring algorithm, a disease detection model, or a recommendation engine that shapes what news someone reads. The people who build those systems carry enormous responsibility, and right now, too few of those people are women.
Despite growing awareness, only 35% of STEM graduates globally are women, a figure that has not changed in the past ten years. The cost is not just demographic. It is the untapped potential of girls who could have been the coders, data scientists, engineers, and policy thinkers that AI development desperately needs.
What changes this requires is not complicated in concept, though it takes sustained effort in practice:
- Starting ICT education earlier, particularly in underserved and rural schools, and making it hands-on rather than theoretical.
- Creating safe environments where girls can experiment, fail, iterate, and grow without being discouraged by social norms or a lack of belonging.
- Investing in mentorship so that girls pursuing data science have professional relationships with women who have walked that path.
- Designing digital inclusion goals into national development strategies from the beginning, rather than treating them as an afterthought.
Conclusion: Girls Are Not the Future of AI Development. They Are the Present.
Fact: Research from Nesta shows that only 14% of AI research papers have a female first author, while UNESCO reports that women globally are 25% less likely than men to possess basic digital skills and four times less likely to have advanced programming skills. This means most AI models are being shaped by a narrow perspective from the very beginning of the research pipeline.
International Girls in ICT Day is a useful focal point, but efforts to increase girls’ participation must continue year-round. Every day that a girl in a rural school does not encounter a coding tool is a day the pipeline narrows. Every time a young woman leaves a tech program because the culture is unwelcoming is a loss that compounds over time.
The institutions, companies, and communities doing this work well are not just improving representation metrics. They are actively shaping what AI for development can achieve, whose problems it addresses, and what kind of digital future actually gets built. When girls are given the tools, the safety, the role models, and the opportunities to lead in data science and ICT, they do not just participate in the digital future. They help design it into something worth building toward.
Frequently Asked Questions
What is International Girls in ICT Day and why is it important?
International Girls in ICT Day is a global initiative that encourages girls to pursue careers in technology. It highlights the need for inclusive digital transformation by ensuring girls actively participate in building and shaping digital systems.
Why is increasing girls’ participation in AI and data science important?
Greater participation ensures diverse perspectives in building AI systems, reducing bias and improving how technologies serve different populations and real-world needs.
What are the main barriers preventing girls from entering ICT and data science fields?
Limited access to technology, social norms, affordability issues, lack of safe online spaces, and fewer visible role models all contribute to lower participation.
How can early ICT exposure influence girls’ career paths?
Early exposure to coding, robotics, and digital tools helps build confidence and interest, making girls more likely to pursue careers in AI and data science.
How does improving digital inclusion for girls impact the global economy?
Bridging the gender gap in digital access and skills can unlock significant economic growth, increase workforce participation, and drive innovation across sectors.
