International Women's Day: If women are not shaping AI, they will be shaped by it

Throughout my career in technology, I've seen women impacted by the myth of the 'male genius' in technology. It is a culture that gives some people far more leeway to fail, while holding others to a much higher standard. In that environment, many women are conditioned to believe that if they're not going to be the best at something, they don't belong.

That belief is damaging, and it has deep roots. For decades, women have been underrepresented in computer science and technical leadership roles. The reasons are complex, however, corporate culture plays a powerful part. When brilliance is portrayed as innate and male, women are subtly told they are outsiders. At this point, mistakes are tolerated as part of growth for some, but judged harshly for others, and it leads to confidence eroding quickly.

Unfortunately, most companies have not had the systems in place to avoid holding women back. Performance frameworks, promotion criteria and leadership pipelines have often reinforced bias rather than challenged it. Even well-intentioned organisations can fail to recognise how uneven expectations shape outcomes.

AI – part of the core skillset

The same patterns emerge with the next frontier: AI.

According to Harvard analysis, for every 100 men using GenAI tools, only 78 women do. The gap exposes who feels entitled to experiment with new technology and who feels they need permission.

Women have been excluded from much of computer science and technology to date, and we cannot afford for this to happen with AI. The stakes are higher than ever. The gender gap in STEM fields is particularly concerning, as women account for only approximately 21.3% of those who earned a Bachelor's degree in computer and information sciences.

AI is not a niche skill set reserved for engineers. It is rapidly becoming embedded in marketing, customer service, operations, HR, finance and everyday life. 

Technology and data fluency are becoming foundational across every role. If women do not understand how AI systems work, they will not be able to shape outcomes, regardless of confidence. They may be users of tools designed by others, but they will not influence how those tools are built or trained.

With this in mind, we cannot expect others to bring everything to us, and we ourselves need to seek out new challenges, even if they are hard and scary. For example, I took 4 months long AI and ML class at MIT, which was truly hard but also so rewarding. 

The problem lies not only at the individual level, but also in the corporate environment. We all know that diverse teams build better systems. When only part of the population shapes AI, blind spots multiply, and bias becomes harder to detect and easier to scale.

The responsibility lies across the board

Companies cannot treat these gaps as a pipeline problem alone. They need to be responsible for the environments they create. Equal opportunity does not happen by accident. It requires deliberate action. It requires investment in skills, transparent progression and leadership that actively challenges outdated narratives about who belongs in technology.

Organisations and education systems must do more to ensure AI literacy at every level, age and gender as it redefines our workforce. Not everyone needs to become a data scientist overnight – but we need to understand the basics. How are AI models trained? Where does data come from? What limitations exist, and how should outputs be questioned?

At Yext, our AI literacy programmes are ensuring no one is excluded from benefiting from AI. The programmes cover every level, as well as specific approaches to reimagine operating models and workflows and drive deeper transformation. We see this as a responsibility, not a nice-to-have initiative or a tick-off exercise. When people are given structured opportunities to learn and experiment, confidence follows.

We need to make girls feel entitled to make bold moves

I am also involved in Girls Who Code and the Georgia Tech Foundation, where 50,000 graduates have now had exposure to working in a start-up by the time they graduate. I believe that girls need to feel entitled to learn these new skills and benefit from systems that allow them to experiment, fail and try again with freedom.

That freedom is critical. Too often, women feel they have to prove competence before they are allowed to explore. In fast-moving fields like AI, exploration is how competence is built. Waiting until you feel fully ready means being left behind.

International Women's Day is an important moment to reflect, but reflection is not enough. If businesses are serious about equality, they need to measure who is using AI tools internally, who is being trained and who is progressing into AI-related roles. They need to ask uncomfortable questions about why gaps exist and act on the answers.

AI is already reshaping our economy, workplaces and daily lives. Women need to get involved in designing, questioning and leading AI solutions.

We have a chance to not repeat the 'male genius' story again with AI. Companies and education systems need to ensure they drive women's skills and literacy in AI with innovative programmes that support them.

The future of AI should not belong to those who were simply given more leeway to fail. It should belong to everyone willing to learn, experiment and contribute.