Somewhere Between Daycare Drop-Offs
and Strategy Sessions

I became an AI founder somewhere between the daycare gate and a strategy session, and I am aware that I am not who most people picture when they think of someone building in this space.

I am a mum. I am nearly middle age. I came back to my career after two years away, and I rebuilt it around something I genuinely believe in. And for a long time, I quietly assumed that backstory made me an exception, something to explain or contextualise before getting to the real conversation.

I don't think that anymore. I think it says something about what we still expect builders of technology to look like, and what we lose when those expectations go unexamined. This is a piece about women in AI leadership, and why the question of who builds AI is not a secondary issue.

The numbers behind women in AI

The data is hard to ignore. Women make up just 26.7% of the global tech workforce, and the picture becomes significantly starker when you look at AI specifically, where women hold only 22% of roles and just 12% of research positions globally. At leadership level, women hold roughly 29% of C-suite roles in tech and only 16% of CTO positions. And McKinsey and LeanIn's most recent research shows the steepest drop-off happens not at the entry point but on the way to management, where for every 100 men promoted, only 87 women make the same step.

This isn't a participation problem. It's a structural one.

And it isn't just about who's missing. It's about where they go. Industry data consistently shows that half of all women who enter tech have left the field by 35, not because they couldn't get in, but because the conditions for staying and growing simply weren't there. Talent is not missing from this industry. It is being filtered out over time, and that filtering shapes everything built above it, including the AI systems increasingly shaping all of our lives.

Women in AI: a different entry point

My own path into AI had no linear entry point. There were daycare runs and interruptions and long stretches of rebuilding identity in fragments of time that most career narratives don't account for or celebrate. But somewhere in that process, I stopped asking whether I fit the image of a tech founder and started paying closer attention to what I was actually building, and why that mattered.

The technology sector has long operated with an unspoken assumption: that innovation comes from a narrow and predictable profile. Young, uninterrupted, highly technical, linear. But AI is beginning to expose the limits of that assumption in ways that are hard to overlook. Because when the people designing and building these systems don't reflect the diversity of the world those systems operate in, something important is lost. Not just representation, but perspective. And perspective determines what gets identified as a problem in the first place.

Diverse founders build better AI

This isn't about symbolism or making the industry look more palatable in a brochure. The deeper issue is one of structural quality. AI systems aren't neutral. They reflect the assumptions, incentives and blind spots of the people who build them, and when those builders are drawn from a narrow segment of society, the systems they produce inherit that narrowness, often in ways that only become visible once they're deployed at scale and affecting real people's lives.

At hum[ai]n, this is precisely why we believe the human side of AI matters as much as the technical side. The work we do is grounded in the conviction that who builds AI, and who is included in those conversations, is not a secondary question. It's the primary one.

A different kind of builder is already here

I don't believe the future of AI will be defined by those who arrived first or who fit the archetype most naturally. I believe it will be defined by those who ask better questions. And increasingly, those questions are coming from people building alongside other responsibilities, entering industries later, bringing experience that sits well outside the dominant narrative of tech.

People like me. Somewhere between the daycare drop-off and the strategy session.

If AI is going to shape the systems we all rely on, and it will, then the question is no longer whether diverse voices should be part of building it. It's whether we can afford for them not to be.