I’m a woman working in ‘deep tech.’ Here’s why you don’t see more women in AI (hint: it isn’t a pipeline problem)

The first time a venture fund assumed I was an executive assistant for my male cofounder, I laughed. The second time it happened, I responded with a curt clarification, “I’m actually the CEO.” By the third time, I started to wonder why the broader tech industry seemed unable to process the idea of a female executive in generative AI.

While it might be easy to scapegoat the so-called “pipeline problem,” arguing there simply aren’t enough women making their way through the maze of academia and industry, the percentage of women pursuing careers in artificial intelligence aligns fairly closely to the overall trends in STEM. In other words, women appear to be equally underrepresented in AI as they are in other STEM fields.

As an AI founder myself, I meet and work with women every day who are running AI/machine learning (ML) research labs, adopting generative AI tools in the enterprise, and considering the ethical impacts of this new technology. I can easily point out women in pivotal roles across the AI sector, like OpenAI’s Mira Murati and Stanford’s Fei-Fei Li . Yet, women are conspicuously absent from recent lists celebrating AI leaders. Women can be the flirty voice of your AI assistant , but not the metaphorical voice for the AI industry. So where is the disconnect?

New industry, same voices

Gen AI only entered the mainstream with the launch of ChatGPT in 2022. Since then, the pace of innovation has been unprecedented.

In the face of this uncertainty, there has been a natural inclination to defer to anyone claiming to know the way forward, which has invariably meant traditional tech CEOs with large megaphones. Sam Altman, Satya Nadella, Elon Musk and others lack graduate degrees and deep AI engineering experience, but they have the credibility that comes from already leading respected tech organizations. Even as new leaders have gained influence through the growing prominence of generative AI—among them Demis Hassabis of Google’s DeepMind and Dario Amodei of Anthropic —they’ve earned recognition through traditional resumes in academia and Big Tech, which are the same pathways that have long been hostile and gatekeeping to women. With AI, the underlying technology may be new, but the gender power imbalance is not.

Front end vs. deep tech

The AI frenzy has largely been focused on research-oriented, science-heavy solutions like large-language models (LLMs). Organizations such as OpenAI and Anthropic have been delivering models that can ingest more data, sound more human, and respond with greater speed and accuracy. The AI hype cycle has followed these (male-led) companies with rapt attention.

Yet, women lead the industries that will actually need to adopt and develop AI applications, including education, customer service, and HR. These practical implementations have created decidedly less fanfare. This disparity in recognition highlights a broader trend: While scientific breakthroughs garner significant attention, the real-world applications of these technologies often receive less respect. Female entrepreneurs like Whitney Wolfe Herd of Bumble and Melanie Perkins of Canva have demonstrated the immense value of user-focused technology applications, but are not heralded as technical visionaries alongside deep STEM male peers. Similar patterns are unfolding with AI.

The ‘bro code’ of AI business

Regulation and legislation have not kept up with the pace of artificial intelligence. While there are endless ethical considerations across AI, the potential gold mine awaiting successful AI innovators has yielded a Wild West–like atmosphere in the kinds of business practices many of these new gen AI companies employ. This “ask for forgiveness, not permission” mindset brings to mind some of the most egregious “tech bro” stereotypes that have persisted in the industry for decades and continue to make AI as hostile a place for women as other parts of tech.

Fortunately, with a new frontier comes the opportunity to make new rules. We don’t need to adhere to the old power norms. The AI revolution gives us an opportunity to welcome a new slate of leaders. To move the industry forward:

1. Make room for new voices: In times of uncertainty, it’s comforting to turn to familiar leaders. In doing so, we’re missing this critical window in the early days of AI to uplift new experts.
2. Focus on users, not just builders: You don’t need a PhD in ML to understand how gen AI can improve productivity, efficiency, and other parts of work. Women represent many of the industries best suited for AI transformation and should be leaders in shaping its impact.
3. Don’t reward the “move fast and break things” approach (even Facebook stopped citing this as a core value years ago) or allow the fast pace of AI innovation to create a new kind of tech bro.

We are in the early stages of building tech history. Let’s not pass up this opportunity to create new leaders and influencers across the gender divide. And at least don’t assume the female CEO is the executive assistant.

Read more:

• Why I’m yet another woman leaving the tech industry
• I became the semiconductor industry’s first female CEO after being a broke, single mom in a trailer park. Here’s how I did it
• Women in tech can get out of the mid-career limbo by being themselves—and using this one superpower to get ahead
• Here’s how women in tech can break the bias and be their own advocates

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This story was originally featured on Fortune.com