The first time a venture fund mistook me for an executive assistant to a male co-founder, I laughed. The second time it happened, I explained matter-of-factly, “I'm actually the CEO.” By the third time, I began to wonder why the tech industry at large couldn't grasp the idea of a female executive in generative AI.
While it may be easy to scapegoat the so-called “pipeline problem” and claim that there aren't enough women making it through the maze of academia and industry, the percentage of women pursuing careers in artificial intelligence is pretty similar to the overall trend in STEM. In other words, women appear to be just as underrepresented in AI as they are in other STEM fields.
As an AI founder myself, I meet and work with women every day who run AI/machine learning (ML) labs, adopt generative AI tools in their companies, and consider the ethical implications of this new technology. I can easily point to women in pivotal roles across the AI sector, such as Mira Murati at OpenAI and Fei-Fei Li at Stanford. Yet women are conspicuously absent from recent lists honoring AI leaders. Women can be the compelling voices of AI assistants, but not the figurative voices of the AI industry. So where is the disconnect?
New Industry, Same Voice
Gen AI only went mainstream with the launch of ChatGPT in 2022. Since then, the pace of innovation has been unprecedented.
In the face of such uncertainty, there is a natural tendency to follow someone who claims to know the way forward, and that has always meant traditional technology CEOs with big megaphones. Sam Altman, Satya Nadella, Elon Musk, and others have no graduate degrees or deep experience in AI engineering, but they have the credibility that comes from having already led respected technology companies. New leaders who will become more influential with the rise of generative AI (such as Demis Hassabis of Google's DeepMind and Dario Amodei of Anthropic) also gained recognition through traditional resumes in academia and big tech, the same paths that have long been hostile and closed to women. In the case of AI, the underlying technology may be new, but the imbalance in gender power relations is not.
Front-end vs. deep tech
The AI boom has been primarily focused on research-oriented, science-heavy solutions like Large Scale Language Models (LLMs). Organizations like OpenAI and Anthropic have delivered models that can ingest more data, be more human-like, and respond faster and more accurately. The AI hype cycle has followed these (male-led) companies avidly.
Yet it's women who lead the industries that actually need to adopt and develop AI applications, such as education, customer service, and human resources. These practical implementations have notably not received as much attention. This perception gap highlights a broader trend: scientific breakthroughs get a lot of attention, but the real-world applications of these technologies often get less respect. Female entrepreneurs like Bumble's Whitney Wolfe Herd and Canva's Melanie Perkins have demonstrated the immense value of user-centric technology applications, yet they aren't celebrated as technical visionaries alongside their male colleagues with deep STEM knowledge. A similar pattern is playing out with AI.
The “rules of friendship” in AI business
Regulations and laws have not kept pace with advances in artificial intelligence. While AI presents endless ethical considerations, there is a potential gold mine waiting for successful AI innovators, and the business practices adopted by many of the new generation of AI companies have a Wild West feel to them. This “ask for forgiveness, not permission” mentality brings to mind some of the most egregious stereotypes of “tech bros” that have persisted in the industry for decades and continue to make AI, like other tech fields, a hostile place for women.
The good news is that with new frontiers comes an opportunity to make new rules. We don’t have to stick to old power norms. The AI revolution gives us an opportunity to bring in new leaders to drive the industry forward:
Make room for new voices: In uncertain times, it’s comforting to lean on familiar leaders. By doing so, we miss this critical opportunity to develop new experts in the early days of AI. Focus on users, not just developers: 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. Don’t encourage a “move fast and break things” approach (even Facebook stopped listing this as a core value years ago) or create a new breed of tech bros with the rapid pace of AI innovation.
We are in the early stages of making history in tech. Don’t miss this opportunity to create new leaders and influencers across genders. And at the very least, don’t assume that a female CEO will be an executive assistant.
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