Are these scenarios so different? The sad truth is—instead of being a democratising tool for women, AI threatens to deepen gender inequality. Women are in roles more likely to be automated, and they’re also upskilling in AI tools less. It’s a double whammy.
If left unchecked, this trend will soon become a crisis, but it’s a tide we can turn. Like many great technological shifts that have come before, AI holds significant promise to help level the playing field for women. It’s possible, but it’s contingent on all of us.
Generative AI is here to stay, but women aren’t using it as much as men
AI is not new. For decades, algorithms have quietly aided industries in prediction, pattern recognition, and data analysis—functions that, while incredibly valuable, aren’t what most of us consider inherently human traits. The advent of generative AI changed that equation dramatically. Instead of simply sorting and predicting, this new wave of AI can create, compose, and design, encroaching on creative and cognitive territories we previously believed were exclusive to humans.
At its best, generative AI has the potential to improve lives. It can be a thought partner and collaborator. It can automate repetitive tasks, freeing up time as a result. At its worst, it sends us in the opposite direction. An analysis by UNC’s Kenan Institute shows 8 out of 10 women in the United States are at high risk of automation in their jobs, compared to 6 out of 10 men. Jobs like administrative support, retail, and customer service—which have higher female representation—are at the forefront of AI-driven disruption. But, despite this, women are using AI less frequently than men.
According to a study published by Oliver Wyman, 71% of men aged 18-24 say they use generative AI weekly, compared with 59% of women of the same age. For older age groups the gap is less stark, but still there, with 59% of men saying they use AI weekly in their jobs, compared to only 51% of women. This matters because job automation won’t happen all at once: roles are more likely to be consolidated than replaced wholesale. The remaining individuals are likely to be ones who can manage the efficiencies afforded by AI.
One reason for the gap may be the need for women to feel they must be over-prepared and over-qualified before stepping into new technologies or roles, whereas men are often encouraged to “learn by doing.” This isn’t just a phenomenon in AI, by the way. Studies have shown women are less likely than men to apply for the same job because they did not want to put themselves out there if they were likely to fail. If you’ve ever dug into the world of cognitive biases, this is something we like to call the Dunning-Kruger effect.
It is also possible that women are less forgiving of the technology. Large Language Models (LLMs) have evolved dramatically since OpenAI‘s ChatGPT reached one million users in five days in 2022, but many had unsatisfying experiences with answers that were clearly wrong in the early days and have since written off these tools.
Finally, it is no secret that women carry the disproportionate burden of unpaid care and household labor. Just look as far as the most recent UK census and you’ll see that men enjoy five more hours of leisure time a week than women. This time poverty makes it harder for women to upskill during non-work hours.
What can we do about it?
As much as I encourage the women around me to experiment with AI tools, large scale change must have the participation of our institutions. First, organisations need to take proactive steps to provide access to mentorship and upskilling opportunities. AI tools are becoming easier to use and more intuitive, but support is crucial in bridging the gap between availability and adoption given women’s relative time poverty.
Second, the application of AI in digital products is another way we can work to level the playing field. For example, scaling personalised expert knowledge to make accessible what was previously only afforded to the wealthy. At Cleo, we’re working on exactly this by bringing personalised financial coaching to the 99%. We can now engage people with their data in ways that were previously dependent on having an expert comb through your financial accounts. The end game is to increase financial literacy and fluency. As UN studies have shown us, when women have more economic power, it raises the wealth of their entire community. This is just one example of how AI can start to level the playing field.
Thirdly, technology firms need to tackle bias in their datasets and headcounts. It’s a mistake to think that AI is unbiased, because it’s generated by a machine. On the contrary, AI inherits the biases found in its training data—data drawn from a world full of stereotypes, prejudices, and systemic inequities. Technology companies need to prioritise the identification and correction of biases, ensuring that AI systems are developed, tested, and deployed in ways that promote fairness and inclusivity. This isn’t just an ethical imperative, it’s a business one. Inclusive AI products are better positioned to serve diverse markets effectively.
The tech industry has long been male-dominated, especially in leadership roles, which impacts everything from funding opportunities to product development decisions. More women need to be involved in the design, development, and governance of AI tools. Encouragingly, as generative AI evolves to become less technical in its use and application, there is an opportunity for these tools to transition from being the domain of the tech elite to a user base diverse not just in gender but in experience.
A democratising force, if we let it be
We’re at an inflection point with AI, which is equal parts exciting and scary. There’s no turning back from the growing impact of AI on our lives and societies, but we have to ask ourselves what we want that impact to look like.
If we work smart, we can create space for women to amplify their voices, streamline workflows, and gain access to opportunities previously out of reach. But realising this promise takes more than just women embracing AI—it hinges on a collective shift in how we train and integrate this technology into our daily lives and work.
Fernanda Dobal is the Product Director of AI & Chat for Cleo.
