Women are using artificial intelligence at lower rates than men. Most recent research, by Haas School of Business / UC Berkeley, places the difference between 20 to 25 percent. The disparity is real, but it varies depending on how and where AI use is measured.
In professional environments, the gap is most visible. Surveys consistently show that women are less likely to use AI tools in the workplace, particularly in fields where these technologies are rapidly advancing. Tools such as chatbots, coding assistants, and automated analytics platforms are more commonly adopted in industries like technology, finance, and engineering, where men remain overrepresented. This imbalance in job roles plays a significant part in shaping overall usage patterns.
Outside of work, the difference becomes less pronounced. With the rise of widely accessible AI tools, especially conversational platforms, adoption rates among women have increased significantly. In some cases, usage is now approaching parity with men, suggesting that ease of access and everyday relevance are key factors in closing the gap.
Several underlying causes help explain why the divide still exists. Occupational distribution remains one of the strongest influences, as men are more likely to be in roles where AI is integrated into daily tasks. Confidence and trust also play a role. Research indicates that women tend to express greater caution about AI, including concerns about reliability, ethical implications, and long term impact on jobs.
Workplace dynamics further reinforce the trend. Women often report receiving less encouragement to experiment with emerging technologies, and in some cases, less recognition when they do. In environments where adopting AI is informal or self driven, this lack of support can slow uptake. “If we’re not in the room, then we don’t get represented, and AI learns from us…” comments Seema Victory, Head of Memberships at UNTIL.
Despite these challenges, the gap is already beginning to shrink. As AI becomes more embedded in everyday tools and workflows across a wider range of industries, adoption is spreading more evenly. The current difference is not fixed, and trends suggest it will continue to narrow as access, familiarity, and workplace support improve.