Gender Gap in Tech Adoption

When a new technical tool comes onto the market, not everyone reaches for it at the same pace. Some try it out right away, others only years later or never at all. If you count who belongs to which group, a pattern regularly emerges: men use new technology more often and earlier than women. This gap is called the Gender Gap in Tech Adoption, meaning the gender gap in the uptake of technology. It is usually measured as the difference in usage rates in percentage points. If, for example, 60 percent of men and 40 percent of women say they regularly use a program, the gap is 20 percentage points.

What the gap costs with AI tools

With earlier waves of technology, the gap was often a matter of convenience. With AI programs that write texts, generate code, or summarize data, it is a matter of working time. Those who master such tools complete certain tasks in a fraction of the time. Those who don’t use them don’t necessarily work worse, but they work slower. Over the years, this turns into a difference in promotions and pay.

Several large surveys from 2023 to 2025 found gaps of around 10 to 25 percentage points for tools like ChatGPT. This holds true even within the same profession and the same age group. So the gap cannot be explained solely by the fact that women and men have different jobs. For companies, this is a practical problem: software that only half the workforce uses only delivers half the productivity.

There is also a feedback loop. AI models learn from what people input and how they rate responses. If a group uses the systems less often, its questions and feedback are incorporated less. The tools then become better suited to the needs of the heavy-user group. This can further reinforce the original gap.

Where the gap comes from

The most important factor is not ability, but confidence. In studies, women rate their own tech skills lower on average than men, even though tests show no difference in performance. Those who feel uncertain try out an unfinished tool less often. But that is exactly what new AI programs demand: experimenting around without knowing what will come out.

Added to this is the fear of being accused of cheating. Surveys at universities and in offices show that women are more likely to fear that AI use could be seen as fraud or a sign of laziness. As long as it is unclear within a team what is allowed, they tend to hold back more. Men use the tools in this gray area more often anyway.

A third point is time. Unpaid work such as housework and childcare is unevenly distributed in many countries. Those who have fewer free hours in the evening spend them less often exploring a new program. It is important to distinguish this from the Digital Divide: that concept is about lacking access to devices and the internet. With the Gender Gap in Tech Adoption, access is usually available, but usage is still lacking.

Where the figure shows up in the news

You’ll most often come across the term in quarterly reports from software companies and in studies by institutions such as the OECD or the World Economic Forum. There it might state, for example, what percentage of an AI assistant’s users are women. Application statistics for computer science degree programs are also often cited in this context. As an investor or reader, you can read such figures as an indication of whether a product is actually reaching its potential audience.

In companies, the gap becomes concrete in training programs. Companies that only offer AI use on a voluntary basis usually end up with a skewed distribution. Companies that set clear rules and train all teams at the same time report significantly smaller differences. Clear directives work better here than appeals.

A common misconception is that the gap will disappear on its own with the younger generation. That was indeed the case with mobile phones and social networks. With AI tools, however, studies find the gap even among schoolchildren and students. So pay less attention to who knows a tool, and more to who uses it daily for real tasks.