According to a new report from the Deloitte Centre for Technology, Media, and Telecommunications, the percentage of women using generative AI has tripled year-over-year, from just 11% in 2022 to 33% in 2023. Although men still lead in adoption, with 44% using the technology this year, the gap is closing.

By the end of 2024, women in the U.S. are expected to match or pass men in AI usage, with Europe following within two years. Despite these gains, disparities remain in daily usage, with 34%  of women using generative AI daily compared to 43% of men.
However, women in tech roles are kicking the trend, with 44% using generative AI for tasks, compared to 33% of men, and showing no significant gap compared to their male counterparts.
Scepticism about data security and bias remains a hurdle for many women with only 18% trusting AI companies to safeguard their data, compared to 31% of men. This hesitation is compounded by concerns about implicit bias, as women make up less than one-third of the AI workforce. Many professionals believe that biased outcomes will persist until the field becomes more gender-diverse.

Antonia Walt, Chief for Client Experience at AND Digital said: “Women are redefining the tech landscape by embracing generative AI and shattering outdated stereotypes about tech adoption. Women love tech and 89% love being a tech leader and thrive in the fast-paced, innovative environment that continues to grow. Women bring unique perspectives to the AI space, which are essential for developing technologies that are fair and impactful for everyone. By investing in diverse representation and fostering trust, businesses not only empower women but also unlock the full transformative potential of AI.”

Sheila Flavell CBE, COO of FDM Group said: “Promising to see the gender gap in AI use narrowing, as AI has the potential to level the gender playing field in technology and close the gap. Equipping women with the necessary skills related to AI, such as data and analytics, will enable them to be at the forefront of innovation where they can lead the creation of a reliable and trustworthy ecosystem that boosts productivity for businesses. The research also highlights an important underlying issue: trust. Concerns over AIs handling of data privacy and the biases in AI models reflect a broader need for improved transparency and inclusivity in technology. AI’s effectiveness is closely tied to the quality of data it processes, which underscores the importance of training employees in data quality management and analysis. Addressing these trust gaps will be key to ensuring sustained, widespread use of these technologies in today’s evolving tech landscape.”