The evolving landscape of AI adoption: a generational and gender divide

Our research reveals a complex picture of AI adoption in the UK, marked by both potential and challenges. Younger generations, particularly Gen Z and Millennials, are embracing AI more readily, recognising its potential to enhance their work. This is reflected in the data: while 46% of Gen Z and Millennials use AI daily or weekly, only 24% of Baby Boomers do the same. This generational gap highlights a need for targeted training initiatives that address the specific needs of older workers and bridge the skills divide.

Bridging this gap requires more than just technical training. It necessitates a shift in mindset, encouraging older generations to see AI not as a threat, but as a tool to enhance their skills and productivity. Organisations can achieve this by creating a supportive environment where older workers feel comfortable exploring AI, receiving personalised training, and having access to ongoing support.

Furthermore, men are significantly more likely than women to use AI regularly for work-related tasks. This disparity is evident across various AI applications:

Non-administrative tasks: Over half (53%) of respondents reported using AI to complete non-administrative tasks more quickly, such as creating content, writing emails, or making decisions. Men are more likely to use AI in this way (53% vs. 41% of women).
Admin support: 42% of respondents used AI for administrative tasks, including taking notes, filling in timesheets, scheduling meetings, or data analysis. Again, men are more likely to utilise AI for these tasks (49% vs. 36% of women).
Problem-solving: Nearly half of respondents (48%) have used AI to problem-solve at work, with men more likely to use AI for this purpose (48% vs. 36% of women).

These disparities underscore the urgent need to address the underrepresentation of women in the AI workforce. Proactive interventions that focus on increasing women's access to AI training and development opportunities, fostering confidence and leadership in the field, are crucial to ensuring a more equitable future. This might involve targeted mentoring programmes for women pursuing AI education, and initiatives that encourage them to explore careers where utilising AI is more common.

Balancing innovation and equity

While 48% of respondents believe AI can be used to enhance equity in the workplace, reducing bias in recruitment and providing personalised learning and development programmes, concerns remain about potential bias and the need for a human-led approach alongside AI.

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