AI-powered CV screening tools are said to be disproportionately filtering out mid-life women, with London-based companies stopping use of some tools over bias concerns and calls for mandatory regulation growing
BBC News has published an investigation into the impact of AI-powered recruitment tools, specifically CV screening and AI-scored interview systems, on mid-life women seeking to return to employment. The BBC spoke to more than 60 women aged 40 to 65 across a range of industries, most of whom hold or have held senior roles and report high volumes of automated rejections. Stacey Duguid, 52, spent 16 months sending applications with minimal response despite a senior corporate career in fashion; Koeyli Jaluka, 49, applied for 442 jobs and heard back in only a handful of cases; Anna Cowie, 52, has been unemployed for almost four years after a 30-year career in advertising and is currently on jobseeker's allowance. Laura Holden, an AI lawyer and founder of the Bonsai AI legal consultancy, told the BBC that companies often do not understand how AI recruitment tools function, creating potential for significant harm. She described CV scoring tools that grade candidates from A to D and flag career gaps, and argued that although vendors describe these as decision-support tools they frequently operate as automated decision-making systems. Holden called for mandatory testing and stronger regulation before deployment, arguing existing laws were not designed with AI in mind. The City of London Women Pivoting to Digital Taskforce, chaired by Caroline Haines and focused on the financial and professional services sector, estimates that AI and automation could displace hundreds of thousands of women's jobs by 2035, and that without significant retraining investment firms could face over in severance costs. In a survey of over 1,000 women, 68 per cent said they had not been given the opportunity by their employer to retrain or transition into digital roles. The BBC reports that some have already stopped using AI recruitment tools over bias concerns.