AI Automation and Women’s Jobs UK: Which Roles Are at Risk?

How artificial intelligence and automation will affect women’s jobs in the UK is one of the most urgent workforce questions facing the country this year. As of early 2026, the conversation has shifted. It is no longer about whether artificial intelligence will change work. It is about which workers will feel the change first, and how sharply. For women running businesses, building careers or thinking about returning to employment, the pattern of risk is not neutral. It tracks existing inequalities: part-time work, caring responsibilities, occupational segregation and gaps in access to technical training. This article pieces together the latest UK data and names the sources. It argues that the real danger is not a sudden wave of redundancies. Instead, it is a slower, more corrosive divide between women who learn to work with AI and women whose tasks simply lose value.

The headline figure: why automation is not just a tech story for women’s jobs

When analysts talk about automation and women’s jobs in the UK, they usually start with the headline number. In 2024, the Institute for Public Policy Research warned that up to eight million UK jobs could face exposure to automation if current trends accelerate without government intervention (IPPR, 2024). The report found that back-office, entry-level and part-time roles faced the highest exposure, and that women would feel the impact more sharply than men. Existing generative AI could already perform eleven per cent of tasks. That share rises to fifty-nine per cent if companies integrate AI more deeply into their workflows.

Those figures are projections, not predictions. They describe exposure, which means tasks that AI could perform, not tasks it will perform tomorrow. Even so, the direction of travel matters. The Department for Science, Innovation and Technology published its own assessment in January 2025, “Assessment of AI capabilities and the impact on the UK labour market” (DSIT, 2025). It concluded that AI is likely to reshape labour demand rather than simply replace workers. A companion report, “AI Skills for Life and Work,” used the Working Futures model to look ahead to 2035. It stressed that the outcomes depend heavily on policy choices around skills, infrastructure and regulation.

The older but still granular baseline comes from the Office for National Statistics. Its 2019 analysis found that automation threatened around 1.5 million jobs in England, equivalent to 7.4 per cent of all jobs (ONS, 2019). The ONS also found that women, young workers and part-time workers were more likely to hold roles at high risk. That pattern has not gone away. Generative AI may widen it further, because it makes it cheaper to automate the communication, scheduling, record-keeping and customer-contact tasks that employ large numbers of women.

Which roles face the highest exposure

Three overlapping pressures shape the risk for women in the UK: the concentration of women in routine administrative and service roles; the rise of tools that can write, code, schedule and summarise; and the uneven distribution of AI skills across the workforce. To understand the risk in practical terms, look at where women actually work.

The ONS 2019 study listed the occupations most likely to see tasks automated. Many are either female-dominated or have a substantial female workforce. They include waiters and waitresses, shelf fillers, elementary administrative occupations, finance administrators, payroll managers, bank and post office clerks, receptionists, customer service occupations, bookkeepers, human resources administrative roles, and secretarial and typing work. The common thread is not low intelligence or low effort. It is that the tasks are rule-based, repetitive, text-heavy or transaction-based. That is exactly where large language models and workflow automation have improved fastest.

Source: ONS, 2019.

The risk also varies by region. Areas with a higher share of administrative, retail and customer service employment will feel the pressure earlier. That includes parts of the Midlands, the North of England and coastal towns. Economies dominated by specialised professional services or advanced manufacturing will feel it later. For women who run regional businesses, this is both a workforce issue and a customer issue: if local disposable income comes under pressure, demand shifts.

Commentators sometimes present finance and technology as safer ground. They are not. Research by PwC and the IPPR has found that women in tech and financial services face greater exposure to AI-driven change than their male peers (PwC, 2025; IPPR, 2024). The reason is structural. Women in those sectors are more likely to be in mid-level, operational or support roles that sit close to automated processes. Men are more likely to occupy senior engineering, architecture or deal-making positions that are harder to replicate. The same pattern appears in law, accountancy and consultancy. Junior associates and paralegals there face pressure from document review and drafting tools.

Part-time, returning and older workers: the hidden face of the risk

The risk profile changes sharply once you add hours and age. According to IPPR, part-time jobs are disproportionately exposed because they cluster in retail, hospitality, administration and customer service (IPPR, 2024). Women make up the majority of part-time workers in the UK, and many of those jobs were already precarious before AI arrived. Automated scheduling, self-service checkouts, AI phone systems and customer relationship management tools could give employers another reason to reduce headcount or reshape rosters.

For women returning after maternity leave or a career break, the picture is mixed. On one hand, AI tools can make flexible and remote work more viable. They automate routine tasks and allow people to focus on judgement, client relationships and creative problem-solving. Our guide on career returner women UK sets out how some women are using that flexibility to restart on their own terms. On the other hand, entry-level and administrative roles often serve as stepping stones back into work. If employers thin these out first, the route back becomes steeper.

Watch older women too. ONS data have shown strong growth in self-employment among women over fifty, partly as a response to ageism and inflexible employment (ONS, 2023). AI could help some of those women run leaner businesses. It could also undercut service-based micro-businesses by lowering the cost of the bookkeeping, marketing, virtual assistance and admin support they sell. The women who build businesses around these tasks may find themselves competing with AI-assisted platforms that charge a fraction of the hourly rate.

The wage paradox

While one stream of data warns about displacement, another shows that automation can also deliver a wage premium for women with the right skills. PwC’s 2025 AI Jobs Barometer found that demand for AI-skilled workers in the UK had rebounded sharply. Postings for specialist AI roles rose by 61 per cent in a single year, from 112,000 to 180,000 between 2024 and 2025. The wage premium for workers with AI skills tripled, from 11 per cent in 2024 to 34.2 per cent in 2025 (PwC, 2025).

That creates a two-track labour market. On one track, women in routine roles face downward pressure on hours, pay and security. On the other track, women who can combine domain expertise with AI literacy command a significant premium. The risk is not that AI destroys all women’s jobs. It is that AI polarises the female workforce into those it augments and those it undercuts. PwC itself frames this as “AI is creating winners, not just efficiencies.” It notes that companies most able to use AI are expanding hiring faster than their peers. They are placing greater emphasis on human skills such as judgement, creativity and leadership.

The gap is partly about access to training. Our earlier coverage of the AI gender gap among women entrepreneurs found that women were adopting AI quickly for shallow tasks such as content drafting and scheduling. They were falling behind on deeper integration such as custom workflows, data analysis and AI-driven product development. Employees face a similar gap. Employers who do not train or encourage women to use AI tools at work may leave them slower, more expensive or less visible than colleagues who do.

Government policy and the response

So far, the policy response has been more diagnostic than decisive. The DSIT assessment published in January 2025 was a welcome evidence base, but it did not come with new funding or binding obligations on employers. The “AI Skills for Life and Work” report set out long-term projections. It stressed the importance of adult learning, apprenticeships and technical education. Existing programmes such as Skills Bootcamps, Free Courses for Jobs and the apprenticeship levy are the main vehicles, but take-up among women returning to work or in part-time roles remains uneven.

The Employment Rights Bill, introduced in 2024 and expected to take effect from 2026, matters here (UK Government, 2024). It gives employees stronger rights to request flexible working from day one. It also introduces new protections around predictable hours and redundancy during pregnancy and maternity. Those rights are not directly about AI, but they shape who can stay in the labour market while adapting to technological change. Our article on flexible working rights UK 2026 explains the practical implications for women.

The National Living Wage, at £12.21 an hour from April 2025, adds another layer (Low Pay Commission/GOV.UK, 2025). As automation becomes cheaper, some employers may prefer to invest in technology rather than pay higher wages for routine tasks. That is not an argument against the wage floor. It is a reminder that the minimum wage and automation interact most intensely in sectors such as retail, hospitality and care, where women are strongly represented. Policymakers need to ensure that wage policy and skills policy are pulling in the same direction.

The contrarian view: is this about displacement or polarisation?

Not everyone reads the data on automation and women’s jobs in the UK as a story of net job loss. The contrarian argument, backed by PwC’s 2025 analysis, is that AI is augmenting work more than replacing it in the short term. Companies that integrate AI most deeply are often the same companies that are expanding headcount fastest. The technology raises productivity and creates demand for new services. The historical pattern with previous waves of automation is that productivity gains eventually create new jobs, even if the transition is painful.

In this reading, the real risk is not wholesale replacement but a widening gap between the AI-enabled and the AI-excluded. Women who can use AI to amplify their expertise will do well. Women whose employers fully automate their tasks, and who lack the support to retrain, will face the squeeze. The policy challenge is therefore not to stop AI but to manage the transition: better careers advice, funded retraining, portable qualifications and support for women moving from shrinking occupations to growing ones.

There is also a sectoral counterpoint. Healthcare, social care, education and early-years provision employ millions of women. These roles are hard to automate fully because they rely on human presence, empathy and trust. AI may change how organisations structure those jobs, but they will still need people. The question for women in those sectors is whether AI will reduce workload and improve pay. Or will it simply demand more output from fewer staff?

What businesswomen should do now

Anyone running a business needs to track these trends because they affect costs, talent and competitive positioning. For founders, the practical starting point is to audit which tasks add value and which ones are commoditising. If your business sells time-based services that large language models can now reproduce, you need a plan. That might mean moving upmarket or specialising in judgement and client relationships. It could also mean embedding AI into your own delivery to improve margins. Our guide to the best AI tools for UK small businesses covers the current options.

For employees, the shift demands a deliberate skills strategy. The PwC data is clear: AI skills carry a wage premium and open doors. That does not mean everyone needs to become a machine-learning engineer. It means becoming the person in your team who knows how to prompt effectively, verify outputs, integrate AI into workflows and spot errors. It means leaning into the human skills that AI cannot replicate: complex judgement, emotional intelligence, negotiation, ethical reasoning and creative leadership.

For women thinking about starting a business, the disruption also creates openings. AI tends to automate the low-value, repetitive parts of a job. The higher-value parts can become the foundation of a consultancy or freelance practice. These include strategy, client advisory, community building and bespoke problem-solving. Our page on setting up a business today sets out the first steps. The women who thrive will be those who treat AI as a co-pilot, not a competitor.

The bottom line: treat AI as a skill layer, not a storm cloud

The impact of AI on women’s jobs in the UK is not a single trend but a mirror held up to the labour market. It reflects where women already work, how employers structure their hours, who has access to training and which skills employers value. The most useful response is to treat AI as a skill layer that will gradually separate the augmented from the automated. That separation is not inevitable; it depends on choices employers, educators and policymakers make.

The evidence as of early 2026 points to three priorities. First, women in high-exposure occupations need affordable, practical routes into AI-augmented roles, not abstract digital literacy courses. Second, employers should redesign jobs around the tasks that remain genuinely human, rather than using AI simply to speed up the same old workflows. Third, government should join up its AI skills strategy with its wider agenda on flexible working, childcare, adult education and regional growth.

This is why the impact of AI and automation on women’s jobs in the UK matters for the economy as a whole. Women make up around half the workforce and an increasing share of business founders (ONS, 2024). If the transition leaves them on the wrong side of an AI-driven divide, the UK loses talent, income and growth. If policymakers support them through the transition, AI becomes an opportunity to close old inequalities rather than deepen them.

For more data on women in the UK economy, visit our women in business facts page.