The hidden inequalities in NHS digital transformation

The rollout of AI within the NHS is likely to create gendered divisions within the workforce, warns Professor Nora Colton, founding director of the UCL Global Business School for Health

When a female clinician returned to work after maternity leave, she found herself struggling with the electronic health record (EHR) system at her organisation on her first day back.

A year away from the clinic meant three software updates she had never seen and new processes she had never used. She was expected to simply work it out as she went along.

This is not a story about poor IT support.

It is a warning about what happens when the NHS rolls out powerful new digital tools without thinking about who will struggle to keep up, and why.

Research based on in-depth interviews with 27 clinical fellows all at the same stage in their careers across two London hospitals shows that the rollout of AI within the NHS is likely to create gendered divisions within the workforce.

The research shows that the way technology is used often impacts female and male clinicians differently, leading to a risk of widening workforce inequalities at a time when the health service is struggling with labour shortages.

Extra layer of vigilance

For women, differences start with how new technology is integrated into daily work. Many described an additional layer of vigilance: checking whether AI-generated diagnoses might be biased or wrong, cross-referencing drug dose recommendations, and reassuring patients when their attention must shift to a screen.

Women often perform this relational ‘screen-side manner’ work instinctively, narrating what the system is doing so patients still feel seen.

Women ask whether they can trust the algorithm. Men ask whether the algorithm is replacing them

Female clinicians’ assumption that vigilance is required is not unfounded. Research often finds that AI systems perform less accurately for women in dermatology, cardiology and critical care, often because training datasets under-represent female bodies.

Precautionary measures mean women can spend more time questioning AI outputs and managing patient rapport, adding to already stretched workloads.

Where women ask whether they can trust the algorithm, men ask whether the algorithm is replacing them. Male clinicians frequently worried that rigid digital systems constrain their professional judgement.

They described creating shortcuts and workarounds to avoid endless clicking, and they feared that overly prescriptive decision-support tools might erode their diagnostic skills.

Many men also raised a different pressure: the way EHR apps and WhatsApp groups extend the working day, with notifications bleeding into evenings and weekends.

The most striking gap we found was around career interruptions, with women raising maternity leave or part-time work as key moments that cause challenges in how they use technology.

With digital systems updating every few months, a year away from clinical work can mean missing interface changes, new safety protocols, and entirely reconfigured pathways.

A year on maternity leave can mean missing interface changes, new safety protocols, and entirely reconfigured pathways

Yet support for returning staff varies wildly. Some NHS trusts offer shadowing weeks, funded refresher courses, and paid catch-up days. Others provide little more than a link to an online tutorial.

A watershed moment

Women moving between hospitals during leave face a lottery. The result: heightened stress, slower work, and in some cases a sense of being digitally ‘out of date’ before they have even restarted.

The NHS needs to create proper support for anyone returning after prolonged time away, whether for maternity leave, research, or illness.

Structured refreshers spread over weeks, not a single overwhelming session, are essential. Digital tools that can be questioned, with clear explanations of their reasoning and data sources, are equally critical so clinicians can trust and challenge outputs when needed.

The NHS could allow digital transformation to amplify existing disadvantages, or it can get ahead of this watershed moment to build fairer systems.

As the NHS reaches a critical junction in the AI revolution, taking the right turn couldn’t be more important.