Technology
Could AI support expansion of nurse roles?
A major Cochrane review has found that nurses can safely and effectively deliver many aspects of hospital care traditionally provided by doctors. Tim Morris and Greta Westwood CBE PhD RN discuss how the nursing workforce could prepare for expanded roles with blended learning and AI-informed decision-making.
Working closely with nurse leaders and their frontline teams, we see firsthand the sustained pressure facing healthcare systems, driven by rising clinical complexity, higher patient acuity and persistent workforce shortages. As a result, nurses are increasingly being asked to extend their already wide-ranging roles, taking on responsibilities previously reserved for doctors. Evidence suggests this shift is not only necessary, but clinically appropriate. A major Cochrane review drawing on data from 82 studies and more than 28,000 patients across 20 countries found that nurses can safely and effectively deliver many aspects of hospital care traditionally provided by doctors. In some settings, nurse-led care was associated with outcomes that exceeded those achieved through doctor-led models.1 An expanded scope of practice is only one
part of the challenge. The nature of clinical work itself is changing. Care delivery is becoming more digitally integrated, with growing volumes of data, new decision-support tools and increasing expectations around documentation, reporting and standardisation. Nurses are required not only to develop new clinical skills, but also to work confidently with digital systems that shape day-to-day decision-making and workflow. The implication for nurse leaders and policy
makers supporting the nursing workforce is clear. Preparing nurses for these expanded roles requires learning approaches that are responsive, practical and embedded in real clinical contexts. Traditional, one-off training models are unlikely to be sufficient on their own. It is critical that we assess how digital eLearning and AI-enabled clinical decision support can play a meaningful role in helping nurses adapt to modern care environments. Used together,
these approaches can provide a practical safety net, supporting consistent, evidence-based decision making, while helping services to scale nurse-led care safely and sustainably across diverse clinical settings.
The case for strengthening workforce capability As nurse-led models of care continue to expand, the capability of the nursing workforce becomes a critical enabler of safe and effective service delivery. Nursing has always demanded resilience, professional judgement and a commitment to lifelong learning, but in today’s clinical environment, those attributes are under increasing pressure. Workflows are more intense, staffing gaps persist, and
Nurses increasingly need learning models that are flexible, evidence-based and accessible when and where they are needed.
expectations around clinical autonomy and accountability are rising. The ability to apply sound clinical judgement and keep pace with evolving standards of care has never been more important. At the same time, we are acutely aware that the conditions under which nurses are expected to learn have become more challenging. Protected time for development is limited, shift patterns are often irregular, and traditional classroom-based training can be difficult to access or sustain. Without new approaches to education, there is a risk that the pace of clinical and technological innovation will outstrip the confidence and preparedness of frontline teams. Strengthening workforce capability, therefore, requires a shift in how education and development are delivered. Nurses increasingly need learning models that are flexible, evidence- based and accessible when and where they are needed. Educational approaches must reflect the realities of modern practice, supporting incremental learning, reinforcing clinical
June 2026 I
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