The evidence base for the study consists of individual interviews with 18 nurses and physicians, conducted between March and May 2020, precisely the window in which the pandemic first disrupted routine Swedish healthcare. The timing matters scientifically. Because the interviews took place while the crisis was unfolding rather than in retrospect, the data capture workers’ sensemaking in something close to real time, before memory had been smoothed by hindsight or by later knowledge about the virus. The researchers analysed the interview material using reflexive thematic analysis, a qualitative method in which researchers systematically code the data and iteratively develop themes, while remaining explicitly aware of how their own perspectives shape interpretation. Rather than testing predefined hypotheses, the approach allowed patterns of meaning to emerge from the accounts themselves.

The analysis revealed an overarching pattern: sensemaking operated as a way of holding clinical practice together throughout uncertainty. This pattern unfolded across three mutually interrelated levels. At the organisational level, sensemaking was anchored in how organisational structures contributed to stability in the organisation of work. In other words, formal frameworks, routines and directives were not merely administrative apparatus; they provided interpretive anchors that helped workers understand what was expected of them when the situation itself offered no clear script. The authors emphasise that clear organisational directives are important for fostering a shared understanding of how uncertain situations should be interpreted and managed in practice, a finding with direct implications for crisis planning in health systems.

The interpersonal level of sensemaking captured something equally vital: the understanding of uncertain circumstances was grounded in a collective understanding, in which healthcare workers reflected together and in relation to others. Confronted with questions that no individual could answer alone, such as how the disease presented, how it spread and how care should be reorganised, workers turned to colleagues as interpretive partners. Through conversation and shared reflection, tentative individual impressions were tested, refined and converted into workable collective understandings. The study’s implications section underscores this point, noting that healthcare workers need opportunities and time for interaction with colleagues, enabling them to collectively construct meaning and maintain a sense of stability when managing uncertainty. In crisis conditions, social interaction is not a luxury; it is a cognitive infrastructure.

The third level, the individual, captured healthcare workers’ capability and commitment to continuing to provide care despite uncertain circumstances. Even as guidelines shifted and knowledge about the virus remained fragmentary, individual clinicians drew on their professional knowledge, accumulated experience and personal sense of responsibility to sustain care. The researchers argue that it is important for healthcare organisations to acknowledge workers’ individual knowledge, experiences and capability to sustain clinical practice under such conditions. This finding reframes resilience during the pandemic not simply as endurance or sacrifice, but as an active interpretive achievement: clinicians continuously constructed workable courses of action from incomplete and evolving information.

From a theoretical standpoint, the study demonstrates the analytical value of treating sensemaking as a multilevel phenomenon rather than a purely individual psychological process. The three levels described in the findings are characterised as different but mutually interrelated, meaning that organisational structures, collegial reflection and individual commitment reinforced one another. Clear directives from above gave workers a common interpretive frame; collegial interaction allowed that frame to be adapted to local clinical realities; and individual competence enabled the frame to be enacted at the bedside. Disrupting any one of these levels, the analysis implies, could destabilise the whole system of meaning on which crisis response depended.

The practical implications for health services research and management are considerable. The authors state that sensemaking at organisational, interpersonal and individual levels should be an important consideration for healthcare organisations when facing future crises or other uncertain events. For planners, this suggests that pandemic preparedness should include not only material resources such as protective equipment and ventilator capacity, but also communicative and structural resources: unambiguous directives that reduce interpretive ambiguity, and protected time and space for colleagues to talk through evolving situations together. The finding is especially relevant for health systems that operate under high autonomy and decentralised decision-making, where the translation of national guidance into local practice depends heavily on collective interpretation.

The study also contributes methodologically to the literature on healthcare work during COVID-19. By interviewing nurses and physicians across the early weeks of the pandemic and applying reflexive thematic analysis, the researchers produced a thematically organised account of the work situation that complements quantitative studies of infection rates, staffing and burnout. The focus on sensemaking, a concept with roots in organisational sociology and qualitative psychology, connects the Swedish experience to a broader research conversation about how organisations and professions cope with radical uncertainty, a conversation that spans crisis management, organisational climate and the sociology of work.

The research was carried out at the Department of Health Sciences at Mid Sweden University, with open access funding provided by the university and financial support from AFA Försäkring, the Swedish collective agreement insurance provider, under grant number 200126. The authors report no competing interests. In line with the recommendations of the Internal Review Board at Mid Sweden University, the study, which focused on experiences and perceptions of the working situation rather than sensitive personal information, was not subject to the regulations of the Swedish Research Ethics Act. Participants received written information about the study’s purpose and their right to withdraw at any time, gave oral consent documented in the audio recordings, and were assured confidentiality, with data handled in accordance with GDPR and stored on a secure university server with restricted access, in compliance with the Helsinki Declaration.

As health systems worldwide continue to digest the lessons of COVID-19, this study offers a deceptively quiet insight with far-reaching consequences. The capacity of healthcare organisations to withstand crises may depend less on heroic individual effort than on the quality of the interpretive environment in which clinicians work: how clearly directives are communicated, how freely colleagues can reflect together, and how genuinely their individual expertise is recognised. Sensemaking, the Swedish findings suggest, is not an abstract academic construct but the everyday mechanism by which clinical practice survived the pandemic’s most confusing weeks, and a resource that future crisis preparedness would be unwise to overlook.

Subject of Research: Sensemaking among Swedish healthcare workers during the early weeks of the COVID-19 pandemic

Article Title: How Swedish healthcare workers managed the early weeks of the COVID-19 pandemic: sensemaking across organisational, interpersonal and individual levels

Article References: Månsson Sandberg, H., Jong, M., Jong, M. C., & Wall, E. (2026). How Swedish healthcare workers managed the early weeks of the COVID-19 pandemic: sensemaking across organisational, interpersonal and individual levels. BMC Health Services Research. https://doi.org/10.1186/s12913-026-15826-y

Image Credits: AI Generated

DOI: 10.1186/s12913-026-15826-y

Keywords: COVID-19, sensemaking, healthcare workers, nurses, physicians, pandemic, crisis management, organisational behaviour, qualitative research, thematic analysis, health services research, Sweden

The research team, comprising Professor Dirk Lindebaum of the University of Bath’s School of Management, Professor Natarajan Balasubramanian of Ohio State University, Dr Mehreen Ashraf of Cardiff University and Dr Patrick Haack of the University of Lausanne, set out to model how the growing presence of generative AI in the workplace interacts with the processes through which managers acquire and refine practical wisdom. Their paper, titled A Process Model of Managerial Phronesis in the Age of Generative AI, argues that the appeal of these systems lies in their speed, but that speed is precisely what makes them risky when they are treated as substitutes for thinking rather than as aids to it.

Professor Lindebaum’s central point is that generative AI, however fluent its outputs may appear, cannot replicate the lessons that come from first-hand experience. Unlike humans, AI does not experience the world, understand the consequences of decisions, or grasp the social and emotional complexities that shape behaviour in workplaces. Instead, it produces responses based on patterns found in existing data. That distinction matters because managerial phronesis is not a body of information that can be retrieved; it is a capability that accumulates through acting, observing outcomes and reflecting on them, often in situations where the right answer depends on context, relationships and moral considerations that no dataset fully captures.

The danger, according to the researchers, is that as managers increasingly outsource their thinking to generative AI, whether for idea generation or when a practical problem arises at work, they may rely less on their own judgement. Over time, this could reduce their ability to learn from experience, think critically, and anticipate what kinds of actions are needed now to meet future goals. The concern is not that AI produces wrong answers in every case, but that the habit of deferring to it weakens the mental muscles that managers need precisely in the situations where AI is least reliable: ambiguous, novel and morally charged decisions.

To describe this dynamic, the team coined the concept of epistemic de-skilling, a process in which people gradually lose knowledge-related capabilities because they outsource too much of their thinking to generative AI. The researchers suggest this is most likely to occur when managers are under intense time pressure and use the technology as a shortcut rather than engaging deeply with a problem themselves. In such situations, managers may stop asking important questions, seeking different perspectives or learning from real-world interactions. Instead of developing a nuanced understanding of employees, customers or organisational challenges, they may come to depend on AI-generated answers that lack the context and moral judgement needed for complex decisions.

The mechanism matters as much as the outcome. Practical wisdom, in the Aristotelian tradition from which the term phronesis derives, is built through the repeated cycle of confronting a concrete situation, judging what is at stake, acting, and reflecting on the results. If the first and most demanding step of that cycle is handed to a machine, the subsequent steps lose their raw material. A manager who no longer wrestles with a problem before consulting an AI system has nothing of their own to test the system’s output against, and the reflective part of the loop collapses into passive acceptance. The study frames this as a process model precisely because the damage is cumulative: each shortcut makes the next one easier, and the capability fades through disuse rather than through any single dramatic failure.

Crucially, the researchers do not conclude that generative AI is inherently corrosive to managerial judgement. They also developed the idea of how the technology may be used to develop the judgement of managers, although they note this is likely to prove more challenging. Generative AI can strengthen managerial judgement when it is used as a tool for reflection rather than a replacement for thinking, a process the researchers dubbed epistemic up-skilling. Rather than accepting AI outputs at face value, managers can use them to challenge assumptions, explore alternative scenarios and test the reasoning behind their own decisions. Because AI systems often struggle to explain why they produce particular answers, the gaps in those explanations can encourage people to think more deeply about their choices and the consequences of their actions.

That up-skilling path, however, demands deliberate effort. Professor Lindebaum emphasised that it requires persistent effort on the part of managers to fill the explanatory gaps that AI leaves behind. The study suggests this beneficial outcome is most likely when managers know they will be held accountable for their decisions. In workplaces where individuals must justify their actions and explain their reasoning, generative AI can become a trigger for deeper reflection instead of a substitute for judgement. As Lindebaum put it, it is that which generative AI cannot satisfactorily explain that managers must explain to themselves and others. Accountability, in this framing, functions as a safeguard: the obligation to give reasons forces the manager back into the reflective cycle that passive reliance on AI would otherwise short-circuit.

The implications for organisations are direct. It is becoming increasingly clear, the researchers argue, that simply introducing AI tools will not automatically improve decision-making or organisational performance. Instead, organisations need to carefully design roles, responsibilities and workflows to ensure employees continue developing the human skills that AI cannot replicate. That design challenge extends to how performance is evaluated and how time pressure is managed, since the study identifies intense time pressure as a key condition under which de-skilling takes hold. Workplaces that reward speed above deliberation may inadvertently push managers toward the shortcut that erodes their judgement, while those that build in reflection and accountability can turn the same tools into instruments of learning.

The study, published in the Academy of Management Review with the DOI 10.5465/amr.2024.0582, arrives at a moment when generative AI is being embedded into professional work faster than the norms governing its use are being established. Its message is neither technophobic nor celebratory. The same system that can hollow out a manager’s capacity for judgement under time pressure and passive reliance can, under conditions of accountability and active reflection, sharpen that capacity by exposing the limits of machine-generated answers. The difference lies not in the technology itself but in how it is woven into the daily practice of management, and in whether organisations treat AI as a replacement for experienced human thinking or as a sparring partner for it.

Subject of Research: The effects of generative AI on managers' practical wisdom and judgement in the workplace

Article Title: AI could undermine managers' judgement unless used carefully, University of Bath-led study warns

Article References: AI could undermine managers' judgement unless used carefully, University of Bath-led study warns. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: generative AI, managerial phronesis, epistemic de-skilling, epistemic up-skilling, managerial judgement, University of Bath, Academy of Management Review, workplace decision-making, accountability, ChatGPT, organisational behaviour, practical wisdom