Harry Scarbrough

New technologies are equivocal, triggering sensemaking responses from the individuals who encounter them. As an ‘epistemic technology’ AI poses new challenges to the expertise and jurisdictions of professionals. Such challenges may be interpreted quite differently, however, depending on the specialized role identities which develop within the wider professional domain. We explore the sensemaking responses of these intra‐professional groupings to the challenges posed by AI through an empirical study of professionals playing different roles (front‐line, hybrid and field‐level) in the field of radiology within NHS England. We found that these intra‐professional groupings sought to make sense of AI through a triadic view focused on the interplay of professional, client and technology. This sensemaking, arising from different jurisdictional contexts, led individual professionals to perceive that their agency was diminished, complemented or enhanced as a result of the introduction of AI. Our findings contribute to the literature on professions and AI by showing how intra‐professional differences affect sensemaking responses to AI as a jurisdictional contestant.

Digital health solutions have the potential to bring about great improvements in the delivery and quality of services in healthcare systems. In this paper, we draw on the extensive experience of NHS (National Health Service) England to develop a practitioner perspective on the challenges of effectively implementing and sustaining such solutions. We argue that a properly sustainable approach requires a shift in both thinking and practice when it comes to the spread and adoption of such technologies. Our thinking needs to shift from a focus on the technology itself to how we bring about the changes needed to deliver more efficient and effective care for patients. In practical terms, this means focussing on the changes involved to integrate digital health solutions into the delivery of services. In particular, it requires greater attention to the motivations, constraints and specific contexts that influence users and patients. The technical expertise of innovators therefore needs to be complemented by other forms of insight into change processes, including clinical and behavioral insight, process engineering and knowledge management. In this paper, we show how these different pillars of the NHS Sustainable Healthcare approach help to ensure the effective implementation and use of digital solutions. We draw out the implications of this approach for policy-makers in healthcare systems, highlighting the need to give greater attention and resources to the downstream challenges of implementing digital health solutions.

Background: Artificial Intelligence (AI) innovations in radiology offer a potential solution to the increasing demand for imaging tests and the ongoing workforce crisis. Crucial to their adoption is the involvement of different professional groups, namely radiologists and radiographers, who work interdependently but whose perceptions and responses towards AI may differ. We aim to explore the knowledge, awareness and attitudes towards AI amongst professional groups in radiology, and to analyse the implications for the future adoption of these technologies into practice.Methods: We conducted 18 semi-structured interviews with 12 radiologists and 6 radiographers from four breast units in National Health Services (NHS) organisations and one focus group with 8 radiographers from a fifth NHS breast unit, between 2018 and 2020.Results: We found that radiographers and radiologists vary with respect to their awareness and knowledge around AI. Through their professional networks, conference attendance, and contacts with industry developers, radiologists receive more information and acquire more knowledge of the potential applications of AI. Radiographers instead rely more on localized personal networks for information. Our results also show that although both groups believe AI innovations offer a potential solution to workforce shortages, they differ significantly regarding the impact they believe it will have on their professional roles. Radiologists believe AI has the potential to take on more repetitive tasks and allow them to focus on more interesting and challenging work. They are less concerned that AI technology might constrain their professional role and autonomy. Radiographers showed greater concern about the potential impact that AI technology could have on their roles and skills development. They were less confident of their ability to respond positively to the potential risks and opportunities posed by AI technology.Conclusions: In summary, our findings suggest that professional responses to AI are linked to existing work roles, but are also mediated by differences in knowledge and attitudes attributable to inter-professional differences in status and identity. These findings question broad-brush assertions about the future deskilling impact of AI which neglect the need for AI innovations in healthcare to be integrated into existing work processes subject to high levels of professional autonomy.

Issue: In broad terms, current thinking and literature on the spread of innovations in health care presents it as the study of two unconnected processes—diffusion across adopting organizations and implementation within adopting organizations. Evidence from the health care environment and beyond, however, shows the significance and systemic nature of postadoption challenges in sustainably implementing innovations at scale. There is often only partial diffusion of innovative practices, initial adoption that is followed by abandonment, incomplete or tokenistic implementation, and localized innovation modifications that do not provide feedback to inform global innovation designs. Critical Theoretical Analysis: Such important barriers to realizing the benefits of innovation question the validity of treating diffusion and implementation as unconnected spheres of activity. We argue that theorizing the spread of innovations should be refocused toward what we call embedding innovation—the question of how innovations are successfully implemented at scale. This involves making the experience of implementation a central concern for the system-level spread of innovations rather than a localized concern of adopting organizations. Insight/Advance: To contribute to this shift in theoretical focus, we outline three mechanisms that connect the experience of implementing innovations locally to their diffusion globally within a health care system: learning, adapting, and institutionalizing. These mechanisms support the distribution of the embedding work for innovation across time and space. Practical Implications: Applying this focus enables us to identify the self-limiting tensions within existing top-down and bottom-up approaches to spreading innovation. Furthermore, we outline new approaches to spreading innovation, which better exploit these embedding mechanisms.

In this paper, we illustrate the link between social network structures, dominant cognitive frames on network purpose and the innovative power of a network, through a mixed-method comparative analysis of two knowledge translation networks (KTNs) in the English National Health Service (NHS). Our findings illustrate several challenges for networked forms of organization linked to different manifestations of social networks (centralized/decentralized) and dominant cognitive frames (polarizing/loosely clustered). Our paper contributes a better understanding of how dominant frames on network purpose emerge alongside the development of network structure itself, and explores how this interplay between dominant frames and social networks impacts upon the collaborative work that supports the network’s innovative power.

Studies suggest that the experience of liminality – of being in an ambiguous, ‘betwixt and between’ position – has creative potential for organizations. We contribute to theory on the link between liminality and creative agency through a study of the coordinators of ‘knowledge-sharing communities’; one of the latest examples of a ‘neo-bureaucratic’ practice that seeks to elicit innovative responses from employees while intensifying control by the organization. Through a role-centred perspective, our study found that both the structural and interpretive aspects of coordinators’ role enactments promoted a degree of creative agency. ‘Front-stage’ and ‘back-stage’ activities were developed to meet the divergent expectations posed by senior management and community members, and the ambiguity of their roles prompted an array of different role interpretations. Our findings contribute to theory by showing how the link between liminality and creative agency is not confined to roles and spaces (consultancy work, professional expertise) that are positioned across organizational boundaries, or free from norms and expectations, but may also apply to roles that are ambiguously situated within organizational contexts and that are subject to divergent expectations. This shows how neo-bureaucratic forms may be both reproduced and renewed through the creative responses of individual managers.

Recent work has questioned the institutional model of management innovation by highlighting interactions between the field‐level actors engaged in diffusing innovations and implementation of the innovation at organization level. Focusing on the adaptation of management innovations to their context, rather than their creation, we review this work and use it to analyse the global diffusion of resource planning (RP), counter posing this case with the widely studied example of total quality management. Both of these innovations experienced a high level of failure when implemented by organizations. Total quality management's diffusion was characterized by a ‘boom and bust’ cycle. RP, however, has continued to spread globally in the form of its variants: MRP, MRPII and ERP. Our analysis seeks to account for the long‐run diffusion of RP through a processual model which highlights the interplay between RP's discursive framing at field level, the affordances of the innovation itself and its adaptation within organizations. This demonstrates how objectifying RP in software not only helped to spread the innovation but also allowed field‐level actors to differentiate its development as a successful innovation from the many failures experienced by organizations attempting to adapt it.