Can Generative Artificial Intelligence Productivity Tools Support Workplace Learning?:A Qualitative Study on Employee Perceptions in a Multinational Corporation

PurposeThe purpose of this study was to explore employees’ perceptions and firsthand experiences of the impact of generative artificial intelligence (AI) productivity tools, specifically Microsoft 365 Copilot, on individual and collective learning processes within a multinational corporation. In doing so, the study provides insights into how these tools can shape workplace learning dynamics, fostering both individual skill development and collaborative knowledge-sharing practices.Design/methodology/approachThe authors collected responses from 357 participants through a survey that included both multiple-choice and open-ended questions. This study focuses exclusively on the qualitative responses. The reflexive thematic analysis method was used to capture and interpret employees’ perceptions of the role of Microsoft 365 Copilot – a generative AI-powered assistant integrated into the Microsoft 365 suite of applications (e.g., Word, Excel, PowerPoint, Outlook, Teams) – in enhancing their work and learning opportunities in the workplace.FindingsThe results highlight four key themes contributing to workplace learning. At the individual level, Task Support illustrates the extent to which generative AI productivity tools transform work practices and facilitate both formal and informal learning pathways, while Meaningful Work underscores the tools’ role in enhancing employees’ foundational knowledge through enriched information. At the organisational level, organisational culture suggests the importance of fostering a supportive environment for AI integration, while organisational socialisation highlights its influence on team cohesion and the informal knowledge-sharing processes essential for effective collaboration within and among team members.Practical implicationsThe results of this study offer actionable insights for organisations integrating generative AI productivity tools in the workplace. Understanding employees’ perceptions of the role of AI in workplace learning can inform the design of targeted training programmes that promote individual skill development and foster collaborative knowledge sharing. Furthermore, a supportive organisational culture that positions AI as a complementary resource can improve employee engagement, reduce resistance to new technologies and encourage a growth-oriented mindset, ultimately driving both personal and organisational development.Originality/valueThis study shifts the narrative around the role of AI in the workplace by examining how generative AI productivity tools can enhance workplace learning at both individual and organisational levels, rather than focusing solely on their potential to disrupt work through displacement and automation. By positioning AI-based applications as complementary to human work, this approach highlights their potential as enablers of skill development, knowledge sharing and job enrichment, fostering a more adaptive and learning-oriented work environment

Meaningful work as shaped by employee work practices in human-AI collaborative environments:a qualitative exploration through ideal types

Purpose: This study aimed to investigate how employees perceive meaningful work in tasks co-generated by Microsoft 365 Copilot, an AI-powered workplace assistant. Specifically, it explored how its adoption influences work practices, autonomy and decision-making, identifying patterns of user experiences that shape attitudes toward AI integration in professional settings. This offered an opportunity to further theorise the notion of meaningful work as it is constructed and reconfigured through emerging patterns of human–AI collaborative environments.Design/methodology/approach: Data were collected through a survey administered to 802 employees of a multinational company who were given a Microsoft 365 Copilot licence to test this AI-powered assistive tool in their daily tasks, yielding 357 responses. The survey included both multiple-choice and open-ended questions, with this study focusing on the qualitative empirical data. Specifically, we applied the qualitative ideal-type analysis method to identify typologies of user adoption practices with the artificial intelligence (AI)-powered assistive Microsoft 365 Copilot tool.Findings: Three Ideal Types were identified: Ideal Type [1] – the Efficiency-Seeking Type – perceives Microsoft 365 Copilot as a straightforward task-assistance tool, Ideal Type (2) – the Pragmatic Integrator Type – views it as a smarter assistant, and Ideal Type (3) – the Collaborative Optimiser Type – considers it an expert-like teammate. The results indicate that meaningful work is not a static construct; rather, it evolves through the dynamic interplay between objective dimensions of meaningful work in human-AI collaborative environments – such as task discretion and organisational structures –and subjective experiences, including users’ perceived role and expertise. Additionally, we underscore how cognitive prompts and metacognitive prompting become not only a technical competence to effectively interact with technology, but a reflective and interpretive practice through which workers negotiate relevance, value and purpose in their tasks.Practical implications: Understanding diverse employee perspectives through ideal-type analysis enables tailored strategies for reskilling and upskilling, supporting individual needs and fostering adaptive work practices. It also informs the design of personalised development programmes and awareness initiatives that highlight human expertise, ensuring meaningful work and engagement in human-AI collaborative environments.Originality/value: This article advances the discourse on meaningful work within human–AI environments by examining the factors that support or constrain employees' capacity to find significance and fulfilment in their roles, as influenced by the interplay between individual agency – reflected in users’ decision-making, engagement and role adaptation – and organisational contexts, including technological integration, workplace structures, and human-AI collaborative practices. The use of Ideal Types in the qualitative approach strategy helps maintain the uniqueness of users' perspectives, capturing diverse experiences and patterns of AI adoption while preserving individual meanings and interpretations of meaningful work

Realising human-robot collaboration in manufacturing? A journey towards industry 5.0 amid organisational paradoxical tensions

Human-robot collaboration is envisioned as a cornerstone of the future ‘ideal’ industry (Industry 5.0)—resilient, sustainable, and human-centred. While this goal has not yet been fully realised, advancements in collaborative robotic technology are expected to accelerate progress. Central to this vision is a workforce equipped with the skills necessary to collaborate effectively with robots in ‘ideal’ hybrid teams. Existing literature widely supports this optimistic outlook, suggesting that with the right technological developments, workforce reskilling and upskilling, and the resolution of key ethical and social concerns, human-robot collaboration in manufacturing will eventually become a reality. In this paper, we draw on a one-year field study that engaged with 39 representatives from industry, research, and other key stakeholders in both the technical and human factors of collaborative applications. Using constructive grounded theory and abductive reasoning, we challenge the assumption that the trajectory towards human-robot collaboration is straightforward or can be resolved through a one-time solution. Instead, our results reveal a journey marked by a series of paradoxical tensions, providing a fresh perspective on the complexities and unexpected empirical ‘surprises’ that define the transition towards Industry 5.0. We employ Paradox Theory to examine and elucidate this evolving journey, where paradoxes— such as automation vs augmentation, technical efficiency vs human wellbeing, and exploration vs exploitation— emerge, shift, and are managed in unexpected ways, revealing interdependencies between different types of responses across micro, meso, and macro levels of analysis. Extending beyond current theorisations on the implementation of Industry 5.0, our study contributes substantively and theoretically to understanding the evolving socio-technical complexities that shape this transition, highlighting the interplay between technological advancements, organisational dynamics, and workforce adaptation

Testing a novel haptic tram master controller technology via virtual reality:feasibility and user acceptance considerations

Purpose: Virtual Reality (VR) has been explored as a training and testing environment in a range of work contexts, and increasingly so in transport. There is, however, a lack of research exploring the role of VR in the training of tram drivers, and in providing an environment in which advances in tram technology can be tested safely. This research sought to test a novel haptic tram master controller within a tram-based VR environment (VE). Design/methodology/approach: The master controller is the primary mechanism for operating a tram, and its effective manipulation can significantly influence the comfort and well-being of passengers, as well as the overall safety of the tram system. Here, we tested a haptically-enhanced master controller that provides additional sensory information with 16 tram drivers. The feasibility and user acceptance of the novel technology were determined through surveys.Findings: The results indicate that the haptic master controller is seen as beneficial with the drivers suggesting that it could enhance their driving and demonstrating good acceptance. The VE has provided a potential training environment that was accepted by the drivers and did not cause adverse effects (e.g., sickness). Research limitations/implications: Although our study involved actual tram drivers from a local tram company, we acknowledge that the sample size was small, and additional research is needed to broaden perspectives and gather more user feedback. Furthermore, while our study focused on subjective feedback to gauge user acceptance of the new haptic technology, we agree that future evaluations should incorporate additional objective measures.Practical implications: The insights gained from this VE-based research can contribute to future training scenarios and inform the development of technology used in real-world tram operations.Originality/value: Through this investigation, we showed the broader possibilities of haptics in enhancing the functionality and user experience of various technological devices, while also contributing to the advancement of tram systems for safer and more efficient urban mobility

Transition Between Sensitive Delusion of Reference and Mood Disorder: A Case Report

The Sensitive Delusion of Reference is a clinical entity described by Ernst Kretschmer and never integrated into mainstream nosographic systems. It represents the possibility of developing psychosis starting from a personality characterized by sensitivity, scrupulousness, and fear of judgment of others. The presentation of the following clinical case highlights how the overlap between this clinical entity and mood disorders leads to characteristic psychopathology, which has not been sufficiently detailed. In particular, the delusions, which always starts from the idea of reference and the shame in the face of the judgment of others, takes on characteristics of guilt during the depressive phases and persecutory themes during the activation phases. This clinical observation, which obviously needs to be confirmed on a larger scale, encourages a renewed interest in the concept of Kretschmer's Sensitive Delusion of Reference and creates the possibility of intersecting multiple psychopathological levels, for a more complete perspective on the individual case

What is it like for a middle manager to take safety into account? Practices and challenges

Aviation today is seen as a very safe industry, yet recent accidents have shown that vulnerabilities still exist. The literature has often drawn attention to the role played by top managers/CEO in running their businesses profitably, and at the same time keeping them safe from threats. Research has also investigated the way people at the sharp-end of organisations are ‘mindful’ of the possible threats that can occur in their day-to-day activities, and how they can anticipate (most of) them. But what about the role played by middle managers in ensuring safety in every organisational operation? Even if researchers now agree that middle managers’ actions are a valuable asset for organisations and central to pursuing key organisational outcomes, very little is known about how middle managers take safety into account in their daily operations, and the challenges they face. This paper reports on the safety-related practices and challenges of middle managers of the civil aviation industry. Within the Future Sky Safety project, over a two-year research activity, 48 middle managers from a range of aviation organisations agreed to talk about the strategies and actions they put in place on a routine basis, to embed safety in the daily operations. Methodologically, semi-structured interviews were conducted and the qualitative content analysis (QCA) method was used to make sense of the raw material, through a data-driven coding frame. The findings of this research suggest that the practices middle managers identify as central in relation to their role in the management of safety can be grouped into three high-level categories: (1) making decisions, (2) influencing key stakeholders to get the job done, and (3) managing information. This research adds knowledge in relation to the middle managers’ role in the management of safety, in particular shedding light on the competency that middle managers from the civil aviation industry rely on to get the job done when it comes to contributing to safety

“Braking bad”:The influence of haptic feedback and tram driver experience on emergency braking performance

Trams are experiencing a resurgence with worldwide network expansion driven by the need for sustainable and efficient cities. Trams often operate in shared or mixed-traffic environments, which raise safety concerns, particularly in hazardous situations. This paper adopts an international, mixed-methods approach, conducted through two interconnected studies in Melbourne (Australia) and Birmingham (UK). The first study involved qualitative interviews, while the second was an experimental study involving a virtual reality (VR) simulator and haptic master controller (i.e., speed lever). In tram operations, master controllers play a critical role in ensuring a smooth ride, which directly influences passenger safety and comfort. The objective was to understand how a master control system, enhanced with additional haptic feedback, could improve tram driver braking performance and perceptions in safety-critical scenarios. Interview results indicate that the use of the emergency brake is considered the final or ultimate choice by drivers, and their driving experience is a moderating factor in limiting its application. Combined with the experimental results, this paper highlights how implementing haptic feedback within a master controller can reduce the performance disparity between novice and experienced tram drivers.</p