Manufacturing firms are increasingly pursuing AI-led transformations (e.g., predictive maintenance, quality inspection, and autonomous production), yet implementation often stalls after pilot projects. Prior literature links this “pilot-to-scale” gap to disorganised data and legacy IT (Clemens et al., 2023; Plathottam et al., 2023; Rauh et al., 2022), misaligned investment logics and budgeting routines (Hadhri et al., 2025), and capability deficits spanning technical skills and digital leadership (Mqoqi et al., 2026; Obi et al., 2025). At the same time, responsible AI introduces additional coordination challenges because accountability, transparency, and compliance remain difficult to operationalise across organisational layers and heterogeneous use cases (Besinger et al., 2025; Eng-ström et al., 2025). Based on previous studies (Engström et al., 2025), we argue that AI adoption is a socio-technical change where value arises from combining technology (models, data pipelines, and platforms) with decision-making rights, incentives, workflows, skills, and accountability. If this combination is weak, organisations might fall into “pilotism,” resulting in many projects but little learning or integration. This study asks: What organisational and governance mechanisms are required in manufacturing firms to convert AI aspirations into scalable and beneficial implementations? To answer our research question, a qualitative approach combining a focused literature review with co-creation workshops involving managers and specialists from six companies (A-F) was employed (Ahmed & Asraf, 2018) to identify AI goals, perceived blockers, and scaling mechanisms through discussions and group tasks (Ørngreen & Levinsen, 2017). The empirical material (field notes, audio recordings, and secondary data) was analysed using content analysis to find recurring patterns (Bengtsson, 2016). Across firms, evidence confirms literature: AI remains stuck in fragmented pilots because strategy, budgeting, data/legacy IT, skills, and governance are misaligned. More specifically, AI remains stuck because key organisational elements are misaligned. Firms often run many promising Proofs of Concept (PoCs), but the organisational system required for scaling (strategy → funding → data/IT → people → governance) does not “fit together”, preventing pilots from being industrialised into scalable, accountable deployments. There is a notable lack of shared direction, which results in isolated initiatives that fail to contribute to overall enterprise learning or effective scaling. The current funding model adheres to traditional ROI metrics, which create barriers to securing resources for scaling successful pilots, as they often fail to meet conventional thresholds or timelines. Many pilots are developed under conditions that do not generalise well, leading to challenges in scalability. Companies lack robust pipelines and deployable infrastructure necessary for broader implementation. There is an over-reliance on a limited number of individuals, as roles and learning routines are not well-defined. This situation hinders the establishment of standardised practices across teams. The absence of clear accountability and risk control mechanisms has blocked the operationalisation of successful pilot initiatives. On the other side, companies are working to tackle challenges by implementing a “governance spine” that merges centralised direction with decentralised execution. This approach features a dedicated AI strategy, clear decision rights, and local ownership through AI ambassadors and cross-functional teams. Key elements include a structured use-case pipeline (idea → business case → pilot → adoption), standardised tracking of ROI and KPIs, and role clarity with capability-building infrastructures for ongoing learning. Strong data governance ensures security and compliance. Successful scaling is more about organisational change than technology, requiring effective leadership and adaptive resourcing to align initiatives with operational needs.

Ingress: Organisationer tycks inte bli mer rustade av att förlita sig enbart på traditionella kursupplägg. Företag som presterar starkt ekonomiskt prioriterar verksamhetsnära insatser där ledarskapet utvecklas i det dagliga arbetet, skriver beslutsfattare från näringsliv och akademi.

I projektet System för ledarskapsutveckling har forskare vid Jönköping University i partnerskap med ett tiotal svenska organisationer och genom en nationell telefonintervju med drygt 1 300 privata och offentliga verksamheter fördjupat kunskapen om hur ledarskapsutveckling organiseras, uppfattas och omsätts i praktiken. Resultatet i denna rapport bygger på ett varierat material i form av dokument, intervjuer och workshops.

Genom projektet har vi fördjupat vår förståelse av att ledarskapsutveckling kräver systematik och integration. Det handlar om att arbeta medvetet och långsiktigt med olika arbetssätt som är kopplade till organisationens syfte, samtidigt som vi reflekterar över de antaganden och idéer som påverkar utformningen. Ett ledarskapsutvecklingssystem omfattar de arbetssätt som främjar utveckling av ledarskap anpassat efter verksamhetens syfte, kontext och föränderliga behov.

I rapporten beskriver sju organisationer sin syn på ledarskap och hur de arbetar för att utveckla detsamma. Genom deras egna ord får vi en inblick i hur ett system för ledarskapsutveckling kan se ut i praktiken. Särskilt markeras att ledarskapsutveckling måste skräddarsys utifrån organisatoriska förutsättningar och individuella behov. De aktiviteter och metoder som används måste kontinuerligt testas, förstärkas eller fasas ut beroende på relevans. Hellre hålla fast vid en genomtänkt metod än att ständigt byta.

Den nationella kartläggningen ger en översikt av vilka aktiviteter som är mest använda och till vem de vänder sig. Fördjupande analyser visar att de organisationer som har starkast finansiella resultat värderar fem verksamhetsnära metoder främst; chefsmöten, gruppreflektioner, utvecklingssamtal, förbättringsarbete och tillfälliga uppdrag.

Slutligen presenterar vi en uppsättning framgångsprinciper, frågor och verktyg för att arbeta mer systematiskt med ledarskapsutveckling. Vår förhoppning är att de ska fungera som en kompass för ett mer nyfiket och reflekterande arbetssätt och öppnar vägen mot en hållbar och framgångsrik ledarskapsutveckling.

In the project System for Leadership Development, researchers at Jönköping University have, in partnership with about a dozen Swedish organizations, deepened their knowledge of how leadership development is organized, perceived and put into practice. This was, among other things, done through national telephone interviews with more than 1,300 private and public organizations. The results presented in this report are based on various empirical sources in the form of documents, interviews and workshops.

Through the project, we have deepened our understanding of the need for leadership development to be systematic and integrated. It is a matter of working deliberately and with a long-term perspective with different practices that are linked to the organization’s purpose, all the while reflecting on the assumptions and ideas that influence the design. A leadership development system encompasses the practices that promote the development of leadership, adapted to the purpose, context and changing needs of the organization.

In this handbook, seven organizations describe their views on leadership and how they work to develop it. Through their own words, we get an insight into what a system for leadership development can look like in practice. In particular, it is emphasized that leadership development must be tailored to organizational conditions and individual needs. The practices and methods that are used must continuously be tested, strengthened or phased out depending on relevance. It is better to stick to a well-thought-out practice than to constantly change.

The national survey provides an overview of the practices most used and which target groups they are aimed at. In-depth analyses show that the organizations with the strongest financial results primarily prioritize five practices close to daily operations: leadership forums, performance and developmental reviews, improvement work, group reflections and temporary assignments.

Finally, we present a set of success principles, questions, and tools for working more systematically with leadership development. Our hope is that they will serve as a compass for a more curious and reflective way of working and that they will open the way towards sustainable and successful leadership development.

Purpose: This paper examines how gender shapes employees' emotional reactions to workplace AI, and whether these differences are associated with epistemic legitimacy, explained by perceived AI knowledge and conditioned by psychological safety. Design/methodology/approach: We analyse survey data from 104 employees using a conditional process framework. Multiple regression models test direct gender effects on cognitive and emotional reactions to AI, mediation via perceived AI knowledge, and moderation by team-level psychological safety. Findings: Women report less favourable cognitive and emotional reactions to AI than men. These differences are largely attributable to lower perceived AI knowledge. Psychological safety attenuates the direct gender effect: in high-safety climates, gender gaps in reactions diminish; in low-safety climates, they re-emerge. Overall, the pattern supports a contextualised partial-mediation model in which perceived knowledge is pivotal, but its explanatory power depends on climate. Research limitations/implications: The cross-sectional design limits causal inference and the generalisability is bounded by the organisational context studied. Future research should use longitudinal or experimental designs, examine additional inequality dimensions (e.g. age, role), and unpack how AI literacy interventions reshape appraisal dynamics over time.Practical implicationsAI initiatives should build employees' perceived understanding (how AI works, limits, and human-AI complementarity) and foster psychological safety so that questions and uncertainty are acceptable. Monitoring gendered participation and confidence during roll-out helps prevent AI from amplifying existing inequalities. Social implications: Managing AI adoption as an inclusion challenge-rather than solely a technical one-can reduce uneven emotional costs of digital transformation and support fairer access to AI-enabled opportunities. Originality/value: The study integrates gender, appraisal (perceived AI knowledge), and climate (psychological safety) into a single framework explaining both cognitive and emotional reactions to AI. It reframes gender gaps as contextual, highlighting levers - literacy and climate - that organisations can use to enable more equitable AI adoption.

AI is viewed as the next major technological breakthrough for organizations. The range of areas, professions, and practices that can be improved with AI assistance or automation is overwhelming. However, this wide array of possibilities also brings a variety of expectations about how AI will change organizations and employees’ everyday work. Considering that voiced expectations influence adoption processes by both reflecting and shaping certain relational, belief-driven dynamics, we can learn a great deal about AI adoption by studying the organizational plurality of AI expectations. Therefore, this study examined AI expectations held by employees in three organizations currently adopting AI for use in the workplace. The study is based on a thematic analysis of empirical material form 15 focus groups in three Swedish AI-adopting organizations and shows how AI expectations shape the following: (1) a growing desire to move from exploring AI to establishing AI routines and regulations, (2) emerging dilemmas related to both the violation and fulfillment of AI promises, and (3) how dynamics and unpredictability in the AI field require organizations to adapt to shifting trends and innovations.

Purpose

Artificial intelligence (AI) has the potential to be a disruptive technology instigating paradigm shifts and significantly impacting both operational and strategic processes while presenting organizations with contradictory demands. This paper aims to explore tensions in the early stages of AI adoption in manufacturing firms.

Design/methodology/approach

Drawing on paradox theory and 23 focus groups with 112 white-collar employees, we identify 9 themes categorized into 2 overarching dimensions: (1) temporal tensions between current capabilities and anticipated futures and (2) relational tensions between human and machines.

Findings

Temporal tensions unfold along emergent trajectories where progress is uncertain, nonlinear and continuously negotiated. Relational tensions are marked by ethical reflexivity, as employees navigate shifting expectations around trust, control and human identity. Our findings show how these tensions reinforce one another and contribute to organizational hesitation and strategic drift.

Research limitations/implications

The study focuses on large multinational manufacturing firms, limiting the generalizability of findings to other industries or small and medium-sized enterprises. Additionally, the study captures only the early stages of AI implementation, necessitating further longitudinal research to examine long-term organizational adaptations. Future research should explore cross-industry comparisons and investigate how different leadership styles influence AI-driven transformations.

Practical implications

This research provides actionable insights for managers navigating AI integration. Addressing tensions proactively – through strategic workforce upskilling, clear AI governance frameworks and fostering human-AI collaboration – can mitigate resistance and maximize AI’s benefits. Organizations should embrace paradoxical thinking, leveraging AI to enhance productivity while supporting employees in transitioning to evolving roles.

Social implications

The study highlights the societal impact of AI adoption in the workplace, particularly concerning job displacement fears and the evolving human-machine relationship. Managing AI transformation responsibly requires ethical considerations, workforce empowerment and inclusive policies to ensure that AI-driven innovations benefit employees and organizations alike.

Originality/value

By conceptualizing AI adoption as a process shaped by interwoven temporal and relational paradoxes, the study offers new insights into the emotional, ethical and structural dimensions of integrating AI into established organizational settings.

A leadership development system (LDS) encompasses all methods and practices used in an organisation to train and develop effective leadership. However, the underlying assumptions upon which such a system is based are often overlooked, and the workplace as a learning site is generally under-investigated, which may cause an unreflected LDS. Using a social representations theory approach, this study explores such underlying assumptions, i.e. social representations of leadership and leadership development, among 19 employees of an organisation with a non-hierarchical business structure. To collect data, the free association method was used to reveal underlying social representations shaping the company’s current LDS. Through a transdisciplinary framing and customised design of work-integrated learning (WIL) among the employees (N = 57), the study also develops an exploratory model for facilitating the development of a deliberate LDS. The results show that uncovering social representations supports professional learning in work, which helps create an LDS that is based on articulated awareness. The study further shows that the process of uncovering hidden values, ideas, and perspectives can support a context-relevant and customised WIL curriculum for professional learning and cultivate a deliberate and purposeful approach to leadership development.

This study explores the relationship between organizational leadership identity, defined as "who we are" and "what we value related to leadership", and leadership development practices in five Swedish companies. Through the analysis of their narratives, the study reveals five distinct organizational leadership identities, ranging from individual leadership excellence to collaborative self-leadership. These identities significantly influence the shaping of a leadership development system (LDS) in practice. The study highlights three critical aspects—coherence, continuity, and comprehensiveness—that define the interdependency between leadership identity and an LDS. A closer linkage creates high interdependency, resulting in a stronger and more effective system, while weaker linkages reduce this interdependency and its potential to support organizational objectives and manage change. This research challenges traditional, linear models of leadership development, emphasizing the interaction and interconnectedness of practices within an organized "place". This place serves as a site of integration, activation, and interconnection between people, things, and experiences. By integrating concepts of organizational identity, historical context, and values, the study provides a more holistic theoretical framework for understanding how effective leadership is developed within organizations.

In the leadership development literature, there is a strong consensus for the value of taking a tailored approach to leadership development. Yet, the literature is surprisingly silent about what such tailoring actually involves. We review the leadership development literature through a didactical lens and develop a process model of didactic tailoring and leadership development. Our emerging conceptual model subsume the existent but oftentimes scattered research into the tailoring of leadership development programs into an overarching organizing framework. Our model helps identify the underlying processes involved in didactic tailoring of leadership development programs. It also articulate how these processes combine to predict leadership development. Finally, we outline a step-by-step guide informing how to conduct didactic tailoring. Our theoretical model provides valuable guidance for scholars and practitioners interested in designing, executing, evaluating, reporting, and reviewing leadership development programs.