The rapid diffusion of Artificial Intelligence (AI) is transforming job characteristics, raising important questions about how to implement these technologies in organizations in ways that support employee well-being and performance. Drawing on the High-Involvement Management framework, this study examined employee-centered Artificial Intelligence implementation (ECAII) practices (defined as transparent communication, consultation, and training initiatives) as strategic levers to foster positive employee outcomes during Artificial Intelligence-driven transformations. Survey data were collected from 168 Italian white-collar employees who actively used Artificial Intelligence in their work. Structural equation modeling was employed to test direct and indirect relationships among employee-centered Artificial Intelligence implementation practices, work meaningfulness, job satisfaction, and job performance, as well as the moderating role of personal attitudes toward AI. Results showed that employee-centered Artificial Intelligence implementation AcademicEditor: HuaPang Received: 17December2025 Revised: 1February2026 Accepted: 4February2026 Published: 8 February2026 Copyright: ©2026bytheauthors. Licensee MDPI,Basel,Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY)license. practices had significant direct effects on both job satisfaction and performance, as well as indirect effects through work meaningfulness. Latent moderated mediation analyses further revealed that these indirect effects were stronger among employees with more positive attitudes toward Artificial Intelligence. Overall, the findings highlighted the importance of employee-centered strategies for enhancing meaningfulness and fostering positive outcomes during technological change. This study contributed to Human Resource Management (HRM) and meaningful work research by extending classic theoretical frameworks to Artificial Intelligence-enabled workplaces. Furthermore, from a practical perspective, our findings provided valuable guidance for organizations by highlighting the importance of transparent communication, employee involvement, and targeted training in reducing uncertainty and helping employees perceive their roles as relevant during the implementation of Artificial Intelligence.
Making Artificial Intelligence Work at Work: The Role of Human Resource Practices and Personal Attitudes in Fostering Meaningful Work with Artificial Intelligence
Diego Bellini;Carmela Buono;
2026-01-01
Abstract
The rapid diffusion of Artificial Intelligence (AI) is transforming job characteristics, raising important questions about how to implement these technologies in organizations in ways that support employee well-being and performance. Drawing on the High-Involvement Management framework, this study examined employee-centered Artificial Intelligence implementation (ECAII) practices (defined as transparent communication, consultation, and training initiatives) as strategic levers to foster positive employee outcomes during Artificial Intelligence-driven transformations. Survey data were collected from 168 Italian white-collar employees who actively used Artificial Intelligence in their work. Structural equation modeling was employed to test direct and indirect relationships among employee-centered Artificial Intelligence implementation practices, work meaningfulness, job satisfaction, and job performance, as well as the moderating role of personal attitudes toward AI. Results showed that employee-centered Artificial Intelligence implementation AcademicEditor: HuaPang Received: 17December2025 Revised: 1February2026 Accepted: 4February2026 Published: 8 February2026 Copyright: ©2026bytheauthors. Licensee MDPI,Basel,Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY)license. practices had significant direct effects on both job satisfaction and performance, as well as indirect effects through work meaningfulness. Latent moderated mediation analyses further revealed that these indirect effects were stronger among employees with more positive attitudes toward Artificial Intelligence. Overall, the findings highlighted the importance of employee-centered strategies for enhancing meaningfulness and fostering positive outcomes during technological change. This study contributed to Human Resource Management (HRM) and meaningful work research by extending classic theoretical frameworks to Artificial Intelligence-enabled workplaces. Furthermore, from a practical perspective, our findings provided valuable guidance for organizations by highlighting the importance of transparent communication, employee involvement, and targeted training in reducing uncertainty and helping employees perceive their roles as relevant during the implementation of Artificial Intelligence.| File | Dimensione | Formato | |
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