Aurelio Ravarini

In this paper, we present a model that examines the relationship between job crafting and the use of generative AI within evolutionary socio-technical systems. A review of existing literature reveals a lack of focus on the changing nature of socio-technical systems, especially with the integration of technologies like generative AI. Moreover, there's limited research on process-based models in the area of job crafting. Our model addresses these gaps and discusses the role of generative AI in task execution, knowledge sharing, and individual control over tasks. By understanding the connection between job crafting and generative AI, this study offers insights for organizational management and individual adaptation. Future research could consider team interactions, role changes, and new ways to represent changes in socio-technical systems.

This paper presents a scoping review of the field of Digital Job Craft ing, specifically focusing on the impact of Artificial Intelligence and Generative AI on job crafting. This conceptual study provides an in-depth analysis of the literature, which takes advantage of previously developed theoretical frame works on DJC, proposing an innovative model that considers specific variables of the crafter impacted by AI and Generative AI applications.

This article proposes a framework meant to explain the impact of Generative AI on the phenomenon of job crafting. An in-depth analysis of the literature has allowed us to understand the differentiating element of a new form of job crafting, which sees the crafting of the work enabled by Generative AI, and - more specifically - by LLM (Large Language Models) application. The framework proposes to use the sociotechnical system as a reference model, yet focusing on two of its components: “technology” and “people”. The framework specifies the characteristics of the interaction between technology (Generative AI) and people (the crafters, i.e. workers who practice job crafting) by exploiting the most recent studies on both topics. Unlike the traditional applications of the sociotechnical model, this framework proposes to see the interdependence between technology and people as a cyclic ever-stopping reciprocal influence.

Businesses across all sectors are developing and implementing increasingly “intelligent” systems that are empowered by a wave of artificial intelligence (AI) technologies, driven by the growing availability and accessibility of data and processing power. This paper examines the state of AI adoption in small and medium-sized enterprises in the manufacturing sector, an area of research that has received relatively little attention. Three small and medium-sized enterprises, whose main offices are located in Northern Italy, have been studied to understand how they deal with the issue of AI adoption and what problems they typically encounter. An articulated picture emerges where SMEs struggle between the desire to realize the promises of innovation and the ability to build the appropriate organizational setting to pursue it.

In this paper, we introduce Digital Job Crafting as an evolution of the concept of job crafting. An in-depth literature review allowed us to recognize that in the broad research dedicated to job crafting; only limited attention has been dedicated to the effect that digital technology can have on the practices of job crafting. We propose to use the socio-technical approach to make such impact explicit and – therefore – to re-frame the concept of job crafting in a new integrated model. Two case studies are presented to explore the effectiveness of applying the model in different organizational contexts.