Research Information System
44th International Labour Process Conference-Labour Process at a Time of Transformation, Leeds, England, 22 - 24 April 2026, pp.593-595, (Summary Text)
This paper revisits and expands Labour Process Theory (LPT) in the context of the transformation of automotive production with Artificial Intelligence (AI). Classical and second-wave LPT analyses have centered on the dynamics of skills, control, and consent. While these studies revealed how technology and management strategies shape labour power, they often fragmented and overlooked the broader configuration of other production process dynamics, including the production relations, and working conditions. This paper argues that, in the era of AI, understanding the transformation of work requires a holistic/tripartite framework that reconnects the production process, production relations, and working conditions, because these are mutually constitutive.
Within this framework, production process is examined through skill, division of labor, routinization and standardization dimensions, illuminating how workflows and expertise are restructured; production relations is argued with rationalization, hierarchical relations, control, learning the job illuminating how discretion, authority, and agency are renegotiated; and working conditions is argued with wages, working hours, insurance shows how algorithmic management reshapes labour value and security. The tripartite analysis of these dimensions is challenging, yet theoretically necessary, as grasping the changing occupational structures requires observing how these interrelated dynamics mutually constitute and influence one another.
The holistic framework requires a significant theoretical synthesis to enhance labour process theory. Most LPT studies of AI remain rooted in a traditional framework, missing opportunities to integrate insights from contemporary approaches. To conceptually expand LPT, the paper integrates Actor-Network Theory (ANT), Social-Centric AI (SCIA), Human-Centered AI (HCAI), and Human-AI Interaction (HAII). Within this theoretical insight, ANT allows the inclusion of AI as an actor in the production, while SCIA, HCAI, and HAII extend the analysis toward the social dimension of technological integration. This synthesis enables an understanding of the labour process as an assemblage of human and non-human actors, revealing new relations and conditions that transcend classical LPT boundaries.
Furthermore, many analyses risk falling into technological determinism, overlooking the crucial dimension of worker subjectivity. To empirically ground this claim, the study employs through an ongoing qualitative case study based on experiences of blue- and white-collar workers in the Turkish automotive manufacturing sector, moving beyond the limitations of technological determinism to center worker agency in the analysis. The study conceptualizes the factory and labour process as a site of analysis in which human and technological actors continuously shape the work. The dual-focus on professional and non-professional labour allows for a critical, comparative analysis of how AI reconfigures the work.
To sum up, this study offers a contribution to LPT both theoretically and empirically. Theoretically, it expands the analytic lens with ANT, HAII, HCAI, and SCAI through discuss the multifaceted influences under algorithmic transformation. Empirically, it provides qualitative empirical evidence directly from workers’ experience who use AI in the workflow. The study concludes that AI is not an external force but as a constitutive element of the contemporary labour process, a social and technological actor that reshapes how work is organized and experienced the transformation of the production process, relations and conditions.