Revue Internationale de Psychosociologie et de Gestion des Comportements Organisationnels

Éditorial L’intelligence artificielle dans les organisations, comment (mieux) travailler avec ? Perceptions, attitudes et comportements des acteurs face au déploiement de l’IA en milieu professionnel

Christelle MARTIN-LACROUX — 2025-12-14

Éditorial

Artificial Intelligence-Related Anxiety Among Banking Sector Employees

Maria MERCANTI-GUÉRIN — 2025-12-14

Employee anxiety in the banking sector is widely documented in the literature. The question of whether artificial intelligence (AI) increases this level of anxiety remains under studied, while the extensive use of AI throughout the sector could represent an additional stress factor. The objective of this research is to determine what forms AI-related anxiety can take in the banking domain and to identify differences according to institutions and hierarchical levels. This study is based on a netnographic approach of the specialized forum Wall Street Oasis, analyzing 60 discussion threads and 1,421 comments from January 2023 to August 2024. The analysis combines ethnographic observation and automated processing via
Python for sentiment analysis and thematic extraction. The results reveal multidimensional
anxiety structured around three axes: technological (tool mastery, reliability, transparency),
professional (job security, skill evolution), and social (isolation, equity, corporate culture).
Several families of concerns emerge: task substitution/automation, career path dequalifica
tion, work intensification, algorithmic surveillance, ethical risks, and inequalities in access to
skills. Significant differences appear between traditional institutions and hedge funds, as well
as between hierarchical levels. This research opens perspectives for studying the impact of AI
on financial sector employee well-being and proposes managerial recommendations for sup
porting this technological transformation.

The Influence of Metaverses on Remote Collaboration: An Exploratory Study

David Jiwon HONG — 2025-12-14

In recent years, research on metaverses has experienced significant growth due to the increasing interest organizations have in these virtual worlds and the development of generative AI. This study examines the contribution of the metaverse in the context of team-based remote work, using the experience of a French SME. The study adopts a phenomenological approach to describe the perceptions and experiences of remote workers in virtual environments. To achieve this, five weeks of observation in four different virtual worlds, as well as semi-structured interviews, were conducted.
The findings reveal that immersive remote work not only facilitates collaboration within work teams but also enhances human connection and the management of professional image through avatarization. The study highlights the importance of telepresence in reducing the sense of isolation often associated with remote work. However, the effectiveness of this way of working depends on platform features, individual characteristics, and the quality of the equipment used.
From a theoretical perspective, this study underscores the value of incorporating psychological concepts derived from research on virtual environments (notably avatarization and telepresence) into research on new ways of working. From a managerial perspective, the study suggests that deploying metaverses for remote work cannot be generalized. Its adoption requires adaptation to the specific needs of users, particularly regarding coordination and us ability.

Inequity in Algorithmic Matching in HR: An ethnography on recruitment software pro viders’ neglect of procedural justice rules

Agathe FONSAGRIVE — 2025-12-14

This article seeks to shed light on the effects of the practices of actors in the algorithmic matching supply chain on fairness in treatment. It examines how recruitment software providers respond to the ways in which procedural justice rules have been implemented by matching algorithm suppliers. Drawing on Charmaz’s grounded theory approach, it analyzes data collected during a twenty-one-month ethnography conducted as part of a CIFRE doctoral project within a recruitment software provider distributing a third-party matching algorithm. The study is distinctive in that it is based on rare and sustained access to the digital solutions industry, a sector ordinarily hermetic to academic research. The findings reveal that matching algorithm providers supply solutions that violate procedural justice rules, and that recruitment software providers, overly focused on productivity, fail to recognize both this shortcoming and their own role, as distributors, in amplifying it. By adopting a socio-technical perspective, this work contributes to bridging theories on candidate reactions to selection systems with actual professional practices. It also calls on organizations to clarify responsibilities regarding procedural fairness within the subcontracting chain.

Understanding the complexity of an artificial intelligence adoption situation in the pub lic sector, by mobilizing Edgar Morin’s dialogical principle

Magalie DUARTE — 2025-12-14

The present study explores the process of adopting artificial intelligence (AI) in the public sector through the lens of complex thinking and, especially, Edgar Morin’s dialogic principle. The use of public AI creates significant societal and organizational tensions. Existing literature characterizes these tensions and provides insights into the rationale (the what and the why) behind AI adoption. The present study focuses on the process of AI adoption itself. The dialogic principle is mobilized, seeking to unite complementary and antagonistic movements rather than overcome them. It argues that this principle is essential to describe and understand these movements during the decision-making process to adopt AI. The present study adopts a qualitative and interpretive methodology, based on six months of immersion in the innovation department of a social housing provider, working on a predictive model of residents’ risk of loss of autonomy. The adoption process is characterized by the emergence of three antagonisms, as highlighted through our narrative approach: firstly, the tension between algorithmic rationalization and the mission of social support; secondly, the opposition between tacit and explicit knowledge within community-based professions; and third, the dilemma between surveillance and privacy. The dialogic reading proposed here, aligned with Morin’s intricate thought processes, helps facilitate a deeper understanding and reso lution of these antagonisms compared to a binary or factorial decision model of whether or not to adopt AI. The study thus proposes a renewed analytical framework to support public decision-makers in the process of adopting AI, emphasizing the importance of an integrative approach to technical, social, and ethical issues. This study provides insight into the process
of adopting AI in the public sector and encourages in-depth reflection on the responsible and contextualized adoption of these technologies.

Adoption of medical artificial intelligence: an ethnographic study of the trust construc tion among hospital practitioners

Amayelle REY — 2025-12-14

Some research suggests that existing technology acceptance theories must consider the affect elicited by the personalized nature of technology in addition to cognitive trust leading to adoption behavior. Beyond cognitive trust, emotional trust plays a crucial role in determining adoption intention for new technologies, such as medical artificial intelligence. Yet, research on medical AI primarily examines the resistance that hospital practitioners display toward algorithms, without explaining how these staff can cultivate a sense of trust in this technology. The objective of this study is to understand how hospital practitioners build their trust in medical artificial intelligence. A 24-month ethnographic study was conducted by a Ph.D. student in pharmacology at the University Health Research Center in Amiens, where hospital practitioners frequently use artificial intelligence in their work processes. This study demonstrates how the interaction of cognitive and affective elements leads to the development of trust in artificial intelligence, offering both theoretical and managerial contributions. The results provide a better understanding of hospital practitioners’ reluctance to adopt medical artificial intelligence and thus facilitate the adoption of the technology in this highly pragmatic context.

Point de vue Quand l’IA active les biais et la déresponsabilisation des décideurs : risque pour les individus et les organisations

Marius BERTOLUCCI — 2025-12-14

This article examines how the integration of artificial intelligence (AI) reshapes managerial decision-making by activating two often underestimated dynamics: the loss of account ability among actors and the exacerbation of cognitive biases. Based on a literature review, it shows that the use of AI, presented as a mere decision-support tool, transforms human agency to the point of reducing individuals to passive validators. At the organizational level, the adoption of AI induces processes of algorithmization that reconfigure routines, governance, and power relations, with technical dependencies likely to obscure decision criteria and erode discretionary judgment. The article proposes a set of recommendations addressing both AI design and management. Taken together, these insights shed light on the conditions for AI-assisted decision-making that preserve human agency and responsibility, while emphasizing the need for a close coupling between design, practices, and organizational mechanisms.