Organisé par l’AI for Sustainability Institute de l’ESSCA School of Management, l’atelier « AI and the Future of Work : Organizational Challenges and Human Perspectives » examine les transformations du travail et des organisations liées à l’intelligence artificielle, en particulier à l’IA générative. Il explore les opportunités et les risques de la collaboration humain-IA pour la performance, l’innovation, la gestion des ressources humaines et l’expérience des salariés, ainsi que les enjeux de confiance, de sens, de pouvoir, d’éthique et de gouvernance. L’événement accueille des contributions interdisciplinaires sur des systèmes de travail intégrant l’IA de manière responsable, efficace et centrée sur l’humain.

Workshop: “AI and the Future of Work: Organizational Challenges and Human Perspectives” - Thursday, November 5, 2026 ESSCA Bordeaux Campus - 5 place d’Armes, 33100 Bordeaux

Argument

The workshop “AI and the Future of Work: Organizational Challenges and Human Perspectives”, held by the AI for Sustainability Institute of ESSCA School of Management, aims to explore new challenges that Artificial Intelligence (AI) and generative AI (gen AI) in particular brings into the workplace.

With the rising use of AI, organizations are undergoing a profound technological transformation. According to Cristofaro and Giardino (2025), the mid-2020s mark a “paradigm shift toward human–AI collaboration and integrating AI technologies into complex decision-making processes (Rabunal et al., 2009; Felt and Irwin, 2024).” This new paradigm gives rise to several questions, particularly in relation to organizational performance and human resources management. Research on AI and work alternates between emphasizing augmentation and value creation, on the one hand, and documenting resistance, threat, and unintended harm, on the other, revealing unresolved tensions that this call seeks to address.

On the optimistic side, scholars show that well-designed AI-employee collaboration can enhance business performance, dynamic capabilities, and innovation (Füller et al., 2024), especially when supported by knowledge sharing, appropriate skills, and socialization practices that enable “collaborative intelligence” in hybrid human-AI workforces (Chowdhury et al., 2022). Moreover, human-AI collaboration enables to solve unexplored and complex problems (Raisch, & Fomina, 2025).

On the pessimistic side, integrative reviews stress that employees frequently experience AI not as a neutral efficiency tool but as a source of fear (Kertechian, 2025), feelings of reduced self-efficacy, and antipathy (Yam et al., 2022), giving rise to a distinct form of “AI resistance” (Golgeci et al., 2025). These tensions are amplified by evidence that collaboration with AI can undermine core psychosocial mechanisms at work, for instance by lowering impression management concerns and, in turn, diminishing organizational citizenship behavior (Bai & Zhang, 2025). The literature also questions the relevance and effectiveness of human-AI collaboration, as algorithms lack essential features of human interaction, such as mutual understanding and shared goals (Shah & Tamine, 2026) and because humans alone sometimes outperform human-AI combinations (Vaccaro et al., 2024).

Reviews and conceptual frameworks call for human-centered acceptance models (Del Giudice et al., 2023), multilevel perspectives (Bankins et al., 2024), and attention to hybrid human-AI problem-solving (Raisch, & Fomina, 2025) to better understand how design choices around accessibility, anthropomorphism, augmentation, and legitimation shape employees’ experiences of trust, meaning, and control at work. Empirical studies further suggest that AI can reduce repetitive burdens yet simultaneously provoke job insecurity (Ghosh et al., 2024; Kertechian, 2025), spite toward algorithmic or robotic supervisors, and subtle forms of deviance or withdrawal, These developments raiseunresolved questions about power, ethics, and governance in AI-mediated work systems, that are further tackled by emerging regulatory frameworks such as the EU AU Act

We therefore invite contributions that unpack these contradictions, clarify boundary conditions and mechanisms to better understand AI within organizations. The workshop is open to all topics related to AI issues in the workplace, including but not limited to the themes outlined above, and welcomes diverse theoretical perspectives, methods, and disciplinary backgrounds.

Authors may submit their contributions in French or English.

Submission guidelines

Submissions must be original and may be written in either French or English.

The submission deadline is August 31, 2026.

Manuscripts of 1000 – 1500 words should be sent using the online submission form. Authors will be notified of the review outcomes by October 5, 2026.

Scientific committee

• Pauline de Becdelièvre, Professeure des Universités, Université Paris-Saclay, laboratoire RITM
• Pierrette El Howayeck, Postdoctoral Researcher, Organization, Management and Human Resources, ESSCA School of Management
• Rayane Elidrissi, Maître de Conférences, Université Paris 1 Panthéon Sorbonne, IAE Paris
• Stéphane Fauvy, Full Professor, Organization, Management and Human Resources, ESSCA School of Management
• Dejan Glavas, Director of the AI for Sustainability Institute, Associate Professor, Finance, Accounting and Management Control, ESSCA School of Management
• Marine Gouëdard, Deputy Director of the AI for Sustainability Institute, Assistant Professor, Organization, Management and Human Resources, ESSCA School of Management
• Mahrane Hofaidhllaoui, Professor and Research Director, Organization, Management and Human Resources, ESSCA School of Management
• Kevin Kertechian, Associate Professor, Organization, Management and Human Resources, ESSCA School of Management
• Ewan Oiry, Professeur des Universités en GRH, iaelyon School of Management

References

Bai, S., & Zhang, X. (2025). My coworker is a robot: The impact of collaboration with AI on employees’ impression management concerns and organizational citizenship behavior. International Journal of Hospitality Management, 128, 104179. https://doi.org/10.1016/j.ijhm.2025.104179

Bankins, S., Ocampo, A. C., Marrone, M., Restubog, S. L. D., & Woo, S. E. (2024). A multilevel review of artificial intelligence in organizations: Implications for organizational behavior research and practice. Journal of Organizational Behavior, 45(2), 159–182. https://doi.org/10.1002/job.2735

Chowdhury, S., Budhwar, P., Dey, P. K., Joel-Edgar, S., & Abadie, A. (2022). AI-employee collaboration and business performance: Integrating knowledge-based view, socio-technical systems and organisational socialisation framework. Journal of Business Research, 144, 31–49. https://doi.org/10.1016/j.jbusres.2022.01.069

Cristofaro, M., & Giardino, P. L. (2025). Surfing the AI waves: The historical evolution of artificial intelligence in management and organizational studies and practices. Journal of Management History. https://doi.org/10.1108/JMH-01-2025-0002

Del Giudice, M., Scuotto, V., Orlando, B., & Mustilli, M. (2023). Toward the human – Centered approach. A revised model of individual acceptance of AI. Human Resource Management Review, 33(1), 100856. https://doi.org/10.1016/j.hrmr.2021.100856

Füller, J., Tekic, Z., & Hutter, K. (2024). Rethinking Innovation Management—How AI Is Changing the Way We Innovate. The Journal of Applied Behavioral Science, 60(4), 603–612. https://doi.org/10.1177/00218863241287323

Ghosh, B., Wilson, H. J., Castagnino, T., & Waber, B. (2024). Gen AI Will Change How We Design Jobs. Here’s How. Harvard Business Review. https://hbr.org/2023/12/genai-will-change-how-wedesign-jobs-heres-how

Golgeci, I., Ritala, P., Arslan, A., McKenna, B., & Ali, I. (2025). Confronting and alleviating AI resistance in the workplace: An integrative review and a process framework.

Human Resource Management Review, 35(2), 101075. https://doi.org/10.1016/j.hrmr.2024.101075

Kertechian, K. S. (2025). Answering the Call: Reclaiming the Hero’s Journey for Human Agency in an AI-dominated World. The Journal of Applied Behavioral Science, 00218863251380889. https://doi.org/10.1177/00218863251380889

Raisch, S., & Fomina, K. (2025). Combining human and artificial intelligence: Hybrid problem-solving in organizations. Academy of Management Review, 50(2), 441–

464. (184534195). https://doi.org/10.5465/amr.2021.0421

Shah, C., & Tamine, L. (2026). Why “human-AI collaboration” obscures what actually happens in information seeking. Journal of the Association for Information Science and Technology, n/a(n/a), 1–5. https://doi.org/10.1002/asi.70059

Vaccaro, M., Almaatouq, A., & Malone, T. (2024). When combinations of humans and AI are useful: A systematic review and meta-analysis. Nature Human Behaviour, 8(12), 2293–2303. https://doi.org/10.1038/s41562-024-02024-1

Yam, K. C., Goh, E.-Y., Fehr, R., Lee, R., Soh, H., & Gray, K. (2022). When your boss is a robot: Workers are more spiteful to robot supervisors that seem more human. Journal of Experimental Social Psychology, 102, 104360. https://doi.org/10.1016/j.jesp.2022.104360