In a groundbreaking study published in the prestigious Annals of Tourism Research, researchers have revisited the role of Artificial Intelligence (AI) in management systems within the hospitality sector, challenging prevailing assumptions that AI inherently diminishes workplace humanity. This study sheds light on the nuanced interplay between algorithmic governance and human managerial oversight, suggesting that AI’s impact is contingent upon how organizations implement and interact with these technologies.
Amid a surge in the adoption of AI-driven management systems across hotels, restaurants, and call centers, the research draws on an extensive observational study involving interviews with 30 industry professionals alongside the analysis of 61 distinct algorithmic management platforms. Contrary to fears that AI replaces managerial roles, the findings reveal a redistribution of authority—a silent reconfiguration rather than outright displacement. Tasks such as scheduling, performance tracking, and task allocation become algorithmically determined, yet it is ultimately the human managers who interpret, adapt, and sometimes contest these outputs who shape the experience and dynamics of the workplace.
The study introduces a conceptual framework termed “Modalities of (In)Visibility,” which critically examines how these algorithms construct workplace realities by controlling what gets measured, monitored, and valued. When these systems are designed and utilized to foreground contextual information and allow for human discretion, employees report a greater sense of empowerment and respect. Conversely, opacity in algorithmic processes fosters feelings of surveillance and subjugation, underscoring how the design and transparency of AI systems critically influence organizational culture and worker agency.
Dr. Brana Jianu, a key contributor to the study and Research Fellow at the University of Surrey, emphasized the potential of algorithmic management to enhance, rather than erode, workplace humanity. She articulated how embracing AI as a collaborative tool instead of a mechanism for control could uphold employee dignity while simultaneously driving operational efficiency. Her insights underscore the importance of keeping humans central to AI processes—promoting transparency, encouraging managerial discretion, and empowering employees to question and influence automated decisions.
A pivotal recommendation from the authors is the redesign of management dashboards to integrate not only individual productivity metrics but also indicators of team collaboration and collective performance. This holistic approach fosters transparency and inclusivity in algorithmic decision-making. Holding regular transparency sessions that openly communicate the role of data and algorithms in scheduling and evaluations further strengthens trust and diminishes employee anxiety associated with inscrutable automated governance.
The implications of this research extend well beyond hospitality, offering a blueprint for any sector integrating AI into management structures. Professor Iis Tussyadiah, Dean of Surrey Business School and co-author of the study, highlighted this broader significance, asserting that the hospitality industry functions as a critical testing ground for the future of AI in workplace management. The lessons uncovered here about humanizing AI, emphasizing human oversight and cooperative interaction with automated systems, possess transformative potential for reshaping workplaces across diverse domains.
By foregrounding human judgment, transparency, and flexibility within algorithmic management, organizations can recalibrate power structures, moving from rigid control toward collaborative empowerment. This reconsidered role of AI disrupts deterministic narratives of automation-driven job loss and oppression, instead opening possibilities for hybrid models where humans and machines mutually enhance organizational effectiveness and worker wellbeing.
Technically, this study leverages an observational methodology to bridge empirical evidence with conceptual innovation. The in-depth interviews offer qualitative insights into the lived experiences of those navigating AI-infused environments. Meanwhile, the systematic examination of multiple algorithmic systems provides a comprehensive understanding of the technological architectures shaping decision-making processes in real-world settings. This dual focus marries social science theory with applied engineering considerations, illustrating how adaptive design principles can embed human values within complex algorithmic systems.
Ultimately, the research suggests that AI itself is neither inherently liberating nor oppressive; rather, its ethical and practical consequences hinge on organizational choices regarding transparency, interpretability, and human involvement. Designing and deploying AI tools that render their logic visible and invite human intervention fosters an empowered workforce capable of critical engagement with technology. Such designs prevent the alienation associated with opaque surveillance and instead cultivate workplaces where dignity and efficiency coalesce.
This study represents a critical advance in understanding the socio-technical dynamics of algorithmic management, spotlighting how AI can be harnessed responsibly to support rather than supplant human leadership. It calls for an urgent reevaluation of AI governance frameworks in workplaces, urging collaborations between technologists, managers, and workers to develop systems that are not only technologically sophisticated but also ethically grounded and socially considerate.
As organizations globally accelerate their adoption of AI, the lessons drawn from hospitality offer a powerful template for embedding humanity at the core of algorithmic management. By fostering transparency, discretion, and dialogue rather than concealment and control, AI has the potential to contribute positively to the future of work, making workplaces more equitable, humane, and responsive to human needs.
Subject of Research: People
Article Title: Humanising algorithmic management systems
News Publication Date: 10-Sep-2025
Web References: https://www.sciencedirect.com/science/article/pii/S0160738325001276?via%3Dihub
References: doi:10.1016/j.annals.2025.104021
Keywords: Human resources, Artificial intelligence, Machine learning, Public health, Sociology
