PhD Thesis Defense Presentation: Rania Afiouni
Rania Afiouni, a doctoral student at 91丝瓜视频 in the Information Systems area will be presenting her thesis defense entitled:
A Control Perspective of Delegation to Artificial Intelligence at Work: From Worker Adaptation to Job Transformation
Tuesday, June 16, 2026, at 9:00 AM
(The defense will be conducted in hybrid mode: Location - Armstrong Building, Room 250; for zoom link, please contact the PhD Office)
Student Committee Co-chairs: Prof. Alain Pinsonneault
Please note that the Defence will be conducted in hybrid mode.
Abstract
Delegating tasks to autonomous Artificial Intelligence (AI) systems alters how work is exercised and experienced. As AI systems assume decision authority, workers must continuously negotiate their own sense of personal control. While the human-AI
work literature has enhanced our understanding of workers鈥� adaptation and changes to their practices, there is yet a need for an integrative theoretical perspective that accounts for the interconnectedness of separate adaptive behaviors and cognitions and extends adaptation beyond the immediate interaction with AI systems. The thesis recognizes this need and proposes a control perspective to attend to it by asking the question: How does delegation of work to increasingly autonomous AI systems reshape personal control dynamics and reconfigure jobs? To answer this question, we develop a multi-level and temporally layered account of control in AI-enabled work contexts through three interrelated essays.
Essay 1 reviews the human-AI work literature, examining its intellectual structure. Drawing on science-of-science perspectives and a corpus of 651 articles published between 2015 and 2025 in leading Information Systems (IS) and management
journals, it combines bibliographic coupling, thematic modeling, and emergence metrics to analyse the state of this research area and the topics that dominate it. The analysis reveals that topics exhibiting high growth recombine established conceptual vocabularies, suggesting growth through consolidation rather than conceptual novelty. By mapping the field鈥檚 structural dynamics, the essay identifies a strategic opportunity for IS scholarship to shape the next phase of human-AI research through novel theoretical contributions.
Building on this opportunity, essay 2 represents the theoretical core of the thesis, developing the Human-in-Control (HiC) model to explain how workers adapt when delegating to AI. Conceptualizing personal control as a dynamic experiential process, the model introduces contextual congruence to capture the alignment between delegation preferences and work environments. It identifies four adaptation pathways characterized by distinct configurations of primary and secondary control processes through which workers maintain, restore, or enhance personal control. This essay contributes to IS scholarship by offering an integrated framework explaining how workers reconfigure personal control under conditions that encourage or limit AI delegation. It extends adaptation theory by addressing delegation constraints that create disruption through deprivation.
While the HiC model explains how control tensions unfold in the short term at the individual level, essay 3 examines longer-term transformations of work through an indepth qualitative study of consultants adapting to process mining technology. Building on job crafting theory, it develops a model of job transformation in which changes to automated and augmented tasks, relationships, and cognitive reframing unfold in ripples enabled by the development of particular skills and by changes to the mindset. Together, these ripples expand consultants鈥� job horizontally and vertically through scope crafting, proposed as a fourth dimension of job crafting. The study contributes a skill-contingent, non-linear account of how digital technologies transform work.
Collectively, the three essays identify and articulate a need for conceptual novelty in the human-AI literature and provide one possible path forward: personal control. They advance a multi-level, temporally layered theory of human-AI work that responds to field dynamics and integrates short-term adaptive processes, and longer-term boundary transformations. By positioning personal control as its integrative mechanism, the thesis provides a coherent framework for understanding how workers navigate delegation to AI and offers a foundation for future research on the evolving relationship between human sense of control and intelligent technologies.
