Navigating personal control: AI augmentation and its impact on decision-making

As Artificial Intelligence (AI) becomes increasingly embedded in organisational decision-making, it fundamentally reshapes workers' personal control over their tasks and outcomes. While, in contrast to AI automation, AI augmentation is typically promoted as a way to preserve human agency and personal control, empirical evidence regarding its psychological consequences remains fragmented. This study adopts Control Theory to examine how varying degrees of AI involvement, conceptualised as a continuous gradient rather than a binary condition, affect Personal Control (PC). Through an online within-subject experiment, participants performed a logistical optimisation task (bin-packing) under varying degrees of AI support. The findings reveal that high AI involvement significantly reduces PC, whereas for low and medium AI levels PC remains comparable to the no-AI condition. The research identifies perceived responsibility as a key mediator: increased AI intervention diminishes the sense of responsibility, subsequently eroding PC. Furthermore, the user's personality - specifically Locus of Control - moderates this relationship, suggesting that individuals with an internal orientation are more sensitive to control loss. The study identifies a critical threshold within the augmentation region beyond which increasing AI involvement begins to produce control-reducing effects comparable to those of full automation, even when humans formally retain final decision authority. The work offers practical implications for the design of human-centric AI systems and for the operationalisation of human-in-the-loop principles in the workplace.