Teaming with Technology: Adaptive Automation in Joint Cognitive Systems for Industry 5.0

Abstract: Adaptive automation enables dynamic reallocation of functions between people and autonomous agents to improve performance in complex work. This paper presents a meta-analysis of experimental and quasi-experimental studies (2000–2025) on joint cognitive systems in industrially relevant contexts, quantifying effects on task performance, safety/failure management, workload, trust, and learning. Across studies, adaptive automation reliably reduces operator workload and shows moderate gains in task performance and safety, with healthier trust dynamics when adaptations are triggered by human-state or event cues, made transparent to the user, and remain rapidly overridable. Risks emerge when performance-triggered switching is opaque or poorly timed, which can erode trust, induce cognitive tunneling, or hinder skill retention. The findings translate into actionable guidance for human-factors researchers, system designers, and operations leaders seeking Industry 5.0 outcomes: human-centric, resilient, and sustainable work systems in which digital teammates help people do their best work.

Keywords: Adaptive Automation, Joint Cognitive Systems, Human-Automation Teaming, Industry 5.0

DOI: 10.54941/ahfe1006995

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