Paper Type
Complete
Paper Number
PACIS2026-1138
Description
Digital transformation in industrial sectors has created new challenges for digital immigrants whose formative personal and professional experiences predate the advent of digital technologies. Most industrial digital transformation initiatives fail to adequately address the technostress experienced by Industrial Digital Immigrants (IDIs). This systematic literature review identifies digital constraints from an IDI-centric perspective, which is currently lacking in the literature. This study also proposes a conceptual framework based on an Artificial Intelligence (AI)-enabled adaptive scaffolding intervention to reduce cognitive load, enhance digital self-efficacy, and improve system usability for IDIs. Within the broader context of Industry 5.0’s core principle of integrating human expertise with intelligent automation, this study proposes a theoretical digital transformation framework to achieve better organisational outcomes and reduce the marginalisation of the IDIs. Furthermore, this framework could support solutions to reduce the digital exclusion of nonindustrial digital immigrants, such as seniors, through its human-centric, adaptive, and cognitively supportive approach.
Recommended Citation
Reddy, Shailendra; Hassandoust, Farkhondeh; and Sundaram, David, "AI-Enabled Human-Centric Approaches for Empowering Industrial Digital Immigrants: A Systematic Literature Review" (2026). PACIS 2026 Proceedings. 1.
https://aisel.aisnet.org/pacis2026/isdesign_tam/isdesign_tam/1
AI-Enabled Human-Centric Approaches for Empowering Industrial Digital Immigrants: A Systematic Literature Review
Digital transformation in industrial sectors has created new challenges for digital immigrants whose formative personal and professional experiences predate the advent of digital technologies. Most industrial digital transformation initiatives fail to adequately address the technostress experienced by Industrial Digital Immigrants (IDIs). This systematic literature review identifies digital constraints from an IDI-centric perspective, which is currently lacking in the literature. This study also proposes a conceptual framework based on an Artificial Intelligence (AI)-enabled adaptive scaffolding intervention to reduce cognitive load, enhance digital self-efficacy, and improve system usability for IDIs. Within the broader context of Industry 5.0’s core principle of integrating human expertise with intelligent automation, this study proposes a theoretical digital transformation framework to achieve better organisational outcomes and reduce the marginalisation of the IDIs. Furthermore, this framework could support solutions to reduce the digital exclusion of nonindustrial digital immigrants, such as seniors, through its human-centric, adaptive, and cognitively supportive approach.
Comments
13-Design