ISSN: 2222-6990
Open access
Malaysia’s rapidly growing data centre sector has led to significant advances in the application of artificial intelligence (AI) in small-to-medium data centres (SMDCs), however there is dearth of research examining the workforce implications of this transformation. Grounded in conservation of resources (COR) theory and social identity theory (SIT), this paper provides a conceptual framework by utilising these theoretical foundations to understudied context of Malaysian SMDCs. The framework centres on a structural condition, deskilling-yet-oversight paradox, wherein AI-induced systems concurrently displace operators' expertise while elevating their accountability as supervisors of automated systems. This condition documented in analogous industries has not been examined in the data centre context. This paper proposes role identity erosion as mediator linking automation exposure to AI-induced technostress. Moreover, a moderating distinction between substantive human-in-the-loop (S-HITL) and nominal human-in-the-loop (N-HITL) arrangements is applied to study how oversight quality affects operator’s identity and technostress in this context. This paper derives five propositions for future empirical testing. An institutional argument is advanced to explain why nominal oversight is the likely structural default in Malaysian SMDCs. Three HRM intervention pathways are proposed to convert the default N-HITL into S-HITL. The paper contributes to literature by providing theoretically integrated framework for understudied Malaysian SMDCs.
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