In an increasingly competitive industrial landscape, digital transformation is essential for sustaining performance, with Artificial Intelligence (AI) positioned as a core technology of Industry 4.0. While research has highlighted the transformative role of AI, its specific contributions to Operational Excellence (OpEx) within Operations Management (OM) remain underexplored. Existing reviews group AI with broader digital technologies or address its adoption drivers, but few systematically examine how AI is practically applied to achieve excellence. To address this gap, this study conducts a systematic literature review to capture and classify AI-driven OpEx applications within OM in the manufacturing sector. 67 peer-reviewed articles were analysed, mapping where AI is most frequently applied across operational domains and clarifying the functions through which it contributes to excellence. The resulting classification framework bridges theory and practice, offering scholars a structured research agenda and providing managers with actionable insights on how to leverage AI for OpEx in manufacturing.
Martuscelli, L., Fantozzi, I.c., Leoni, L., Schiraldi, M.m. (2026). Artificial intelligence for operational excellence in operations management: a systematic literature review and classification framework in manufacturing. PRODUCTION PLANNING & CONTROL, 1-37 [10.1080/09537287.2026.2638482].
Artificial intelligence for operational excellence in operations management: a systematic literature review and classification framework in manufacturing
Martuscelli, L
;Fantozzi, I C;Schiraldi, M M
2026-03-10
Abstract
In an increasingly competitive industrial landscape, digital transformation is essential for sustaining performance, with Artificial Intelligence (AI) positioned as a core technology of Industry 4.0. While research has highlighted the transformative role of AI, its specific contributions to Operational Excellence (OpEx) within Operations Management (OM) remain underexplored. Existing reviews group AI with broader digital technologies or address its adoption drivers, but few systematically examine how AI is practically applied to achieve excellence. To address this gap, this study conducts a systematic literature review to capture and classify AI-driven OpEx applications within OM in the manufacturing sector. 67 peer-reviewed articles were analysed, mapping where AI is most frequently applied across operational domains and clarifying the functions through which it contributes to excellence. The resulting classification framework bridges theory and practice, offering scholars a structured research agenda and providing managers with actionable insights on how to leverage AI for OpEx in manufacturing.| File | Dimensione | Formato | |
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