Artificial intelligence as a strategic lever for enhancing performance in service sector supply chains: a systematic literature review - Badre, El Mehdi; Sidouna, Slimane; Chahbar, Hind; Mrabti, Adnane; Lahrech, Abdelali (Business, Management and Economics Engineering, 2026)
Purpose – this study was undertaken through a systematic literature review to identify the central role of Artificial Intelligence (AI) in improving supply chain performance across all service sectors. Research methodology – a dual methodological approach was used involving both quantitative and qualitative analysis. The former is largely based on a bibliometric analysis of 61 peer-re- viewed articles published between 2019 and 2024. In this respect, two software tools, RStudio and VOSviewer, were used to provide a comprehensive bibliometric landscape. The second concerns a thematic content analysis of 25 full-text studies, focusing on AI techniques, performance results and industry-specific implementation challenges. Findings – the overall result of this systematic review indicates that AI contributes to service supply chain performance by improving forecasting, resilience, operational efficiency and real-time decision-making. Research limitations – however, limitations such as data availability, system interoperability, ethical risks and organizational resistance remain important. Practical implications – the results of this study help practitioners to select AI solutions suitable for their sector and to anticipate obstacles to integration. Originality/Value – this study provides a better understanding of how AI is reshaping supply chains in service industries, while identifying key avenues for both future research and practical adoption.