 Drivers, barriers and social considerations for AI adoption in SCMJohannes Hangl, Simon Krause and Viktoria Joy Behrens Technology in Society, 2023, vol. 74, issue C Abstract: This study explored the challenges and recommendations for implementing Artificial Intelligence (AI) in SC Management (SCM). The experts identified several drivers for AI adoption in SCM, including increased efficiency, improved decision-making, and reduced costs. However, they highlighted several barriers to AI adoption, such as data quality and management issues, resistance to change, and lack of understanding and trust in AI. To overcome these barriers and ensure successful AI implementation, companies should involve all stakeholders, focus on data quality and management, and ensure the AI solution integrates with existing processes and workflows. In addition, companies should also avoid common mistakes when implementing AI, such as neglecting the importance of explainability and transparency in AI decision-making, underestimating the importance of involving all stakeholders, and rushing into large-scale implementation without conducting small-scale pilot projects. By following the recommendations and avoiding common mistakes, companies can harness the benefits of AI in SCM while minimizing risks and challenges. Keywords: Supply chain management; SCM; Artifiicial intelligence; AI (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:teinso:v:74:y:2023:i:c:s0160791x23001045 DOI: 10.1016/j.techsoc.2023.102299 Access Statistics for this article Technology in Society is currently edited by Charla Griffy-Brown More articles in Technology in Society from Elsevier |
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