Enablers of artificial intelligence adoption and implementation in production systems
本研究识别并评估了影响生产系统中人工智能采纳与实施的12个关键推动因素，发现技术类因素比组织或环境因素更重要，其中项目管理最为关键，为管理者提供了优先关注点。
Artificial intelligence (AI) is considered a mechanism that can improve supply chain resilience. Organisations around the world are investing in implementing AI systems to improve their supply chain and become more resilient to pandemics and disruption. At the same time, practitioners are not fully aware of the factors that impact the implementation of these systems. Alongside this, the extant literature lacks a comprehensive study that evaluates the enablers impacting the implementation of AI in production systems. This research fills this gap by identifying, defining, and evaluating the critical enablers influencing the adoption and implementation of AI in production systems. We extracted twelve enablers, created a conceptual model, and categorised the enablers based on the Technology, Organization, and Environment (TOE) framework. After categorisation, we used the analytical hierarchy process to assess the importance of the enablers presented in the model using data collected from eight experts. The results revealed that technology, as a category, is more crucial than organisation or environment. The findings also indicated that project management is the most critical of all twelve enablers. We discuss the implications of the analysis for practitioners and researchers. We also offer twelve propositions that researchers can empirically assess in future studies.