A Decision Process for the Applications of Artificial Intelligence in Sustainable Operations and Supply Chain Management Reza Akbar Muhammad, Benny Tjahjono, Babul Salam KSM Kader Ibrahim, Sri Rachmi Karimah Dewi Ridlo Coventry University Coventry, CV1 5FB, UK rezaakbr@uni.coventry.ac.uk, benny.tjahjono@coventry.ac.uk, ad1465@coventry.ac.uk, ridlos@uni.coventry.ac.uk Tri Yogi Yuwono Institut Teknologi Sepuluh Nopember Surabaya, Indonesia triyogi@me.its.ac.id Abstract Artificial Intelligence (AI) has a growing and wider presence in academic studies and this presence has affected many fields, such as business research, which has picked up on the subject, and AI is now researched from a more holistic perspective, with operations and supply chain management being recognised as one of the areas that is most likely to benefit from AI applications. In addition, many companies have pushed towards using AI in their supply chain processes in order to achieve sustainability. The influence of AI inevitably extends well beyond the production line. It refers to all business units involved in planning, manufacturing, transporting and selling goods. As a result, companies will need engineering business managers who are well-equipped with know-how of the technological changes that may affect their market and workplace in order to effectively navigate them. This paper proposes a framework that can be used as decision making tools, providing steps for practitioners to consider before and after implementing the AI techniques in their engineering businesses. The framework was developed considering the barriers, enablers and challenges of AI implementation. Keywords Artificial Intelligence, Operations, Supply Chain Management, Sustainability, Engineering Management 1. Introduction Operations and supply chain management (OSCM) has played a significant role in the global business world in recent decades. It has become an important part of business and fundamental for customer satisfaction in many sectors such as agriculture, manufacturing, energy, food industry and even the public sector. However, intelligent processes and practices in OSCM pose numerous problems and challenges in terms of sustainability. Bové and Swartz (2016) reported that the supply chain (SC) of a goods and services company affects both social and environment aspects, accounts for 90% of the impact on land, air, water and biodiversity, and more than 80% of greenhouse gas emissions in consumer goods, such as food industry, textile and electronic equipment produced in the SC. Thus, studies have been conducted to mitigate these issues. Furthermore, several methods and tools have been used in order to minimise and reduce the sustainability risk and one of these methods is using the Artificial Intelligence (AI). AI is a field study in science and engineering that defines machine learning capability that has similarities to humans to adapt under certain situations and circumstances, and the ability to respond to certain orders, actions and behaviours as well as detect and extrapolate patterns (Russell and Norvig 2016). Within the context of the SC, in order to attain sustainability, the term ‘artificial intelligence’ has been widely used by both industrial practitioners and scholars. AI is now being studied from a more comprehensive viewpoint, considering SCM as one of the area that most likely to benefit from applications of AI. Moreover, in order to achieve sustainability, many businesses have moved towards Proceedings of the 11th Annual International Conference on Industrial Engineering and Operations Management Singapore, March 7-11, 2021 © IEOM Society International 5071