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.