The digitization of industrial operations and manufacturing has transformed factories through automation and model-based approaches, driving advancements in areas like additive manufacturing, augmented reality, and simulation. While these technologies have significantly enhanced industrial processes, artificial intelligence (AI) has yet to be fully integrated as a central component. Emphasizing the importance of human involvement alongside technological innovation, AI applications are particularly vital in areas such as robotics, where human-centric approaches are key. Despite its widespread use in consumer-focused services, trust in AI remains a major concern in industrial settings. Initiatives such as the European Union’s Trustworthy AI guidelines and the EU Act aim to foster trust in AI while ensuring ethical implementation and worker safety. However, many organizations remain unaware of the need for specific approaches to effectively address trust concerns in AI systems. This work explores the principles required for building trustworthy AI systems for industrial operations and manufacturing and challenges of trustworthy AI.