Generative Artificial Intelligence (GAI) presents significant potential for managing Industry 4.0 companies performance, driving efficiency, reactivity and innovation and enhancing thus the performance. However, despite its advantages, the use of GAI also has several limitations, notably regarding the focus on the short-term techno-centric vision of performance and the associated ethical issues. Moreover, ethical issues that may concern numerous aspects such as data privacy, human dependence, motivation or loss of autonomy can be a threat to the overall vision of performance, particularly in the long term, as the other elements that underlie it are neglected, namely the social and the environmental ones. Aware of the importance and the benefits of using GAI, companies are looking for operational solutions that enable them to ensure long-term performance while avoiding ethical risks. Therefore, the idea put forward in this paper subscribes to the assumption that ethics in use of advanced technologies is a necessary condition for performance. Then, in keeping with performance, the use of GAI must be coupled with management of the associated ethical risks. In this sense, an exploratory analysis is proposed, from data management situations experienced by a bearing manufacturer, partner in this study. Digitalizing its manufacturing for a few years, the Company is facing cases where considering ethics becomes necessary. Hence, associated ethical risks are presented as well as their potential impact on the (efficiency-effectiveness-relevance) performance conditions, in the short, medium and long term, leading thus to the discussion of deontological rules to put in place when using GAI in performance management.