The deployment of Product Lifecycle Management (PLM) software is complex in several respects. The software is expensive, complex and more akin to a macro-work environment through which everything passes than to the old, simple computer-aided design software. However, many solutions exist to improve software adoption, including digital adoption platforms (DAPs). These are software applications that are embedded in the interface of others to guide the user through tasks, with integrated tutorials, input aids and pop-ups. One inescapable difficulty is the sheer number and diversity of users. This entails many guides, hence the need to use generative and automatic systems. In this context, we propose in this study a method for deploying PLM software assisted by a DAP and generative models using AI. The aim of this study is to complete the state of the art with real deployments and present a demonstration case with a prototype, to explore and observe the variations in terms of stability, precision and production capacity between the different configurations. The complementary objective is to outline the issues involved in learning a PLM-type business software package, as well as those involved in industrial software deployment.