The latest advances in Industry 5.0/6.0 paradigms are driving the more advanced use of generative artificial intelligence (genAI) in AI-based digital twins (DTs). This approach allows for the automatic collection and selection of data resources acquired by AI-based digital twins (DTs) and their use to generate a variety of documents useful in automated production processes and the supply chain. This provides greater flexibility and scalability of the solutions used, as well as the ability to further aggregate data from DTs over time (for change monitoring and predictive maintenance) and from multiple DTs simultaneously (e.g., from production line quality control points). From an operational perspective, this also ensures faster event handling and a broader selection of pre-prepared scenarios within the operator-cyber-physical system interface than traditionally possible. These genAI solutions represent another step toward supporting operators of complex industrial processes and systems, especially those operating under multiple constraints. The contribution to knowledge of this article is the development of genAI applications in technological transformation technologies in such a way as to facilitate the creation of human-centric, self-evolving technological transformation ecosystems aligned with the goals of sustainability, resilience, and cognitive autonomy of Industry 5.0 and 6.0.