Green hydrogen energy plays vital role in future sustainable development of fuel and environmental impact such as reduction in carbon emission leads. Investigate the past and current trends in research and commercial hydrogen related aspects including energy production, methods, economy, applications etc, are important for future research direction and development in both laboratory and industrial scale production of green hydrogen energy. Generative Artificial Intelligence (i.e. Generative AI) is an artificial intelligence technology and algorithms used to create new content including image, audio, video etc. Historic datasets related to those contents are the fuel/source for Generative AI in order to create new content. In this study, we create automatic pipeline to extract massive hydrogen related datasets from common, journals and preprocess it and also developed dynamic unsupervised algorithm to analysis the historic trends in hydrogen. Also developed Generative Adversarial Networks (GAN) and discussed the potential way to use generative AI for future hydrogen energy research and commercial development. We acknowledge Big Data Science & Technology Limited and Space 4.0 Limited for Funding Support
