Use Cases of Generative AI in Asset Management of Railways

Asset management of railways is a data-driven process. Empowering asset management through utilisation of Artificial Intelligence (AI) and digital technologies for data-driven fact/based decision-making is highly dependent on the availability and accessibility of data. Additionally, data-driven approach puts demands on the quality of data and the relevance of the datasets to the contexts of analytics. This is to ensure the accuracy of the analytics and the precision of the predictions. One of the emerging approaches that can be utilised to augment data used for analytics and model learning process is Generative Artificial Intelligence (GAI). GAI can be useful in the various contexts of asset management of railways. This paper aims to provide some use cases in which GAI can be utilised for e.g. data augmentation that will lead to an improved accuracy and precision of decision-support. The identified use cases will provide a list of potential areas that can be used to develop a roadmap for implementation of GAI within the asset management of railways.