Backlog refinement is a critical process within Agile practices which often faces challenges like ambiguous user stories, prioritization difficulties, and cognitive overload among team members. Teams spend a lot of time in grooming user stories and refining them based on the client or business requirements and customer feedback. In this paper, we present an empirical study, exploring the integration of Generative AI (GenAI), specifically Large Language Models into backlog refinement workflows to address these challenges.