This blog post provides a comprehensive overview of generative AI's impact on the telecom industry, detailing theoretical foundations and practical applications, with a focus on large language models and their integration with telecom-specific data. It highlights the significance of retrieval augmented generation (RAG) in enhancing AI responses and discusses a successful real-world implementation of an RAG-based chatbot designed for addressing specific questions related to open radio access networks. The post concludes by noting the public availability of the chatbot on GitHub, reflecting significant industry interest.