Artificial intelligence (AI) is reshaping radiological practice, with recent advancements in natural language processing (NLP), large language models (LLMs), and chatbot technologies opening new avenues for clinical integration. These AI-driven conversational agents have demonstrated potential in streamlining patient triage, optimizing imaging protocol selection, supporting image interpretation, automating radiology report generation, and improving communication among radiologists, referring physicians, and patients. Emerging evidence also highlights their role in decision-making, clinical data extraction, and structured reporting. While the clinical adoption of chatbots remains limited by concerns related to data privacy, model robustness, and ethical oversight, ongoing developments and regulatory efforts are paving the way for responsible implementation. This review provides a critical overview of the current and emerging applications of chatbots in radiology, evaluating their capabilities, limitations, and future directions for clinical and research integration.