Data storytelling is an interdisciplinary approach that combines data analysis, visualization, and narrative to enhance comprehension and engagement with data-driven insights. While traditional data visualization methods focus on graphical representation, data storytelling aims to contextualize information, transforming abstract datasets into meaningful and persuasive narratives. Despite its growing relevance in various domains, including marketing, journalism, and business intelligence, research on data storytelling remains fragmented, particularly concerning its automation and integration with artificial intelligence (AI). This study explores the role of ChatGPT in facilitating data storytelling, addressing the gap in literature regarding its potential to automate narrative generation and improve data interpretation. The study follows a mixed-methods approach, combining a systematic literature review with experimental case studies where ChatGPT generates narrative-driven insights from structured datasets. The results show that ChatGPT makes data storytelling easier to understand and more flexible by giving explanations in context, finding patterns, and creating coherent stories that are fit for different audiences. However, challenges remain regarding the accuracy, ethical implications, and limitations of AI-generated content. The study concludes that AI-assisted data storytelling is a promising step forward, but it still needs to be supervised by a person to make sure it is reliable and appropriate for the situation. Future research should further investigate the integration of AI with interactive storytelling frameworks to enhance engagement and decision-making.