Investigating User Perceptions of Generative AI for Data Storytelling

Data storytelling combines narrative techniques with data visualisation to present complex information in an engaging and actionable manner. Recently, the potential use of Generative Artificial Intelligence (AI) in data visualisation and storytelling has gained attention but has seen limited empirical evaluation. This study addresses this gap by investigating whether Large Language Models (LLMs) can effectively assist individuals in crafting data-driven stories. To assess this, we designed a three-stage survey that captures participants' initial perceptions of Generative AI tools, followed by a hands-on activity where participants create data stories using LLMs, and concludes with a post-activity survey to evaluate changes in their attitudes. Our findings indicate that individuals with prior experience using Generative AI are more inclined to adopt these tools for data storytelling. However, those who have specifically used LLMs for visualisation purposes exhibit less enthusiasm towards adoption, potentially due to prior challenges or limitations encountered. Additionally, participants found Generative AI tools particularly useful in the initial stages of data storytelling, especially when identifying the target message. Importantly, we observed a significant positive shift in participants' likelihood to adopt Generative AI following hands-on experience. These insights highlight the potential of Generative AI in enhancing data storytelling processes and highlight opportunities for improved human-AI collaboration, particularly within Business Analytics.