INTELLIGENT DATA VISUALIZATION AND DASHBOARD AUTOMATION USING AI

Abstract

This review paper discusses the growing role of AI-based automation in data preparation, visualization, and dashboard generation. It examines how modern approaches are addressing challenges such as manual data cleaning, static dashboards, and limited language support. Recent systems increasingly use large language models (LLMs), agent-based AI, and generative AI techniques to build intelligent, interactive, and explainable analytics platforms. The paper highlights recent research in areas such as multilingual natural language to visualization (NL2VIS), agent-based data processing pipelines, automated insight generation, and adaptive chart recommendation systems. A comparative analysis identifies emerging trends including personalization, improved explainability, and stronger collaboration between humans and AI systems. At the same time, several challenges remain, including issues related to scalability, data quality management, and domain-specific adaptation. The study concludes by outlining future research directions for AutoDashAI, including the development of fully autonomous analytics pipelines, support for additional languages, and the creation of dashboards that are both ethically responsible and easily interpretable.