Automated data visualization hands over the decision to Ai to decide the appropriate visualization types, such as bar charts, scatter plots, or heatmaps, to represent the information effectively. This automation accelerates the data exploration process and enables actuaries to quickly identify patterns, trends, and anomalies. NLP techniques are now being deployed by actuaries. Natural Language Processing (NLP) tools extract key insights from textual data, such as customer reviews, social media posts, or insurance claims descriptions. AI can automatically analyze and summarize text, identify sentiment, extract relevant keywords, and visualize textual data through word clouds or sentiment analysis charts, providing valuable insights for decision-making. Interactive Visualizations or AI-powered visual analytics tools can create interactive dashboards and reports that allow actuaries to explore data dynamically. Actuaries can interact with visualizations by filtering data, drilling down into details, and changing parameters. AI algorithms enable real-time updates and responsiveness, allowing users to gain immediate insights and adjust visualizations on the fly. Pattern Recognition and Anomaly Detection: AI algorithms can identify complex patterns and outliers in large datasets, which can be challenging for humans to detect manually. In visual analytics, AI can automatically highlight clusters, trends, and anomalies in the data and these techniques are helping actuaries to uncover hidden patterns or identify potential risks and opportunities, enhancing their decision-making capabilities