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AI-Powered Dashboards: Integrating Visualization and Machine Learning for Enhanced Insights

Year: 2026

Type: article

Abstract: Modern data analytics is undergoing a paradigm shift with the integration of artificial intelligence into visualization systems. Traditional dashboards primarily focus on descriptive analytics, limiting their ability to provide proactive insights. AI-powered dashboards extend these capabilities by incorporating predictive analytics, anomaly detection, and automated recommendation systems. This paper explores the design, development, and evaluation of intelligent dashboards that leverage machine learning techniques to enhance decision-making processes. The study presents an expanded framework that combines visualization, adaptive interfaces, and AI-driven automation to transform raw data into actionable insights. The proposed approach highlights scalability, real-time processing, and user-centric adaptability as key components of next-generation analytics platforms. Keywords — Artificial Intelligence, Data Visualization, Machine Learning, Predictive Analytics, Smart Dashboards

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.19822552

Authors: Thote, Ved, Tripathi, Vibhaw, Hiremath, Vishwanath, Gurav, Raju

Institution: MIT Art, Design and Technology University

Language: English

Topic: Data Visualization and Analytics

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W7156333799

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