AI-driven data visualization: Enhancing user interfaces with machine learning

Deshwal, Priyanshi (2025) AI-driven data visualization: Enhancing user interfaces with machine learning. World Journal of Advanced Engineering Technology and Sciences, 15 (2). pp. 2176-2182. ISSN 2582-8266

[thumbnail of WJAETS-2025-0704.pdf] Article PDF
WJAETS-2025-0704.pdf - Published Version
Available under License Creative Commons Attribution Non-commercial Share Alike.

Download ( 498kB)

Abstract

AI and machine learning technologies are transforming data visualization, offering solutions to the challenge of deriving insights from increasingly complex datasets. This article explores how these technologies enhance user interfaces through automated visualization recommendations, personalized dashboards, real-time predictive analytics, and natural language interfaces. By analyzing implementation considerations across technical, design, and strategic dimensions, the article demonstrates how AI-driven visualization tools improve efficiency, accuracy, and accessibility. A case study of a financial services institution illustrates these benefits, while an exploration of future trends—including augmented analytics, multimodal interaction, embedded intelligence, and collaborative intelligence—reveals the evolving landscape of data visualization. These innovations are making analytics more intuitive and impactful, allowing organizations to process information more effectively in an era of exponential data growth.

Item Type: Article
Official URL: https://doi.org/10.30574/wjaets.2025.15.2.0704
Uncontrolled Keywords: Augmented Analytics; Collaborative Intelligence; Data Visualization; Machine Learning; Natural Language Interface
Depositing User: Editor Engineering Section
Date Deposited: 04 Aug 2025 16:39
Related URLs:
URI: https://eprint.scholarsrepository.com/id/eprint/4042