Human-Centric AI in BI: Enhancing user experience through interactive data visualization

Madabhushini, Indraneel (2025) Human-Centric AI in BI: Enhancing user experience through interactive data visualization. World Journal of Advanced Research and Reviews, 26 (1). pp. 877-887. ISSN 2581-9615

This article examines the transformative impact of human-centric AI approaches on business intelligence visualization systems across multiple sectors. It explores how organizations can extract meaningful insights from their data by designing visualization systems that augment rather than replace human decision-making capabilities. The inquiry analyzes the foundational principles of human-centric AI in business intelligence, including cognitive resonance, semantic interaction, and bidirectional feedback mechanisms. Through evaluation of implementations in healthcare, manufacturing, and methodical analysis environments, the article identifies key technical methods that have proven successful in each domain. The work further addresses critical technical challenges in balancing complexity with usability, ensuring real-time performance, and integrating with existing enterprise systems. Finally, the article explores emerging directions in the field, including multimodal interaction, ambient intelligence, federated learning for privacy preservation, and neuroadaptive interfaces that respond to human cognitive states. By focusing on the complementary strengths of human intuition and machine intelligence, these frameworks deliver visualizations that are not only accurate but also actionable and intuitive.