Abstract

This study explores the role of data-driven methodologies, specifically AI and analytics, in enhancing business agility within product management. As companies increasingly face rapid market shifts and evolving customer demands, the need for agile and data-centric product management has grown. Through a mixed-methods approach involving case studies and surveys, this research examines how AI tools—such as predictive analytics, machine learning, and natural language processing—support product teams in making real-time decisions, improving customer insights, and aligning product roadmaps with market trends. Key findings reveal that AI-driven product management enhances customer-centricity, reduces time-to-market, and fosters cross-departmental collaboration, significantly improving business agility. However, challenges such as data quality, AI expertise gaps, and data privacy concerns pose barriers to effective implementation. This study concludes that embracing data-driven practices is essential for product teams aiming to stay agile and competitive in today’s digital landscape, and it calls for further research into industry-specific applications and ethical considerations in AI-driven product management