Published Paper Details:

Artificial Intelligence (AI) has become a transformative force in the retail sector, particularly through its applications in predictive analytics for inventory optimization and marketing performance. This study explores how AI-driven tools enhance inventory accuracy, supply chain responsiveness, and marketing outcomes in the retail ecosystem of India. Using survey data from 120 retail managers across Tier-1 and Tier-2 cities, combined with secondary analysis of industry case studies, this research evaluates the relationships between AI-enabled inventory decisions and marketing performance indicators such as sales, promotions, and return on investment (ROI). Statistical methods including percentage analysis, Chi-square tests, and ANOVA were applied. The findings show that AI adoption significantly improves inventory accuracy, reduces stockouts, and enhances supply chain efficiency. Further, AI-driven decisions positively correlate with sales performance and promotional effectiveness. However, challenges such as data integration, cost of implementation, and workforce readiness remain barriers to widespread adoption. The study concludes that successful AI adoption in retail requires both technological investment and organizational adaptation, offering insights for retail managers aiming to build resilient and customer-focused operations.