AI in Predictive Analytics: EnhancingDecision-Making in Retail andHealthcare

Abstract

This paper explores the transformative role of Artificial Intelligence (AI) inpredictiveanalytics, specifically within the retail and healthcare sectors. As organizations increasinglycontendwith vast datasets, AI algorithms provide innovative solutions for forecasting trends, enhancingoperational efficiency, and improving decision-making processes. Through a comparativeanalysisofcase studies from retail and healthcare, we illustrate how AI-driven predictive modelsenablebusinesses to anticipate customer behavior, optimize inventory management, andpersonalizemarketing strategies in the retail landscape. In healthcare, we highlight the applicationof predictiveanalytics in patient outcome forecasting, resource allocation, and disease outbreak prediction. Ourfindings underscore the potential of AI to not only increase accuracy in predictions but alsotofosterproactive strategies that enhance performance and patient care. The paper concludes bydiscussingthe challenges of integrating AI solutions, including data privacy issues and the needforskilledpersonnel, while advocating for future research to develop frameworks that maximize thebenefitsofAI in predictive analytics across sectors