Year: 2025
Type: article
Abstract: This study explores how artificial intelligence (AI), specifically machine learning (ML), transforms Decision Support Systems (DSS) from descriptive tools into predictive and prescriptive engines for strategic decision-making. Using a case study in the retail sector, structured (sales, financials) and unstructured (reviews, social media) data were analyzed through supervised learning, natural language processing, and reinforcement learning models. Findings show improved predictive accuracy, customer retention, and sustainable pricing strategies compared to traditional IS/MBAs frameworks. The research contributes theoretically by extending DSS and IS literature, and practically by providing business leaders with actionable, AI-driven frameworks for long-term strategic agility.
Author: Osita Victor Egwuatu
Institution: University of Toledo
Language: English
Subfield: Management Information Systems
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W4413835012