Rethinking Inventory Intelligence: A Conceptual Model in Adopting AI-Based Demand Forecasting within Malaysian Retail Supply Chains

Artificial Intelligence (AI) is increasingly transforming global supply chain practices, particularly in demand forecasting, where traditional methods often fall short in capturing dynamic market complexities. Despite growing awareness of AI’s potential, many Malaysian retailers continue to rely on manual or historical trend-based forecasting methods. This often leads to inefficiencies, including stock imbalances, overstocking, and poor responsiveness to shifting consumer demand. Government-led initiatives such as the Malaysia Digital Economy Blueprint and the National AI Roadmap aim to close this digital gap, yet significant readiness barriers remain including lack of infrastructure, skill shortages, and limited strategic alignment. Thus, this conceptual study explores the integration of AI-based demand forecasting into inventory decision-making processes within Malaysian retail supply chains. Grounded in the Resource-Based View (RBV) and Technology–Organization–Environment (TOE) frameworks, the research aims to identify key enablers, practices, and expected impacts of AI adoption, while accounting for Malaysia’s unique technological, organizational, and policy landscape. This study proposed a conceptual framework that highlights the interaction between critical stakeholders (e.g., retail managers, inventory analysts), enabling conditions (e.g., digital infrastructure, organizational culture), and core practices (e.g., automated demand forecasting, AI-driven replenishment planning). Expected outcomes include improved forecast accuracy, enhanced inventory responsiveness, and greater supply chain agility. As this study adopts a constructivist qualitative approach, it also remains open to the emergence of new themes during empirical investigation to ensure that context-specific insights and lived experiences are fully captured. Ultimately, this research contributes to the limited body of knowledge on AI adoption in Malaysian retail and provides a foundation for future empirical inquiry. By contextualizing global best practices within Malaysia’s retail environment, it offers practical insights to guide policymakers, retail leaders, and technology adopters in building intelligent, resilient, and future-ready inventory systems.