In today's rapidly evolving economy, the adoption of artificial intelligence (AI) within supply chain management (SCM) has emerged as a key area of study. The integration of AI technologies into SCM systems presents a transformative opportunity for organizations seeking to enhance operational efficiency, reduce costs, and establish a competitive advantage in a dynamic market. AI technologies—ranging from machine learning algorithms to predictive analytics—serve as pivotal tools in addressing these challenges. By automating routine tasks, forecasting demand with greater accuracy, and facilitating real-time decision-making, AI enhances responsiveness and agility within supply chains. The economic benefits of incorporating AI into SCM frameworks are substantial. Implementing AI-driven solutions can lead to significant cost savings through improved inventory management, reduced waste, and enhanced resource allocation. For instance, machine learning models can predict stock requirements more accurately, minimizing excessive inventory and associated holding costs. Additionally, AI enhances supplier relationship management by analyzing vendor performance data, leading to more informed selection processes and negotiation strategies. As the field continues to evolve, it is crucial for professionals to engage with emerging technologies, ensuring that they remain competitive and responsive to the demands of an ever-changing market landscape. This study reviews the literature to determine why supply chain management (SCM) needs to adopt artificial intelligence (AI) in terms of integrative tactical planning, resource utilization and cost reduction, risk management, data management and inventory management. The aim of this study was to encourage professionals to investigate the possibilities of AI technology to enhance several elements of the supply chain.