Impact of Artificial Intelligence on Supply Chain Efficiency in Turkey

Purpose: The aim of the study was to evaluate the impact of artificial intelligence on supply chain efficiency in Turkey. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: Artificial intelligence (AI) has significantly enhanced supply chain efficiency in Turkey. AI applications such as predictive analytics, demand forecasting, and optimization algorithms have streamlined operations, reduced costs, and improved decision-making. Automation of repetitive tasks through AI has increased productivity and accuracy in inventory management and logistics. Unique Contribution to Theory, Practice and Policy: Resource-based view (RBV) theory, dynamic capabilities theory & technology acceptance model (TAM) may be used to anchor future studies on the impact of artificial intelligence on supply chain efficiency in Turkey. Invest in continuous training and development programs for supply chain professionals to effectively utilize AI tools. Develop industry standards and regulatory frameworks for the ethical use of AI in supply chains. These policies should address data privacy, security, and the responsible use of AI technologies to protect stakeholders.