This study provides a literature review on data mining, artificial intelligence (AI) and supply chain inventory forecasting which is the subject of this paper. Using a mixed-method approach, this paper investigates the strategic significance of these technologies in improving accuracy of forecasts and agility in operations. The study uses a hybrid of thematic and quantitative analysis of interviews and data patterns from SCM professionals to identify the advantages and disadvantages of AI and data mining in-order-fulfillment and inventory management. Results indicate that AI and data analytics tools are effective at handling complex demand patterns; however, implementation barriers—mostly data quality, IT system integration, and workforce capabilities—exist to fully benefit from it. This research study will provide valuable recommendations to companies who have intentions of future use of AI and data mining for the purposes of inventory forecasting along with avenues for future research in SCM technology.