AI-generated from publicly available materials.Cencora is leveraging artificial intelligence to enhance its demand forecasting capabilities in the pharmaceutical sector, achieving a notable 10% improvement in accuracy.
The company, represented by Matt Sample, highlights the limitations of traditional supply chain data, particularly the absence of real-time point-of-sale information that is common in consumer markets. To address this gap, Cencora has implemented an AI tool that analyzes historical forecasts alongside current ordering patterns. This system not only identifies discrepancies in demand but also provides insights into the reasons behind these variations, allowing for more informed decision-making.
Currently, the AI tool is employed by a select group of buyers and focuses on a limited range of stock-keeping units (SKUs). The early results are promising, indicating that the tool can help optimize inventory levels, either by ensuring adequate stock or reducing excess from over-purchasing. Additionally, Cencora is exploring the use of knowledge graphs to assess risk factors related to market shortages, linking data from manufacturers and regulatory actions.
This proactive approach is increasingly critical, especially as the number of active drug shortages continues to rise. With 227 reported shortages in the second quarter of 2026, Cencora’s AI-driven insights could play a vital role in mitigating supply chain disruptions.