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AI and ML Adoption Surges in High-Growth Supply Chains

Epicor Study Finds, High-Growth Supply Chain Businesses Adopting AI and ML at Faster Pace than Competitors

According to the 2024 Agility Index research study from Epicor and Nucleus Research, nearly half of surveyed companies across the make, move, and sell industries cited concern over escalating costs as the foremost challenge confronting supply chains. More than half are using artificial intelligence, automation, or machine learning for at least one supply chain management application to address this. Notably, a higher percentage of businesses (63 percent) that identify as high-growth — defined by revenue growth of 20 percent or more over the past three years — have already integrated generative AI into their respective supply chain operations to manage cost and operational challenges.  

Nucleus Research surveyed more than 1,700 supply chain management leaders worldwide to understand how they are leveraging powerful technologies like artificial intelligence and machine learning to thrive while navigating challenges like supply chain disruptions, escalating costs, and skilled labor gaps. The study also uncovered anticipated future investments in these technologies. 

Survey respondents indicated they are integrating generative AI into digital supply chain operations across various functions such as product descriptions, customer service chatbots, natural language querying, reporting, and in-application assistance. Specifically, the adoption of generative AI in customer service chatbots, noted by 72 percent of organizations, is highlighted as the most prevalent use case. This widespread implementation is attributed to the technology’s ability to streamline customer interactions across various sectors.  

Similarly, 67 percent of organizations currently employ generative AI for crafting product descriptions, leveraging the technology’s capacity to analyze customer sentiment and forecast market demand. This enables a more informed approach to product design and feature development. 

Businesses are also implementing machine learning most frequently in inventory optimization (45 percent) and demand forecasting (40 percent), underlining the critical role of these technologies in managing inventory levels and accurately predicting future demand. 

According to survey respondents, the greatest hope for the impact of automation technologies lies in increased efficiency and productivity (32 percent), cost savings (26 percent), and improved supply chain automation (23 percent). This reflects a strong belief in the potential of these technologies to drive significant improvements in supply chain management. 

To download a copy of the 2024 Agility Index, please visit our website

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