Artificial intelligence has initiated a new technological revolution, utilizing operational data from various devices and cloud applications to generate valuable insights. The applications of AI in supply chain management have been gaining attention from experts.
The primary reason for using AI in supply chain management is to improve efficiency, decision-making, and overall processes. SCM can benefit from AI by reducing logistics costs, improving service excellence, and elevating inventory levels. However, there are some setbacks to using AI in SCM applications.
The ideal roadmap for implementing artificial intelligence in supply chain management involves embracing AI technology to develop smarter supply chains that are instrumented, intelligent, and interconnected. AI uses advanced mathematics and data analytics to create adaptable and learning products, systems, and processes.
During the global pandemic in 2019, AI played a major role in digitalizing supply chain operations when traditional methods faced bottlenecks. AI has the capability to manage large volumes of data, make predictions, and establish connections between multiple data sources.
Early adopters of AI in supply chain management have successfully reduced logistics costs by 15% and improved service excellence by almost 65%. By embracing AI on a larger scale, supply chain management can revolutionize efficiency, decision-making, and processes.
The interplay between AI and supply chain management can enhance inventory management, real-time delivery controls, smart manufacturing, and dynamic logistics systems. AI helps in ensuring better productivity, efficiency, and sustainability in supply chain operations.
AI can provide prediction, analysis, and automation to facilitate comprehensive visibility in supply chains. It can also help in real-time monitoring of perishable items, inventory management, and automation of supply chain operations. Data analytics powered by AI can enhance decision-making in supply chain management, offering valuable insights and predictions for optimizing workflow and improving efficiency.
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