Artificial Intelligence and Machine Learning in Supply chain
ABSTARCT :
The modern supply chain has evolved into a dynamic, data-driven ecosystem that demands real-time responsiveness, agility, and strategic foresight. In this transformative landscape, Artificial Intelligence (AI) and Machine Learning (ML) have emerged as powerful technologies reshaping how supply chains operate, adapt, and innovate. These technologies are redefining decision-making by enabling machines to analyze vast amounts of data, recognize patterns, learn from historical events, and make predictions with increasing accuracy. As businesses navigate volatile markets, unpredictable demand, and global disruptions, AI and ML provide the intelligence necessary to forecast trends, optimize logistics, improve inventory management, and reduce operational costs.
Artificial Intelligence and Machine Learning are no longer futuristic concepts—they are practical tools with real-time applications in sourcing, production, distribution, and customer service. From automating repetitive tasks such as order processing and demand planning to enabling advanced solutions like predictive analytics and autonomous delivery systems, these technologies are contributing to the creation of smarter, more resilient supply chains. AI-driven algorithms can quickly adjust procurement decisions based on supplier performance, lead times, or raw material prices, while ML models can identify inefficiencies or fraud that might go unnoticed through manual processes.
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