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5 Ways To Use AI For Supply Chain Management - KDnuggets

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Supply chains have gotten increasingly more complicated to manage in recent years. Physical flows are becoming more interconnected and market volatility has increased the requirement for agility and adaptability. This has only been exacerbated by the COVID-19 pandemic which has seen an increased global demand for resources while juggling a variety of changing pandemic precautions. This is why using AI to help optimize supply chain management is becoming more prevalent across industries. Early adopters are more resilient and prepared for the inevitable future of artificial intelligence within the supply chain management industry.


5 Ways To Use AI For Supply Chain Management

#artificialintelligence

Supply chains have gotten increasingly more complicated to manage in recent years. Physical flows are becoming more interconnected and market volatility has increased the requirement for agility and adaptability. This has only been exacerbated by the COVID-19 pandemic which has seen an increased global demand for resources while juggling a variety of changing pandemic precautions. This is why using AI to help optimize supply chain management is becoming more prevalent across industries. Early adopters are more resilient and prepared for the inevitable future of artificial intelligence within the supply chain management industry.


Using AI to Solve Complex Global Supply Chain Management Challenges - Liwaiwai

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Companies are starting to apply artificial intelligence across global supply chain management to improve efficiency, speed and decision-making in areas such as supply chain planning, warehouse automation, and logistics. The SCM World 2016 Future of Supply Chain Survey found that the importance of artificial intelligence has grown rapidly, with 47 percent of supply chain leaders believing the technology is disruptive to global supply chain management strategies. Market-research firm IDC predicts that by 2020, 50 percent of mature supply chains will use AI and advanced analytics for planning, and to eliminate sole reliance on short-term demand forecasts. Supply chain planning and optimization, including demand forecasting, are among the key areas where AI is already beginning to be deployed. Experts say that global supply chains have become so complex, and are affected by so many variables, that AI may be essential to help identify and predict problems and potential solutions.


Demand Forecasting Methods: Using Machine Learning and Predictive Analytics to See the Future of…

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What is the top pain point for business executives? Gartner, the world's largest IT research firm, gives a clear answer: demand volatility. Too many factors from weather fluctuations to posts by social media influencers -- impact buyers, causing them to frequently change their minds. Worse still, things reshaping customer intentions happen quite unexpectedly. Think, for instance, of the teenage climate activist Greta Thunberg.


Nine ways machine learning can improve supply chain management

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Efficiency and cost-effectiveness are the biggest challenges facing supply chain management today. Businesses are continually striving to reduce costs, enhance profit margins, and provide exceptional customer service. In such a competitive market, disruptive technologies like Machine Learning (ML) and Artificial Intelligence (AI) have opened up exciting opportunities for companies. Are you grabbing these opportunities? Artificial Intelligence and Machine Learning have recently become buzzwords across different verticals, but what do they mean for modern supply chain management?