Analyst Insight: With recent disruptions such as the pandemic and hurricanes accounting for billions of dollars in damages, the need for creating a more resilient supply chain network with greater visibility and connectivity has increased. Artificial intelligence (AI), machine learning (ML) and data analytics have proven to be innovative solutions to these challenges and have the potential to transform supply chains. 

AI-based solutions can optimize the overall supply chain process by predicting problems in advance and proactively prescribing solutions to manage such disruptions. They can also eliminate inefficiencies through intelligent automation and provide visibility and insights that enable effective decision-making and planning. 

There are various applications of AI and ML, and differing ways they can be operationalized throughout the supply chain. Some of the key areas where they can have the potential to make a transformational impact include: 

Supply chain automation & digitization. A lot of information in the supply chain is transacted through documents such as BOL, POD, contracts etc., which can be easily digitized using AI, thereby reducing human error, and enhancing the customer experience. AI can also intelligently automate a lot of repetitive and manual processes in various areas of the supply chain, driving further efficiencies.  

Real-time visibility & predictive analytics. Businesses can harvest big data generated by a typical supply chain into valuable insights that can be used for strategic and tactical decision-making. While access to the real-time data and information can help businesses respond quickly and inform the value chain, AI and ML can analyze and model historical data to optimize the modern supply chain through better forecasting, planning, prediction and process automation. For example, AI-based solutions can help predict service failures in advance, and mitigate risk. 

Supply chain connectivity. COVID-19 showed us how important it is to have visibility and connectivity across each node in your supply chain, in order to manage uncertainty and unpredictability. While one of the most important steps to connectivity is supply chain digitalization, AI, combined with blockchain technology, can strengthen the end-to-end integrations and connect key activities in the supply chain. These include planning, booking, shipment tracking, and invoicing and payments, across multiple vendors, customers and supply chain partners. 

Sustainability. AI and data analytics play an important role in making supply chain operations greener and more sustainable. Utilizing ML and data analytics can optimize vehicle routes to minimize miles driven and reduce fuel consumption. AI can empower businesses to reduce waste in the supply chain by providing more accurate forecasting for demand, inventories and sales. 

Last-mile logistics. With the rise of e-commerce, and the rapid evolution of consumer behavior, last-mile logistics is becoming increasingly critical for efficient supply chain operations. AI and ML can help with the optimization of cost, service and asset utilization, ameliorating these inherent challenges within last-mile supply chain logistics. 

Outlook: The global logistics industry is expected to reach more than $15 trillion by 2023, with a compounded annual growth rate of 5% per year, while the U.S. logistics industry is expected to exceed $2 trillion by 2023, representing 8-9% of total U.S. GDP. Businesses that leverage AI and ML will be well-positioned to optimize their supply chain and respond with greater agility to changing consumer behaviors and external factors.