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Logistics AI: Improving Demand Forecasting and Optimizing Processes and Shipping Routes
Like many other industries, logistics and supply chain practitioners are beginning to use artificial intelligence to try to minimize errors and to optimize processes and shipping routes.
What are some of the ways that AI can improve logistics?
- Improve demand forecasting accuracy
- Reduce time and costs related to shipment tracking
- Route optimization to reduce time and costs of shipping
Philip Ashton, CEO of 7bridges, said that “the global logistics industry is expected to increase to a value of $3.215 trillion by 2021. AI solutions in transport and logistics (T&L) are part of this growth, and will be essential for meeting consumers’ increasingly high expectations.”
Anshuman Singh, vice-president and head of consulting, Europe at Mindtree, said that “the fast inroads made by emerging and new technologies have left transport and logistics companies with a lot of catching up to do. In 2019, we saw an increase in an infusion of IoT into existing scenarios – with most of the challenges around adding IoT/sensor capabilities and enabling intelligence on the edge being resolved under AIoT. While the original purpose behind enabling these capabilities may have been to do with early prediction of faults or optimizing usage patterns for efficiency, the large volume of data now available from these devices/sensors has opened up new avenues of exploration and optimization.”
