Generative AI in Supply Chain Management

Supply chain management has always been an area which has multiple use cases. The use cases include logistics, transportation, warehouse management, inventory management etc. Over the years, with the advancements in technology, the supply chain management has seen a lot of improvements, optimizations in the implementation of the use cases, solving problems and managing the eco-system.

With the advent of Generative AI, there are a lot of areas in Supply Chain management which can be improved and enhanced. Such improvements help optimize routes, reduce shipping time, reduce costs and a lot more such advantages. The continuous progress in the field of Generative AI technology, will create more applications, which will be innovative, disruptive, transformative, not only in supply chain management, but across varied domains. It will help businesses to take quick and better decisions based on the large amount of data available with them. Generative AI will revolutionize the way that businesses manage their supply chains. Let us look at some of the areas where Generative AI will disrupt the existing solutions and provide with innovative, optimized and cost saving solutions.

Optimized Routing: Generative AI can help predict the best routes which can improve the delivery times and reduce the costs. Generative AI can help identify the optimized routes in terms of time and cost using the data about delivery size, shipment details like type of items being shipped, route or location constraints etc. This helps in saving money for the organization in addition to efficient delivery of the shipment.

Dynamic Re-Routing: While optimized routing is already an advantage, there will be chances where the original route may need to be avoided. This could be due to bad weather, traffic, natural calamity, or any other reason which could block the route or make it difficult for transportation. Generative AI can utilize the information from the maps, weather portals and related information to identify and suggest an alternate route dynamically.

Dynamic updates in Delivery Timeline: Generative AI can help track the shipment using the sensor and location details of the shipment vehicles and generate a live dashboard with regular updates on the expected time of delivery. Generative AI

Predictive Maintenance: Vehicles, of late, have the features to track and record the different parameters in the different parts of the vehicle. This also includes fuel, engine oil, brakes, and other important parts of the vehicle. AI models use this data to predict the schedule for the maintenance of the vehicle. Generative AI can be used to generate a report if the vehicle identified for shipment, will be the right choice or does it need to be replaced.

Improving decision-making: Generative AI can be used to analyze large datasets of previous data to identify patterns and trends. This data can be used to make improve decision making which can include demand prediction, dynamic pricing, and identifying and managing risks.

Predicting demand for inventory: Generative AI can be used to analyze past data and predict the future requirement for inventory. This enables businesses to improve and optimize the inventory management.

Identifying potential risks: Generative AI can be used to analyze data on past data on the problems faced and generate a list of potential risks. This can help businesses to plan for mitigating the risks and reduce the impact.

Marketing and campaign management: Gen AI can create relevant content in different formats like Text, Audio, Images, Videos for the marketing. This will save cost and effort.

Documentation: Gen AI with Natural Language processing can be used to create the documents related to invoices, bills, notices etc. This helps in streamlining the content and improved efficiency and accuracy.

Task automation: Gen AI can be used to automate tasks such as order processing, inventory management, and schedule deliveries. This helps save time and effort and provides opportunity to focus on other tasks.

Better customer service: Generative AI can help businesses to provide better customer service with more accurate and up to date information about orders, shipments, and delivery status, especially with the appropriate usage of Natural Language processing.

Those were some of the areas where that generative AI can be used in supply chain management. Overall, generative AI is likely to bring disruption in the existing solutions in supply chain management and make it more efficient, accurate, and cost-effective. As the technology continues to develop, we can expect to see even more innovative applications using generative AI.

Author Details

Mohammad Athar Jamal

Athar is an Enterprise and Cloud Solution Architect at Infosys. He works on Digital Transformation for different clients and enhances the Digital Experience for enterprises. He architects microservices, UI/Mobile applications, and Enterprise solutions by leveraging cloud services, designing cloud-native applications. His work includes providing leadership, strategy, and technical consultation.

Leave a Comment

Your email address will not be published.