AI's potential in supply chain management has changed the entire application. These include optimizing production schedules, predicting demand, improving inventory management, and reducing transportation costs. AI in SCM enables companies to make data-driven decisions.

Machine-Learning is a method where computers analyze large datasets with algorithms to provide meaningful insights. There are several helpful aspects that machine learning delivers to supply chain management including :
- Cost efficiency due to low levels of manual labor which maximize profits.
- Optimization of product flow from suppliers to customers without holding inventory.
- Simpler, faster, and more efficient supplier relationship management.
- Machine learning helps derive actionable insight -- we're able to solve problems quicker and with less effort.

AI has the potential to revolutionize logistics by automating various processes and tasks that are currently carried out manually. For example, AI can be used to automate the routing of vehicles, the scheduling of deliveries, and the tracking of inventory. By automating these tasks, AI can help logistics companies to become more efficient and to better meet the needs of their customers.

With the use of AI, supply chain enterprises aim to make the supply-chain business more:
- Instrumented : (machine to machine) systems process the information they receive on IOT space.
- Intelligent: Smarter and more advanced predictions with data and analytics.
- Interconnected: Easy access to all the information (connected) for better decision making.

As per a report, by 2030, AI will streamline the production process. The AI-driven robots will contribute towards automating various services such as, automated warehousing, self-packing, sorting and delivering. AI will also help to introduce radio-frequency identification to anonymously identify products and deliver it to respective warehouses.