Since its conceptualization and genesis, Artificial intelligence has been harbored by diverse genres of technology; be it automation of a CRM module or achieving a self-sustainable production cycle, AI has been linked with various use cases in multiple domains. On the same lines, Supply chain has been in the limelight for numerous applications fostered by artificial intelligence.

Artificial intelligence brings with itself a suite of automated services that bolster supply chain management (SCM) with real-time data analytics. Rightly validating the hype surrounding the technology, SCM connoisseurs are adapting AI strategies to optimize bare essentials of a supply chain. From real-time data access to segregation of unstructured data to autonomous decision making, AI is making significant changes to the way supply chain is pursued in the current day and age. Consider an example of product distributor operating in three different countries. Not only should the consignments reach its appropriate destination in the stipulated time but also should go through a series of operations that determine the trajectory of the supply chain. Using AI, each succeeding operation can be scheduled in accordance with the trajectory and proceeding operation, thereby completing automated checkpoints along its path. This process accounts for real-time data access, allowing supply chain managers to govern the data flow using the various checkpoints; autonomous actionable parameters can be incorporated within the trajectory so that the process of decision-making is simplified. Additionally, all the data is classified into multiple channels, allowing authorized personnel to augment changes accordingly. Although this is a typical example of supply chain automation, AI goes a long way providing flexibility and ease of operations.