AI empowers logistics decisions by providing predictive analytics and autonomous decision-making, which transforms operations from reactive to proactive. This leads to reduced operating costs, increased efficiency, fewer errors, and improved customer satisfaction.

This session will cover three key topics:

1. A preview of all in-progress Logistics AI agents.
2. A review of a predictive transit time AI example.
3. A deep dive into a solution built in our AI studio: the Connected Logistics Agent.

Drive distribution efficiency and automate decision making through use of AI and machine learning. Evolve from reactive to proactive operations leveraging predictive analytics leading to reduced operating costs, shorter fulfillment cycle times, and more accurate inventory, ultimately resulting in improved customer satisfaction.

This session will cover three (3) topics:

1. In-progress additional AI/ML capabilities
2. Review of a Smart Putaway example
3. Review of a Smart Cycle Count example

Embedded machine learning for Oracle Global Trade Management provides an automated yet responsible product classification proposal workflow. This human-in-the-loop process assists human classifiers in minimizing errors by using historical context of currently classified items while ensuring decisions are auditable.

This session will cover three key topics:

1. A review of an AI assisted product classification proposal example.
2. A preview of future enhancements to AI assisted product classification.
3. An overview of potential future use cases for AI in Global Trade Management including AI agents.