#data-silos

#data-silos

The global supply chain is all about modern logistics today, but it is also fragmented and complex. With different carriers, ports, customs agencies, and logistics companies all using their own unique systems and data formats, it is a recipe for miscommunication, inefficiency, and costly delays. This lack of a common language is particularly evident in the " track and trace " process. When a container moves from a carrier's system to a port's system to a customs agency's system, the data often doesn't transfer seamlessly.

In the race to stay ahead, organizations have thrown open the doors to every AI tool under the sun. The result? AI overload. According to the Wharton School, AI spending has skyrocketed by 130% in just the past year, and 72% of companies are planning to invest even more in 2025. Yet, here's the kicker: 80% of organizations report no tangible enterprise-wide impact from their generative AI investments.

Over one-third (37%) of professionals report that data silos prevent efficient data sharing across teams, highlighting a significant barrier to effective collaboration.