An incredible AI use case opportunity: FedEx.
FedEx moves over 16 million packages a day across 220 countries. Every scan, route change, and failed delivery attempt generates data. To be precise, two petabytes of it. Daily.
For 50 years, the company’s advantage was physical and operational, with 700 aircraft, 200,000+ vehicles, and a network not so easy to replicate.
But the next decade is of data and intelligence.
CEO Raj Subramaniam mentioned, “FedEx is now entering a new era as we build the most flexible, efficient, and intelligent network in history.” The physical network will become an execution layer beneath a real-time intelligence system.
Like many companies that generated data for decades, FedEx too had a fragmentation problem.
The company’s data lived across 600 separate analytics environments and 7,500 applications. Teams built their own tools, and there was no access to insights across the organization.
To scale FedEx’s AI applications, the company needed to unify its data.
So they’ve created Atlas, FedEx’s enterprise data platform. It consolidates FedEx’s data estate into a single governed layer, currently supporting 200+ AI use cases.
By the end of 2027, FedEx plans to consolidate 100% of its data into Atlas and cut its application footprint by 50% by 2029.
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