5 Levers of Digital Sophistication
Most logistics operations are still held together manually. This report explains why.
A Deep Current analysis of where AI adoption breaks down in logistics and what separates experimentation from operational impact.
Based on survey inputs and operational workflow analysis across logistics teams.
Inside the report
- Why data is the real constraint in logistics operations
- Where workflows break down across documents, emails, and systems
- Why AI tools fail when they sit outside execution workflows
- What changes when intelligence is embedded into day-to-day operations
The problem is the data flow (and input) process and architecture
In logistics, critical information exists across emails, documents, and systems, but does not move cleanly across workflows.
As a result:
- teams manually connect systems
- data is re-entered multiple times
- decisions depend on fragmented inputs
This is where inefficiency begins and where most AI initiatives stall.
- Majority (52%) re-enter the same shipment data across multiple systems
- 49% switch between 5+ systems to complete a single workflow
- The highest levels of friction in logistics sit at the foundation, namely data and workflows, where manual intervention remains most prevalent
If your operations still depend on people to connect systems, this is where to start.
Download the report to see what needs to change and where to begin.
Get in touch with our team of logistics professionals who understand where the workflows break and what to fix. Write to us at info@deepcurrent.no