Promises vs. reality: Closing the AI adoption gap in transportation
As teams see AI perform reliably, trust and their willingness to give it more responsibility grow.
Modern AI is advancing rapidly, with new capabilities developing every day. While supply chain applications for AI are growing just as fast, many organizations still struggle to decide where and how to put this technology to work in their real-world environments. This has created an adoption gap in the industry: investment in AI is outpacing organizations’ ability to put it to work in ways operations teams can confidently rely on.
The potential benefits of AI’s ability to create a system of action are exciting, but the expectation of huge ROI by the C-Suite does not translate to enthusiasm from everyday users. Executives may decide to pull the trigger on a widespread implementation, but if users don’t find the tool helpful or see how it makes their jobs easier, adoption stalls.
“Not every AI solution is built for transportation,” Shipwell CEO and co-founder Greg Price points out. Using a solution that’s not designed for supply chain complexity can make users more hesitant to rely on it in their operation.
A recent survey from Kinaxis makes the disconnect in attitudes toward AI between the C-Suite and leadership teams clear. Across supply chain use cases, executives are far more optimistic about the ease of use and financial gain for AI than operations and IT leaders. A couple of notable examples include:
This story was originally published by Supply Chain Dive. Read the full story at Supply Chain Dive →
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