New research on 215 supply chain leaders reveals 78% have no documented AI plan. Get the data and the five-question framework.
AI in Logistics: 78% of Supply Chain Leaders Are Moving Without a Plan
Logistics Technology
AI Is Not a Proxy for Innovation
AI capabilities aren’t proof of vendor innovation. Here’s our take on evaluating AI in a logistics technology selection, and what to demand from vendors as proof.
AI ROI: How Do You Measure It?
We recently asked 215 supply chain leaders about their AI initiatives. We found that only 7% set a baseline, 11% set success criteria, 3% check results afterward. Here’s what a defensible ROI case requires.
Why Your AI Pilot Failed Before It Even Started
Why do AI pilots fail in supply chain? New survey data from 215 supply chain leaders points to a root cause: no business case, no governance, no accountable owner.
Five Questions That Predict Whether Your WMS Implementation Will Succeed
WMS implementation failure usually traces back to five questions nobody asked. Brian Carlson of Cornerstone Edge explores what separates the projects that work from the ones that need rescuing.
What Two Decades of Tuning a TMS Route Optimizer Teaches About Autonomous AI Hype
Read enough industry coverage right now and autonomous AI sounds like a settled outcome: robots in warehouses, agents running freight networks, a shrinking workforce to match. For most shippers today, that isn’t the operating reality, and nothing in the current generation of tools points to it becoming the reality next year either.
What Buyers Need to Understand Before They Invest
When an intelligent capability influences a technology decision, its requirements matter as much as its functionality.
WMS Implementation Isn’t Optional Anymore—Here’s Why
Ask anyone who’s run a warehouse for the last twenty years and they’ll tell you the job used to be simpler. Receive inventory. Pick orders. Ship them out. The systems supporting that work matched the simplicity of the work itself. That era is over, and it isn’t coming back.
TMS Implementation Doesn’t End at Go-Live
TMS implementations rarely fail because of the software. More often than not, internal factors, such as organizational readiness challenges and resource constraints, are to blame.
