Supply chain execution is under more pressure than at any point in the last decade. Here’s what supply chain leaders told us about what’s breaking and what’s not.
say execution speed, not planning, is now the primary source of competitive advantage
have real-time, end-to-end visibility across their supply chain
have fully integrated generative or agentic AI across their supply chain execution
For most organizations, the systems running day-to-day supply chain operations were built to record activity — not act on it. That gap between ambition and legacy systems is where disruptions live, AI stalls and competitive advantage slips.
79%
say execution speed now drives advantage ahead of planning, inventory optimization and cost management
It’s no longer about better plans. It’s about faster, smarter execution across order, warehouse and transportation.
58%
cite manual intervention as their #1 source of inefficiency ahead of technology limitations, data fragmentation and misaligned inventory
Only 20% have real-time, end-to-end visibility, meaning 80% are making execution calls on information that’s already out of date.
LEGACY ARCHITECTURE
There isn’t a budget problem.
Legacy systems are the blockers.
It’s not about willingness to invest. It’s about whether current systems can support the execution model leaders actually need. Legacy debt, integration complexity and budget constraints are symptoms of the same root problem.
AI isn’t the problem. The environment is. Fragmented systems, manual workflows and unclear ROI are what’s blocking progress, not skepticism about the technology. And what leaders expect in return makes the stakes clear: cost reduction, labor productivity, better predictability. Execution outcomes, not analytics outputs.
“The next phase of supply chain advantage will not come from better visibility alone — but from the ability to move from systems that record activity to systems that act, coordinating execution end to end and embedding intelligence at the point of action.”
Three steps toward intelligent, connected execution
The gap between ambition and impact is a technology problem. Here’s how to start closing it.
Look for execution solutions that integrate with existing OMS, WMS and TMS environments and scale incrementally. Modular, interoperable architectures let you scale without disrupting what already works.
Waiting for perfectly clean data will only widen the gap. Value from AI comes from applying it directly within execution, where systems learn and adapt over time. Early use tells you which data actually matters most.
Look for proven solutions that operate across order, warehouse and transportation at scale. Point solutions, bolt-ons and embedded intelligence are not the same thing.
