How to Navigate the High Stakes of AI in Logistics: Key Insights from Bart De Muynck
AI continues to dominate logistics and supply chain conversations, but the gap between experimentation and real operational value remains wide.
In his recent article, The Intelligent Edge: Navigating the High Stakes of AI in Logistics, Bart De Muynck explores why so many AI initiatives fail to scale and what leading organizations are doing differently to achieve measurable results.
Below, we highlight several key takeaways from Bart’s perspective and what they mean for logistics leaders looking to move beyond AI hype and toward practical execution.
Why AI Adoption Alone Does Not Equal Business Impact
AI investment across the logistics and supply chain industry has accelerated rapidly, but success rates remain surprisingly low. Bart points to research suggesting that a significant majority of enterprise AI programs fail to deliver meaningful value, not because the technology is ineffective, but because organizations struggle to operationalize it.
The problem is rarely a lack of ambition. Instead, it is often tied to common execution barriers:
- AI pilots that never transition into scalable solutions
- Data environments that are not prepared to support advanced analytics
- Innovation efforts that remain disconnected from day-to-day operational workflows
Without a clear path from experimentation to execution, even the most promising AI initiatives can stall before producing measurable outcomes.
What the Most Successful Companies Are Doing Differently
Despite these challenges, Bart highlights that a small group of organizations are already generating real value from AI in logistics. These leaders share several consistent traits in how they approach implementation.
They start with focused, high-impact problems rather than broad experimentation. They build cross-functional teams that connect data science with operational expertise. They invest early in data readiness and governance, recognizing that AI outcomes are only as strong as the information feeding the models.
Most importantly, they treat AI as an enabler of better decision-making, not as a replacement for human judgment. The most effective applications support people with faster insights, clearer visibility, and stronger execution across transportation and logistics networks.
Moving Beyond Pilot Purgatory Toward Scalable Results
Bart’s central message is clear: the competitive advantage of AI is not theoretical. It is achievable, but only when companies approach AI as a business capability rather than a standalone technology project.
That means tying initiatives directly to operational outcomes such as cost reduction, improved service levels, enhanced freight visibility, and faster exception management. It also requires designing pilots with scale in mind from the beginning, ensuring that early successes can expand across regions, modes, or enterprise workflows.
AI becomes valuable when it is embedded into real logistics decision-making, not when it lives in isolated dashboards or disconnected proof-of-concepts.
Join the Conversation on March 17
To explore these themes further, together with Better Supply Chains, Intelligent Audit is kicking off a multi-episode series called The Intelligent Edge. The series is all about real conversations with industry leaders that have created, tested, launched, and scaled AI initiatives successfully and are actually seeing value in the efforts. Episode 1 featuring Bart De Muynck, Hannah Testani, and Guru Rao happens live on March 17, 2026.
Inside the 5%: Where AI Is Actually Delivering Value in Logistics
Date: Wednesday, March 17
Time: 2:00 PM EST
Speakers:
- Bart De Muynck
Advisor and Industry Thought Leader
Founder, Better Supply Chains
LinkedIn
- Guru Rao
Founder & CEO, NuPort Robotics
LinkedIn
- Hannah Testani
Chief Executive Officer, Intelligent Audit
LinkedIn
This session will focus on where AI is delivering measurable value today, why so many initiatives fail to scale, and what distinguishes the organizations that are successfully operationalizing AI across logistics.
