Demand for supply chain professionals with AI skills has grown 387% between the first quarter of 2023 and the first quarter of 2026, according to Gartner. That surge has pushed many organizations toward aggressive hiring, but the research firm's data also shows AI-related supply chain roles are concentrating at mid- and senior levels, where competition for experienced talent is fiercest.
The bigger opportunity, argues Sedgwick's Revel Boulon, lies in upskilling the workforce companies already employ. Supply chain professionals who understand freight movement, supplier relationships, and disruption response hold institutional knowledge that can't be replicated by recruiting alone.
The gap between technology and readiness
New AI tools expose differences in how ready teams actually are. Some employees immediately find practical ways to apply the technology to operations. Others hold back - not because they doubt AI's value, but because they haven't been given the training to understand where it fits in their daily work.
Leadership messaging matters here. Boulon says organizations need to communicate both what AI can do and how it will supplement existing skills, while making clear that employees aren't being trained into redundancy. "After all, who wants to lead the charge to implement processes and technology which makes their own position obsolete or redundant."
AI is different from previous supply chain technology investments. Warehouse management systems and transportation platforms automated existing processes. AI influences how decisions themselves get made - identifying patterns, prioritizing exceptions, and generating recommendations in seconds. But those capabilities still depend on experienced professionals who understand the broader operational context.
AI literacy as a core competency
In marine logistics and global supply chains, disruptions often involve weather, port congestion, customs requirements, contractual obligations, and customer priorities simultaneously. AI can organize the information and surface options, but determining the best course of action requires operational experience.
That's why AI literacy shouldn't be treated as a technical skill for data scientists and IT teams alone. It's becoming a core business competency across supply chain operations. Employees don't need to build AI models, but they do need to interpret AI-generated recommendations, recognize when outputs need scrutiny, and know when their own expertise should override an automated suggestion.
Gartner's research suggests organizations that invest in internal upskilling and make better use of entry-level talent will be better positioned to build sustainable AI capabilities than those competing for a small pool of experienced AI hires. Supply chain expertise develops over years of navigating disruptions and understanding operations under pressure - skills that remain highly valuable.
What upskilling signals to employees
Training programs send a message. When companies invest in helping existing staff become confident AI users, they position the technology as an asset that enhances problem-solving and decision-making rather than a threat. That mindset shift matters as much as the software itself.
Boulon notes that the "light-bulb moment" is when an employee realizes how quickly they can perform certain tasks with AI and what that means for their productivity - and that they are now more valuable to the organization. That realization typically triggers positive engagement and questions from others.
The organizations making the most progress aren't necessarily spending the most on technology. They're building environments where employees can learn, experiment, and ask questions without fear.
Why this matters for IT and development professionals
For people building and deploying AI systems, the takeaway is that deployment success depends less on model performance than on user readiness. Technical teams should expect to spend as much effort on training, documentation, and feedback loops as on the systems themselves. Building AI that experienced professionals can actually use - and trust - is the differentiator. The organizations that get this right will be those that treat AI literacy as a workforce development issue, not a recruitment problem.
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