A gap between what executives believe about AI and what frontline workers experience is stalling large-scale deployment across the supply chain industry, according to a survey of more than 200 professionals published by The Loadstar. While 89.5% of organisations already seeing measurable value point to speed and productivity gains, most have not moved AI beyond pilot projects.
The State of AI in Supply Chain report found that only 22.2% of respondents had deployed AI at scale across multiple teams or made it core to operations. Another 43.2% remained in experimentation phases or had not started adoption at all. The findings locate the primary obstacles inside organisations rather than in the technology itself.
The confidence gap between leadership and the front line
Among vice presidents and executives, 77.5% described themselves as optimistic or enthusiastic about AI's impact on their careers. That figure fell to 37.5% among analysts, specialists and other individual contributors. Only 9% of those frontline workers said they felt threatened by the technology.
James Coombes, chief executive of logistics AI provider Raft, said the numbers reveal a disconnect between vision and delivery. "The biggest eye-opener for me was the massive sentiment gap between the boardroom and the front lines," he said. "This tells us the issue isn't frontline fear, but rather leadership selling a grand vision that their execution teams simply haven't seen delivered in reality yet."
Where AI is working - and what's blocking it
Document extraction and processing remains the clearest success story. Nearly 80% of respondents identified it as the area generating the most tangible operational impact. More than half (53.8%) cited a lack of in-house AI expertise and change-management capability as the main obstacle to scaling, while 48.7% pointed to difficulties integrating AI with existing systems.
Measurement compounds the problem. Nearly two-thirds (62.8%) of respondents said they had either not measured the return on investment from AI initiatives or were unsure how to do so. Coombes pushed back on describing the situation as hype. "Hype implies the value isn't real, and across more than 100 deployments with Raft the value is undeniable," he said. "What the survey exposes is something more interesting: a measurement and execution gap. Most firms still can't put a number on what AI is doing for them, and far fewer have deployed at scale than are talking about it."
Regional differences and back-office shifts
North America recorded the highest proportion of companies yet to begin AI adoption, with 25.6% reporting no meaningful implementation efforts. Coombes attributed the lag to operational complexity rather than a lack of ambition. He pointed to the breadth of services managed by many US-based logistics providers, the legacy of extensive offshoring, and deeply embedded operating processes as factors making change harder than in other markets.
Looking ahead, 65.8% of respondents said data quality and integration would be the key differentiator between AI leaders and laggards over the next two to three years. Coombes predicted the next major shift will hit back-office operations directly. "Within three years, the high-volume document triage and actioning that has bottlenecked the logistics back office for decades will be gone," he said. "Reconciling an invoice against an accrual, making a customer booking, chasing a missing field - all of it automated by default, handled before a human ever sees it." What remains, he said, will be high-stakes data requiring human review, mission-critical exception management, and relationship management with customers and service providers.
Why this matters for management
The data makes clear that AI adoption problems are not technical - they are organisational. For managers, the 40-point enthusiasm gap between executives and individual contributors is a direct signal that strategy and execution are not aligned. If frontline teams have not seen the promised gains materialise, the next wave of deployment will stall regardless of how bullish leadership sounds. Closing that gap requires not just a roadmap for technology but a credible plan for change management, measurement, and integration with systems people already use every day.
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