AI ambitions high in UK supply chain but skills & data lag behind
New research indicates that UK supply chain and transportation leaders expect an autonomous AI future, but face major barriers in terms of skills and data integration.
A survey conducted by Manhattan Associates, in partnership with Vanson Bourne, gathered responses from 150 senior executives across manufacturing, retail, wholesale, consumer goods, grocery, and food and beverage sectors in the UK. The findings highlight an urgent need for organisations to enhance internal capabilities and overcome persistent data silos to unlock the full potential of artificial intelligence in transportation management systems (TMS).
Data visibility issues
The study reveals that nearly half (49%) of surveyed organisations do not have sufficient data visibility to proactively adjust shipping routes. Furthermore, 45% indicated they cannot take corrective action before shipments are delayed or disrupted. This gap between technological aspiration and operational reality is compounded by significant internal challenges.
When examining reasons for limited visibility, 42% of respondents pointed to a lack of skills within their organisations, while 39% cited fragmented data across platforms and solutions as a serious obstacle. The combination of talent shortages and data divide is presenting significant hurdles to realising the efficiencies AI is expected to deliver.
AI expectations versus reality
Despite the current roadblocks, there is strong confidence in an AI-driven future. The research found that 63% of organisations anticipate adopting fully autonomous, agentic AI, or requiring only minimal human oversight, within the next five years. However, these ambitions are not reflected in current levels of AI integration. According to the survey, 46% of organisations have highly integrated AI in place, leaving the majority with less widespread adoption. Notably, almost a fifth (18%) report limited to no AI usage, putting them at risk compared to more digitally advanced competitors.
Key reasons underpinning slow uptake include financial and organisational barriers. More than half (55%) of respondents are concerned about the high cost of implementation and ongoing usage. Additionally, 45% acknowledge a lack of internal knowledge and skills as a limiting factor. There is a perception among 43% of those surveyed that executive sponsorship and organisational support for AI initiatives are lacking.
"The findings show a clear disconnect between the anticipated future usage and capabilities of AI in transportation and the current capabilities of many organisations. While autonomous agents have generated considerable interest, the reality is that a substantial portion of the industry is ill-equipped to harness this technology effectively due to internal skill shortages and fragmented data sets," commented Martin Lockwood, Senior Director at Manhattan Associates.
Concerns over system readiness
The research also demonstrates significant unease about the ability of existing TMS to meet future demands. A remarkable 99% of decision-makers surveyed expressed concerns that their current systems may not be able to keep pace with requirements for speed, capacity or cost reduction over the next five years. This finding reflects a broader sense of urgency for businesses to modernise their technology infrastructure while investing in the necessary expertise to manage new solutions.
"To truly unlock the benefits of AI, organisations must prioritise upskilling their workforce and breaking down data silos. Without these foundational elements, the promise of autonomous transportation management will remain out of reach for many, leading to increased costs, inefficiencies, a failure to meet evolving customer expectations and (potentially) a two-tier level of competition," Lockwood added.
The findings suggest that while expectations for AI in UK supply chains remain high, progress is dependent upon coordinated efforts to address internal skills gaps and unify data across platforms. Until these barriers are addressed, organisations may continue to fall short of their ambitions for AI-enabled agility and responsiveness within transportation management.