IN Brief:
- UK search interest for “AI in logistics” hit a late-January 2026 high.
- Operators are prioritising predictive planning and exception automation over experimentation.
- Market growth projections are accelerating vendor competition, and buyer scrutiny.
UK interest in artificial intelligence for logistics has reached its highest recorded level, with Google Trends showing a peak in searches for “AI in logistics” during the week of 18–25 January 2026. The same dataset shows a sharp rise versus early November 2025, suggesting that the conversation inside UK supply chains has shifted from curiosity to deployment planning and procurement.
For operators, the timing is not subtle. Capacity remains tight in key warehousing corridors, delivery promises are still a differentiator, and returns volumes are not obligingly falling back to pre-e-commerce norms. AI spend, when it happens, tends to follow pain — and the most immediate pain points are predictable: volatile demand signals, rising service expectations, and labour that is both expensive and hard to retain.
Advanced Supply Chain, which compiled the search data, argues the change is about where AI is being applied, rather than whether it is being discussed. “What were once proof-of-concept trials are now becoming full-scale rollouts,” said Stuart Greenfield, Managing Director at Advanced Supply Chain. “UK logistics companies are moving beyond pilots and are now using AI to solve real operational issues. We’re seeing a big uptick in deployments of AI-driven demand forecasting, automated exception handling and routing optimisation, all of which directly impact service levels and costs.”
That emphasis matters for how technology is selected. Demand forecasting and routing optimisation are not standalone “AI projects”; they are deeply entangled with order management, transport management, inventory policy, and the quality of master data. Automated exception handling, meanwhile, only works if business rules, event visibility, and customer communications are joined up across carriers, 3PLs, and merchants. In other words, the “AI layer” can be bought quickly, but the operational outcomes are earned slowly.
Market forecasts are reinforcing the sense that buyers are not alone in thinking about execution. One industry forecast puts the global AI in logistics market at $38.68bn in 2026, up from $26.33bn in 2025, with a longer-term projection of $180.63bn by 2030. Those numbers attract investment, new entrants, and product roadmaps — but they also raise the bar for end users, who will be challenged on ROI, governance, and measurable service improvements rather than innovation theatre.
In the UK, “AI in logistics” is being pulled into everyday workflows: planners looking for predictive capacity signals, warehouse teams seeking better labour allocation, and customer service operations pushing for automated, accurate delivery answers that reduce avoidable contact. The winners will be the operators that treat AI as an operational discipline — with data ownership, performance baselines, and process change — rather than a software feature.
