IN Brief:
- Parcelhero’s report says UK transport and storage AI adoption rose from 16.1% to 27.1% in the first quarter of 2026.
- AI-driven route optimisation is delivering reported logistics cost reductions of 10% and on-time delivery improvements of 15%.
- Data quality, legacy systems, manual workflows, and workforce reskilling remain the main barriers to wider adoption.
Parcelhero has published a new industry report showing artificial intelligence moving from trial projects into the operating structure of global supply chains.
The report, Putting the AI into Supply ChAIns, was authored by David Jinks M.I.L.T., Parcelhero’s head of consumer research. It says the proportion of UK transport and storage companies using artificial intelligence rose from 16.1% to 27.1% in the first quarter of 2026, an eleven percentage-point increase in 90 days.
More than 20% of remaining companies planned to adopt AI during the second quarter, indicating that the first wave of adoption is still expanding. Around 40% of supply chain organisations globally are now investing in generative AI, while Deloitte’s 2026 Retail Industry Global Outlook found that 41% of retailers plan to deploy AI within 12 months to improve supply chain visibility.
The operational gains identified in the report cover several parts of the logistics chain. AI-driven route optimisation is delivering reported cost reductions of 10% and on-time delivery improvements of 15%. Algorithms can reorder more than 100 delivery stops in seconds while processing traffic, weather, and customer preference data.
Last-mile logistics remains one of the strongest use cases because it combines high cost, high variability, and direct service pressure. Parcelhero notes that last-mile delivery can account for more than 53% of total shipping costs, while AI use across the segment has grown by 39% in the past year.
Forecasting capability is also improving. Intelligent systems can now predict shipment volumes for specific facilities with up to 95% accuracy, allowing stock and capacity to be positioned before demand fully materialises. That changes the role of forecasting from periodic planning to active network control.
AI is already moving into logistics control rooms, shipment visibility, customs support, and digital twin environments. UPS’ use of AI across tracking, planning, customs, and control-tower activity has shown how large logistics networks are beginning to use the technology as a coordination layer rather than a single optimisation tool.
Warehousing is another strong area of adoption. Parcelhero highlights smart warehouse environments where autonomous mobile robots navigate dynamically, predictive maintenance flags likely equipment failures, and AI-led energy management adjusts electricity use across large facilities in real time. The warehouse is moving from fixed process automation toward systems that respond to live operating conditions.
Maritime logistics is also accelerating. The report values the maritime AI market at £4.13bn in 2024 and projects compound annual growth of 23% over the next five years. In 2025, 420 organisations adopted maritime AI technologies, up from 276 the previous year.
The autonomous electric container vessel Yara Birkeland has completed more than 250 voyages on its Norwegian route, replacing 40,000 diesel truck journeys annually. Although autonomous shipping remains a specialist application, it demonstrates how AI, electrification, and transport redesign can converge around specific freight corridors.
Airfreight is undergoing a quieter but equally practical change. AI is being used to compress rate comparison, export classification, customs documentation, and ETA prediction into faster workflows. The value lies in reducing manual delay, improving disruption detection, and allowing operators to intervene earlier when documentation or capacity issues appear.
The report also identifies the constraints holding adoption back. Legacy systems, batch-processed data, and manual workflows remain common across logistics. AI systems require timely, structured, and reliable data; poor master data and fragmented platforms can weaken model performance quickly.
Workforce impact is more nuanced than simple job loss. Parcelhero’s analysis of ONS data found that 31% of AI-adopting transport and storage companies reported no change in headcount, while the number reporting definite job cuts was too small to register statistically. The stronger operational requirement is reskilling, with staff needed to supervise systems, manage exceptions, maintain data quality, and interpret recommendations.
AI will not compensate for weak process design. In many cases, it will expose it. Companies with clean data, integrated systems, and trained teams will be able to use AI across routing, warehousing, customs, forecasting, and disruption management. Those with fragmented systems may find the technology accelerates decisions faster than the organisation can trust or act on them.
The adoption curve described by Parcelhero shows logistics entering a more demanding phase of digital transformation. AI is no longer confined to pilots and boardroom presentations. It is being pulled into route plans, warehouse floors, customs workflows, fleet decisions, and control rooms, where performance depends on data discipline as much as algorithmic capability.
