A Boston Consulting Group survey of over 180 logistics firms across Europe, North America, Asia, and the Middle East found that more than 40% of companies require AI-enabled logistics services, while around 50% have already implemented AI-powered tracking and visibility solutions. Transport planning and execution leads adoption at 64% among providers. Almost 80% of respondents cite cost reduction and efficiency gains as key drivers. Founders of Intelligenza Artificiale Spiegata Semplice call AI a 'strategic engine' reshaping distribution networks and service quality. The findings reflect a global, cross-regional shift in logistics capability expectations.
According to en.ilsole24ore.com, a Boston Consulting Group (BCG) survey of more than 180 logistics service companies and their customers across Europe, North America, Asia, and the Middle East — conducted in January 2026 — reveals that more than 40% of companies expect logistics service providers to offer AI-based solutions, and around 50% have already implemented dedicated tracking and tracing and visibility technology solutions powered by artificial intelligence.
Adoption Drivers and Impact Areas
The survey identifies transport planning and execution as the core domain of AI integration, where AI has already reached 64% adoption among logistics service providers. Respondents cite cost reduction and increased efficiency as the primary benefits — cited by almost 80% of respondents as the main reasons for AI adoption. Use cases span optimization algorithms for transport planning and predictive analysis for demand forecasting.
Visibility and Operational Precision
The deployed AI visibility tools enable automatic detection of packaging defects, verification of exact delivery locations against planned routes, and prevention of sorting errors before goods leave the warehouse. These capabilities directly support real-time decision-making and reduce manual intervention across fulfillment workflows.
Strategic Shift in Industry Perception
“Artificial intelligence is marking a paradigm shift in logistics,” are the words of Giacinto Fiore and Pasquale Viscanti, founders of Intelligenza Artificiale Spiegata Semplice, the largest Italian community on the subject. “It is no longer just a support tool, but a real strategic engine that enables companies to radically rethink processes, distribution networks and operating models. Whoever integrates AI today into transport planning and execution not only reduces costs and inefficiencies, but also acquires a concrete competitive advantage in terms of speed, precision and quality of service.”
Industry Context and Practitioner Implications
This acceleration aligns with broader industry trends: DHL’s 2025 Resilience Report highlighted AI-driven predictive rerouting during port congestion, while UPS’s ORION system — long using optimization algorithms — has recently integrated real-time traffic and weather data via AI-enhanced APIs. For supply chain professionals, the BCG findings signal that AI readiness is no longer optional for vendor selection or internal capability roadmaps. Procurement teams evaluating 3PLs must now assess AI maturity beyond legacy TMS functionality; operations leads should prioritize interoperability between AI visibility layers and existing WMS/TMS/ERP systems. Notably, the survey’s geographic scope — covering four major regions — confirms that AI adoption in logistics is a globally synchronized priority, not a regional pilot trend.
Upcoming Industry Engagement
The AI WEEK event scheduled for 19–20 May 2026 in Milan (Fiera di Rho) reflects this momentum. Arsenalia, an independent Italian firm partnering on the event, reports its Digital Manufacturing practice — applying AI to robotics, computer vision, and predictive maintenance — is its fastest-growing service line. As Gianluigi Alberici, senior partner at Arsenalia, notes: “What we see every day working with our industrial customers goes far beyond logistics.” This underscores how AI logistics initiatives increasingly interface with production planning, inventory synchronization, and physical asset management — reinforcing cross-functional accountability for AI implementation.
Source: en.ilsole24ore.com
Compiled from international media by the SCI.AI editorial team.
