AI-driven logistics orchestration and control tower THEME 1 Evolutions of themes Build an intelligent logistics network that unifies end-to-end visibility, real-time decision- making and synchronized execution across the operational layer (transport, warehouses, carrier, partners and production). Cost per shipment On time in fullFoundational visibility and issue detection — Consolidate data across the operational layer into a unified view. — Early-warning alerts flag delays, missed pickups, long dwell times, route deviations and capacity issues. — Rapid demand- and disruption-based scenario checks to assess delivery impact.AI-guided logistics decision-making — AI recommends optimal routes that balance cost, speed, reliability and sustainability. — The operational layer synchronizes schedules and execution from a shared logistics plan. — Predictive adjustments smooth flows before bottlenecks occur.Autonomous logistics control tower — AI automatically adjusts schedules, loads and routing as conditions change. — Network flows self-balance across the operational layer with minimal human input. — End-to-end orchestration becomes continuous, adaptive and cost-optimal.NOW (0-2 years) NEAR (3-5 years) NEXT (5+ years) Objectives4.2 External logistics External logistics today remain fragmented, with carriers, warehouses and transport partners operating on disconnected systems that limit visibility and slow down response. Routing, tracking and issue resolution drive higher cost-to-serve and inconsistent delivery performance. The future is a dynamic external logistics network: AI- enabled, connected and continuously optimizing through real-time data, risk prediction and multimodal networks to improve service, resilience and sustainability. EXTERNAL LOGISTICS Intelligent Industrial Operations Outlook 2026 42