Logistics Leaders Navigate Cost and Automation

2026-06-11 · Source: Big Data & AI News - EE Times · Field: Manufacturing & Industrial — Supply Chain & Logistics, Automation & Robotics · Depth: Intermediate, medium

Summary

Gartner VP analyst David Gonzalez, speaking at the Gartner Supply Chain Symposium/Xpo on 06.11.2026, outlined strategies for logistics leaders facing unpredictable shipping costs, rising customer expectations, and labor shortages. He emphasized careful cost management, advocating for strict cost-to-serve and cost-to-deliver models and transparent communication between logistics managers and executives regarding service costs. Gonzalez also highlighted the need for practical technology adoption, noting that only 13% of logistics leaders have fully implemented AI, trailing other sectors. He recommended starting with targeted AI projects, citing Unilever's 50% productivity gain using agentic AI for order inquiries. Furthermore, with Gartner predicting half of new warehouses in developed markets will be 'robot-centric' by 2030, Gonzalez stressed adapting infrastructure to automation, rather than fitting robots into old spaces, and addressing the challenge of shifting from standardized to customized handling for direct-to-consumer demands.

Key takeaway

For Chief Supply Chain Officers facing escalating costs and labor scarcity, you must rigorously implement cost-to-serve models and transparently communicate service costs to executives. Prioritize targeted AI deployments, like agentic AI for order management, and proactively redesign your infrastructure to accommodate future robot-centric warehouses, ensuring profitability and operational resilience amidst increasing customization demands.

Key insights

Logistics profitability requires balancing cost management, pragmatic tech adoption, and infrastructure adaptation for automation and customization.

Principles

• Logistics services must operate profitably.
• Adapt infrastructure to future automation realities.
• Prioritize targeted AI solutions.

In practice

• Implement strict cost-to-serve models.
• Redesign warehouses for robot capabilities.
• Deploy agentic AI for order management.

Topics

• Supply Chain Management
• Logistics Automation
• Cost-to-Serve Models
• AI Adoption
• Warehouse Robotics
• Direct-to-Consumer Logistics

Best for: Operations Professional, Executive, Consultant

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Editorial summary, takeaway, and curation by AIssential. Original article published by Big Data & AI News - EE Times.