THOUGHT Leaders CONTENT PARTNERS
Artificial Intelligence in Supply Chains: Beyond the Hype
Q What are the most compelling models for human-AI collaboration? A Niklas: At Kuehne+Nagel, human-AI collaboration is a strategic enabler. Effective models include human-in-the-loop systems, where AI supports decision-making in complex scenarios; agentic AI, which automates routine tasks; and closed-loop collaboration, where humans set objectives and AI executes them. Mattias: The human factor must remain central. AI should always align with customer goals, whether reducing cost, emissions, or risk. Generative AI only creates value when people define the standards. Q What skills will define the supply chain professional of the future? A Niklas: Hybrid roles will dominate. Professionals will pair domain expertise with digital fluency, filling roles like AI product managers, data translators, and prompt engineers. Scenario planning, machine learning literacy, and human-AI orchestration are critical. Mattias: Supply chains may become more standardized, but partnerships will remain personal. Professionals building strong relationships and delivering reliably in an automated environment will be indispensable. Q How far are we from end-to-end autonomous supply chains? A Niklas: We are piloting AI agents that automate workflows, validate data, and make routine decisions with minimal oversight. But adoption faces barriers—siloed data, governance complexity, and trust. Autonomous
supply chains could be viable in 5–10 years with structured investment. Mattias: Technology alone will not unlock autonomy. Stakeholders must align around shared objectives all the way from origin to final consumer. Without clear goals, AI’s promise will fall short. Resolving this complexity is as important as the technology itself. Q What prerequisites must be in place? A Niklas: Autonomy requires five pillars: 1) AI-ready data architecture with real- time visibility; 2) cloud-native infrastructure for secure orchestration; 3) embedded machine learning; 4) robotics and automation for execution; 5) governance frameworks for ethical deployment. Mattias: Consumer behaviors remain erratic and hence the impact of human connection remains the differentiator. The most effective partners pair cutting-edge technology with trust. Q What framework should guide AI partner selection? A Niklas: We assess partners for strategic fit, technical maturity, governance, and ESG alignment. Leaders should ask: Does the solution integrate with long-term ecosystems? Can it scale? How is data ethics managed? Does it support sustainability goals? We also use ESG-AI scoring and performance matrices. Mattias: Ultimately, technology and trust go hand in hand. Defining the objective with AI, the strategy, and the procedures still is a human responsibility. In logistics, even in an AI-driven future, relationships remain critical. A partner that delivers advanced solutions and a personal touch will stand out.
Niklas Sundberg (top) Chief Digital Officer Kuehne+Nagel
Mattias Praetorius (bottom) Head of Consumer Global Business Development Kuehne+Nagel
kuehne-nagel.com
26 Inbound Logistics • November 2025
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