Analysts to Explore Development of AI-enabled Autonomous Supply Chains at Gartner Supply Chain Symposium/Xpo.
As supply chain disruptions mount from ongoing trade policy uncertainty and intensifying geopolitical conflicts, the likelihood of mismanagement, delayed responses, and financial losses increase without the support of real-time analytics or automated risk analysis.
Gartner data shows many chief supply chain officers (CSCOs) are responding by rapidly embracing agentic AI capabilities, or plan to do so within the next two years. A Gartner survey of 509 supply chain leaders from October 2025 indicated “changes in ways of working driven by advancements in AI and agentic AI” will be the most influential driver of future supply chain performance over the next two years.
“As more frequent and complex disruptions continue to test response capacity, organizations are moving toward AI that can sense and act in real time to improve the consistency and speed of decisions,” said Julia von Massow, Director Analyst in Gartner’s Supply Chain practice. “CSCOs should focus on expanding autonomy in a controlled manner by starting with low-risk decisions and building the data and governance needed to grow automation capabilities responsibly in the coming years.”
Current technological immaturity and data availability issues should, for now, restrict full automation to low-risk decisions. For higher-stakes decisions, AI is better used to augment human judgment where full automation may introduce unacceptable risks. This dual approach allows CSCOs to build the data and governance foundation needed to eventually manage a majority of disruptions without human intervention, as both technology and organizational capabilities expand.
Autonomous Supply Chains Require New Working Models
- Own responsibility for supporting an enterprise-wide AI strategy and roadmap that aligns technology investments with objectives including disruption management and decision automation.
- Prioritize investments in data quality and governance so autonomous supply chain technologies can access accurate, timely, and complete supply chain information, supporting trusted decisions aligned to potential regulatory guidelines when managing disruptions.
- Budget ongoing resources to assess the emotional and performance-based impact of increasing autonomy on existing supply chain roles, treating change management as a core workstream.
- Develop contingency plans for failures in autonomous decisions, including protocols for rapid human intervention and continuous improvement based on incident analysis, supported by governance and performance management frameworks.
