AI Is Reshaping Supply Chain Risk
At Davos 2026, experts like Brandon Daniels argued that AI-driven analytics are enabling a more proactive approach to supply chain risk management. The technology is being used to predict disruptions from geopolitical events, automate supplier compliance monitoring, and improve due diligence, shifting the focus from reaction to preemption.
The global AI in supply chain market is projected to grow from $13.81 billion in 2026 to approximately $236.42 billion by 2035. This expansion is driven by the technology's ability to improve logistics costs, inventory levels, and service, with early adopters seeing improvements of 15%, 35%, and 65%, respectively. A recent Accenture survey found that 85% of supply chain executives plan to increase their AI spending in 2026, with a focus on improving forecasting and risk management. Geopolitical fragmentation remains a dominant risk, with ongoing trade tensions and the formation of competitive economic blocs impacting sourcing strategies for critical materials like semiconductors and rare earths. The "weaponization of the supply chain" is a noted trend, as nations leverage control over key resources to achieve strategic aims. This has led companies to diversify away from single-source dependencies, with many expanding into Vietnam, Mexico, and Eastern Europe to enhance resilience. Regulatory pressures are intensifying for manufacturers. For fiscal years beginning after December 15, 2025, new SEC rules mandate enhanced disclosures on inventory valuation methods and, for the first time, material supply chain risks that could impact inventory. Concurrently, OSHA is increasing enforcement in high-risk sectors like manufacturing, with willful or repeated violations now carrying penalties up to $165,514. The EPA is also enacting stricter rules, with a potential October 13, 2026, deadline for manufacturers to report on PFAS usage dating back to 2011. Additionally, facilities with large refrigeration systems must have automatic leak detection for high-GWP refrigerants by January 1, 2026. These changes add new layers of compliance complexity that AI-powered monitoring systems are being positioned to address. For internal audit functions, the proliferation of AI in supply chain management presents a dual mandate: providing assurance over the AI models themselves and leveraging the technology to enhance risk oversight. As management adopts AI for predictive risk analytics, internal audit's role is shifting to validate the data governance, security, and ethical use of these complex systems. This ensures that insights from AI tools are effectively used to strengthen controls and inform strategic decisions, moving beyond traditional compliance testing.
