According to www.dcvelocity.com, AI adoption in supply chains rose to 41%—up from 30% last year—per The 2026 MHI Annual Industry Report, based on 500 professional respondents. Seventy percent see AI as disruptive. Top uses include demand optimization, predictive maintenance, and logistics routing. Despite economic and geopolitical uncertainty, 56% of leaders are increasing tech investments; 52% plan to spend over $1 million. The report warns of rising input costs and supplier reevaluation pressures.
According to www.dcvelocity.com, artificial intelligence is accelerating its impact across global supply chains, with 41% of surveyed companies now using AI—up from 30% last year. The finding comes from The 2026 MHI Annual Industry Report, titled Rewiring the Future: A Supply Chain Playbook for Innovation, a joint publication by industry association MHI and consulting firm Deloitte. Based on a survey of 500 supply chain professionals, the report identifies AI as the top transformative force, with 70% of respondents believing AI has the potential to disrupt the industry.
From Concept to Agentic Action
MHI CEO John Paxton highlighted the rapid evolution during his keynote at Modex 2026: “If you go back only two years ago, we were having discussions on what is AI. Then last year we talked about the term generative AI. This year we’re talking about agentic AI, which means putting agents to work and taking actual steps out of the operation.”
Top AI Use Cases and Investment Trends
The report identifies the leading applications of AI in supply chains:
- Enhancing demand/inventory optimization
- Predictive maintenance
- Automating decision making in operations
- Optimizing transportation/logistics routes
Despite ongoing economic and geopolitical uncertainty—including trade wars, inflation, sanctions, and border closures—56% of supply chain leaders are increasing their supply chain technology and automation investments this year. Of those:
- 52% plan to spend over $1 million
- 17% plan to spend over $10 million
The report cautions that uncertainty typically triggers cautious investment strategies and supplier relationship reevaluations—and warns of rising costs across goods, services, raw materials, energy, and labor.
Industry Context for Practitioners
This surge in AI adoption aligns with broader industry momentum: at Modex 2026 alone, multiple vendors showcased AI-integrated solutions—from Fanuc’s AI-powered robot arms enabling flexible workflows to Roboteon’s simulation tool quantifying robotic ROI in specific distribution centers. Meanwhile, Linde Material Handling launched myLinde, a telematics-based fleet management platform that integrates AI-adjacent capabilities like real-time battery analytics and equipment utilization tracking. For supply chain professionals, the implications are operational and strategic: AI deployment is no longer theoretical but demands cross-functional alignment on data governance, change management, and use-case prioritization—particularly where predictive accuracy directly affects inventory carrying costs or service-level agreements.
Source: DC Velocity
Compiled from international media by the SCI.AI editorial team.
