NVIDIA
All Dataleo news, jobs, analyses and tutorials around NVIDIA in Supply Chain and Operations.
News (5)
Kinaxis and NVIDIA Explore Long-Running AI Agents for Continuous Supply Chain Planning
Kinaxis disclosed a collaboration with NVIDIA to explore long-running AI agents that could continuously optimize and adapt Supply Chain Planning decisions at scale.
NVIDIA-backed factory upgrade expands AI-component manufacturing in Texas
Gartner’s 2026 Supply Chain Top 25 puts autonomous workforces and AI orchestration at the center
Gartner has published its 2026 Global Supply Chain Top 25, with Schneider Electric retaining first place ahead of NVIDIA and Walmart. The research highlights three major themes: autonomous workforces combining people and machines, adaptive physical networks and end-to-end orchestration.
The ranking points to a broader shift in how leading supply chains are evaluated. AI is moving beyond isolated features toward workforce design, connected decision-making and coordination across enterprise and partner networks.
Schneider Electric is cited for its use of generative and agentic AI to improve visibility, prediction and action coordination, making the ranking a useful market signal on the operating-model implications of Supply Chain AI.
This matters for Supply Chain Leadership because AI maturity is increasingly linked to how work, decisions and networks are orchestrated, not simply to software deployment. The leading organizations are redesigning roles, escalation paths and collaboration models around human-machine teams.
The governance challenge is to preserve accountability as decisions become more distributed and automated. Companies need clear ownership, auditable logic and boundaries between machine recommendations, human approval and execution.
Kinaxis brings NVIDIA AI acceleration into Maestro for large-scale planning optimization
Kinaxis announced work with NVIDIA to accelerate planning optimization in Kinaxis Maestro. The announcement matters for supply chain teams because advanced planning scenarios are increasingly constrained by computation speed, data volume and the need to compare options quickly.
For Concurrent Planning, faster optimization can shorten the time between disruption, scenario analysis and decision. The practical value will depend on whether planners can understand the trade-offs behind AI-accelerated recommendations and apply them through governed Planning Governance.
This is a strong signal that AI infrastructure is becoming part of the planning stack. For Supply Chain AI, acceleration matters only if scenario results remain explainable, auditable and usable by planners under time pressure.
