
AI in the Supply Chain: 5 Practical Use Cases That Deliver Value
Explore five practical AI supply chain use cases and the data, integration, governance, and KPIs required to turn each one into measurable value.
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Fast-moving consumer goods experience weather and price-related changes more than others. They are also heavily impacted by certain social movements and health concerns that undermine consumer confidence. Many are therefore turning to online shopping and the advantages it offers, such as availability of information, ease of delivery and reimbursement, and extensive choices. The rise of these new consumption patterns is generating growth and order variety. Therefore, having a high-performance Supply Chain is the key to meeting such requirements. Manufacturers, therefore, have every incentive to invest in a Connected Supply Chain. For example, ROI can reach 18%, with all sectors of activity combined1. The problem is that 57% of Supply Chain managers surveyed were very reluctant to make such an investment2.
Generix Group takes stock of the primary strengths of the Connected Supply Chain including: reliability and transparency of information, better management of quality-related incidents, optimization of flows, the role of artificial intelligence and blockchain. The themes discussed are divided into three parts:

Explore five practical AI supply chain use cases and the data, integration, governance, and KPIs required to turn each one into measurable value.

Generix is proud to once again be recognized in Gartner 2026 Magic Quadrant™ for Warehouse Management Systems (WMS)

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