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In the supply chain game , the next disruption is always around the corner . With ongoing geopolitical issues , climate-related events , labor disruptions , and more , established supply chains continue to be hit by sudden upsets . Fortunately , fewer companies are operating in the dark by investing in AI-powered supply chain resilience .
AI plays an essential part in reshaping supply chains through better analytics , enhanced visibility and increased accuracy . It is key to organizations moving from a reactive approach to supply chain risk management ( SCRM ), to a proactive one .
In this article , we take a closer look at four ways organizations are using AI to improve their SCRM strategies to stay ahead of disruptions .
Supply chain mapping
Many companies have some visibility into where suppliers and contractors are located around the world . However , the indirect tiers ( Tier 2 + and below ) are where approximately 85 percent of disruptions happen .
To rapidly gain insights into their most likely suppliers , companies can start by utilizing AI-powered mapping . However , coupling this with multi-tier , supplier-validated mapping will provide the most accurate picture of an organization ’ s entire supplier network . Having full visibility and knowledge enables companies to get a head start when a disruption strikes .
For example , the ongoing disruption to supply in the Red Sea in 2024 highlights why this is so important . Shipping delays have impacted anything from furniture to some of the largest automakers globally . In February , EV manufacturer , Tesla , was forced to shut down a factory near Berlin from January 29 to February 11 due to prolonged shipment delays .
By investing in AI and supplier-validated mapping , down to the indirect tiers , businesses can identify where their supply chains are reliant on regions at risk of geopolitical conflict right down to the part level .
Identifying risks in real time with 24 / 7 AI monitoring
There is great potential in what predictive AI models can enable organizations to achieve . For instance , by scanning data sets of tens of thousands of text sources , AI can identify and predict which disruptions will negatively impact a company ’ s supply chain down multiple tiers . This is what Resilinc ’ s global AI-powered risk monitoring solution , EventWatchAI , achieves ; helping organizations proactively prepare for disruptions through real-time alerts .
What ’ s more , predictive AI models can also be used to track purchase orders and commodities , giving organizations insight into delays and material prices in real-time . By watching commodities with this level of
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