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Michael Hung , CEO of TradeBeyond, explains how AI and automation are leading retail supply chains into the future<\/strong><\/p>\n \u00a0<\/p>\n Retail executives are making <\/span><\/span>artificial intelligence<\/span><\/span> the cornerstone of their supply <\/span><\/span>chain<\/span><\/span> improvement<\/span><\/span> strategies <\/span><\/span>to stay ahead of the curve. <\/span><\/span>A <\/span><\/span>new study <\/span><\/span>of senior retail executives<\/span><\/span>, including VPs, directors, and senior managers from leading global retailers and brands<\/span><\/span>, <\/span><\/span>revealed a decisive trend: <\/span><\/span>AI<\/span><\/span> has <\/span><\/span>emerged<\/span><\/span> as the top priority for supply chain managers, with 28% of brands ranking AI implementation as their most c<\/span><\/span>ritical focus<\/span><\/span>over the next three years<\/span><\/span>.<\/span><\/span> This <\/span><\/span>embrace of<\/span><\/span> AI is driven by the need to enhance efficiency across supply chains, <\/span><\/span>just ahead of <\/span><\/span>other pressing goals such as increasing agility and resilience (26%) and scaling operations to support aggressive growth (22%). <\/span><\/span><\/p>\n AI ha<\/span>d long<\/span> been <\/span>anticipated<\/span> to be<\/span> a game-changer<\/span> in <\/span>retail<\/span>. N<\/span>ow<\/span> it<\/span> is<\/span> fully arriving in the supply chain sector, creating transformative impacts <\/span>almost overnight<\/span>. <\/span>This technology is rapidly bringing speed and efficiency to <\/span><\/span>a<\/span><\/span> new<\/span><\/span> level<\/span><\/span>, while also <\/span><\/span>becoming a critical <\/span><\/span>tool in retail\u2019s<\/span><\/span> drive toward sustainability, as <\/span><\/span>tightening global<\/span><\/span> regulation<\/span><\/span>s have<\/span><\/span> ma<\/span><\/span>de<\/span><\/span> it increasingly difficult to <\/span><\/span>maintain<\/span><\/span> compliance and efficiency without <\/span><\/span>sophisticated digital systems<\/span><\/span>.<\/span> For example, b<\/span>y <\/span>optimizing<\/span> routes and inventories, <\/span>AI <\/span>helps <\/span>reduce <\/span>unnecessary fuel consumpt<\/span>ion and waste<\/span>. <\/span>AI-powered tools are revolutionizing traceability by automating chain of custody verification and documentation, ensuring compliance with sustainability regulations. They also transform audit and risk management, analyzing supply chain data to predict risks and improve product quality while reducing costs.<\/span><\/span><\/p>\n We\u2019re already seeing some of retail\u2019s biggest names <\/span><\/span>leveraging<\/span><\/span>AI in their supply chains<\/span><\/span> with impressive results<\/span><\/span>. Walmart and Amazon are using AI-powered robots in fulfillment centers to manage inventory, process orders, and <\/span><\/span>optimize<\/span><\/span> storage space. <\/span><\/span>They\u2019re<\/span><\/span> also <\/span><\/span>utilizing<\/span><\/span> predictive analytics to forecast demand, ensuring products are available when and where they are needed. Zara is similarly using AI for demand forecasting and inventory management, analyzing sales data, social media trends, and other data sources to predict fashion trends more accurately and adjust accordingly, minimizing overproduction and stockouts. <\/span><\/span>For instance, Amazon’s Proteus and Sparrow robots<\/span><\/span>, which incorporate advanced automation and AI-driven capabilities,<\/span><\/span> help with sorting packages and managing inventory, enhancing both efficiency and safety.<\/span><\/span> Meanwhile, Walmart’s use of <\/span><\/span>Symbotic’s<\/span><\/span> AI-powered system has enabled it to fulfill online orders faster and with greater accuracy. This shift toward automation is allowing these retailers to stay competitive and meet increasing consumer demands.<\/span><\/span><\/p>\n All this is just the beginning. As AI evolves, <\/span>it’s<\/span> poised to take on even more complex roles.<\/span> Future applications are <\/span>on track<\/span> to extend into autonomous decision-making where AI systems will not only predict but also make real-time adjustments to supply chains without human intervention. Advanced AI is likely to manage <\/span>most <\/span>end-to-end<\/span> supply chain <\/span>processes<\/span>, from raw material acquisition throug<\/span>h to customer delivery<\/span>, allowing the promise of the most efficient supply chain control tower approach to take shape<\/span>.<\/span> This deeper integration promises to <\/span>transform<\/span> traditional supply chain models into dynamic, predictive networks that can more adeptly respond to global challenges and market fluctuations.<\/span><\/p>\n \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 Building the Data Foundation for AI <\/span><\/p>\n B<\/span>rands and retailers are <\/span>understandably <\/span>eager to <\/span>leverage<\/span> AI <\/span>in t<\/span>heir supply chain operations<\/span>,<\/span> but <\/span>in truth many have not yet created the digital infrastruc<\/span>tu<\/span>re to do so.<\/span> One major obstacle preventing businesses from realizing AI\u2019s potential is the lack of organized, centralized, real-time data. <\/span>To overcome this, companies need to start creating a central repository of supply chain data at the PO, SKU, and factory levels. <\/span><\/p>\n T<\/span>he foundation <\/span>for <\/span>optimizing<\/span> the benefits of AI for any organization<\/span> lies in the ability to interconnect thousands of data points from multiple data sets across your enterprise<\/span>, <\/span>both proprietary, <\/span>company-specific data as well as external environment data points from a range of outside databases. <\/span>That requires aggregating all data from <\/span>early-stage planning through the creation of product specifications, onto sourcing, costing, and <\/span>logistics<\/span>, and including detailed information on all suppliers along the supply chain up to the Nth tier<\/span>.<\/span> It\u2019s<\/span> only once businesses have <\/span>established<\/span> effective data management that they can begin unlockin<\/span>g AI’s full potential.<\/span><\/p>\n Digitalizing with a multi-enterprise platform<\/span> ensures that<\/span> data is current, <\/span>accurate<\/span>, and accessible, setting the foundation for <\/span>leveraging<\/span> AI. <\/span>These platforms provide<\/span> real-time supply chain visibility, allowing businesses to <\/span>monitor<\/span> their supply chains continuously, <\/span>identify<\/span> potential issues before they escalate, and make informed decisions based on <\/span>accurate<\/span>, up-to-date information<\/span>. <\/span>Establishing this robust digital <\/span>infrastructure<\/span> is the<\/span>key to<\/span> equipping<\/span> AI <\/span>with the data it needs for <\/span>predictive analytics<\/span> and<\/span> automated decision-making<\/span>.<\/span><\/p>\n Already these platforms are <\/span>deploying AI in innovative ways<\/span>, and <\/span>their<\/span> capabilities are continually expanding<\/span>.<\/span> New <\/span>AI-powered chain of custody tools<\/span> significantly <\/span>enhance<\/span>traceability by automating documentary verification and documenting the chain of custody of all materials. <\/span>These tools<\/span>proactively assess compliance risks and ensure that every link in the supply chain meets your company\u2019<\/span>s standards of sustainability<\/span> and <\/span>