Fortune | FORTUNE 07月23日 22:15
How Walmart, Amazon, and other retail giants are using AI to reinvent the supply chain—from warehouse to checkout
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在全球贸易摩擦、劳动力短缺和经济不确定性加剧的背景下,企业正积极拥抱人工智能以应对供应链挑战。高达59%的企业表示供应链问题在过去一年有所加剧,而82%的企业计划在下一财年增加对AI驱动的供应链工具的投入。沃尔玛已率先将实时AI系统应用于其全球供应链,覆盖美国、哥斯达黎加、墨西哥和加拿大等市场,显著提升了趋势追踪、商品设计、需求预测和库存调配的效率,将数月项目缩短至数周。亚马逊也大力投资AI技术,旨在通过生成式AI地图技术、AI需求预测模型和智能机器人系统优化物流,为消费者带来更精准的配送和更快的购物体验。AI正从传统的反应式分析转向实时预测和干预, agentic AI(自主AI)的兴起更是能够自动化复杂任务,实现供应链的全面智能化。

🤖 **AI驱动的供应链现代化加速**:在 tariffs、劳动力短缺和全球不确定性增加的时代,AI已成为企业应对供应链挑战的关键工具。Nvidia调查显示,59%的公司面临日益严峻的供应链问题,82%计划增加AI供应链工具的支出,预示着AI在供应链领域的广泛应用和重要性日益凸显。

🛒 **零售巨头AI应用实践**:沃尔玛已成功应用实时AI系统重塑其全球供应链,通过AI追踪消费者趋势、设计商品组合、预测需求并优化库存,将项目周期从数月缩短至数周。其Trend-to-Product系统能根据社交媒体和搜索数据生成产品概念,直接对接原型制作和采购。亚马逊也在其re:Invent大会上展示了Wellspring(生成式AI地图技术)、AI需求预测模型和agentic AI机器人系统,旨在提升物流效率和用户体验。

💡 **AI能力从预测到自动化升级**:早期的供应链现代化工具多依赖历史数据进行预测和路线规划,属于反应式系统。而当前AI应用则具备实时预测甚至指导性能力,能够自动化运营、动态调整运输路线、优化跨区域库存、预警供应商风险,并支持店内自助结账。agentic AI(自主AI)的出现,更是使AI能够以极少的人工干预执行复杂任务,极大地提升了生产力。

📈 **Agentic AI驱动供应链效率新飞跃**:agentic AI(自主AI)是推动供应链下一轮发展的关键。它允许规划者通过自然语言触发任务,获得指导性分析、主动洞察和自动问题识别。新一代AI能够协调整个供应链的自动化,实现前所未有的协同效应,从而带来更高效的规划、打破部门壁垒、优化营运资本,并显著减少浪费。

📦 **AI助力提升零售运营速度与精准度**:Albertsons等零售商利用AI不仅进行预测和优化,还实时分析非结构化供应商信息(如邮件、PDF),提取关键交付信息、风险和承诺,从而帮助采购团队避免遗漏。AI还用于优化门店劳动力分配,确保收货和补货团队与入库货量匹配,如Albertsons在高峰期将商品从装卸区送达货架的速度提升了15%。AI在零售供应链中有效化解复杂性,赋能一线团队快速响应。

In an era marked by tariffs, labor shortages, and global uncertainty, that mission has never been more critical. According to a recent Nvidia survey, companies are feeling the pressure, with 59% of respondents saying that their supply-chain challenges have grown in the past year. Increasingly, companies are turning to AI to help address these challenges, with 82% of companies planning to increase spending on AI-powered supply-chain tools in the next fiscal year.

Last week, Walmart—the world’s largest retailer—announced it has revamped its global supply chain using real-time AI systems. First deployed in the U.S., the technology is now live in markets like Costa Rica, Mexico, and Canada. These tools help track consumer trends, design product assortments, forecast demand, shift inventory to high-need areas, and reduce overstock. According to Walmart, projects that once took months can now be completed in weeks. 

For example, Walmart has developed a system called Trend‑to‑Product—an AI-driven, multi-agent engine that tracks trends (using social media, search data, etc.), generates mood boards and product concepts, and feeds them directly into prototyping and sourcing processes. 

“At this scale, the only way to move faster is to move smarter,” Vinod Bidarkoppa, chief technology officer at Walmart International, said in a blog post. “We’re creating systems that turn real-time signals into real-time action, freeing up associates and delivering for customers.”

Walmart’s top competitor, Amazon, has also been highlighting its AI-powered supply-chain advancements. At the company’s re:Invent event in 2024, CEO Andy Jassy talked extensively about how continuous improvement in the supply chain can save a few pennies per package that add up to billions of dollars at scale. 

Last month, Amazon shared a blog post showing off big new investments in AI applications that solve logistics challenges in the global supply chain: Wellspring, a generative AI mapping technology; an AI-powered demand forecasting model that’s powering Amazon’s supply chain; and new robotics capabilities using agentic AI systems. 

“While these systems work behind the scenes, customers will certainly experience their benefits: more accurate delivery locations, faster shipping options, and improved availability of the products they want, when they want them,” said the blog post.

From forecasting to full-on AI automation

Retailers have been modernizing their supply chains for more than a decade with tools like cloud-based software, AI analytics, and connected sensors. These technologies have helped them plan more accurately, track inventory in motion, and improve order accuracy.

That push accelerated during the COVID-19 pandemic, as shortages, demand spikes, and supply-chain disruptions forced companies to adapt. Services like same-day delivery and buy-online, pick-up-in-store (BOPIS) went from conveniences to must-haves—and they’ve remained part of the baseline ever since.

But the current wave of AI deployment is different, said Manish Kapoor, founder and CEO of Growth Catalyst Group. Earlier systems were helpful but largely reactive—relying on historical data for forecasting or route planning.

“Now, AI operates in real time with predictive and even prescriptive capabilities,” Kapoor said. “These systems can automate operations, reroute shipments on the fly, rebalance inventory across locations, flag supplier risks before they cause disruptions, and even support automated checkout in stores.”

What’s driving the next leap forward is the rise of agentic AI—systems that can carry out complex tasks with minimal human involvement, according to Venky Veeraraghavan, chief product officer at AI platform DataRobot. 

“The rise of agentic AI offers a tremendous opportunity to boost productivity,” he said. “Planners can trigger tasks using natural language and receive guided analyses, proactive insights, and automatic issue identification. This new generation of AI can coordinate automation across the entire supply chain in ways that weren’t possible before.”

The result? More efficient planning, fewer silos between departments, better use of working capital—and significantly less waste.

“AI is reshaping supply chains, and some of the most transformative use cases are coming from systems of AI agents,” said Garth Hoff, director of industry strategy at Pricefx. “AI has become an indispensable tool in forecasting and inventory planning. With tariffs, timing is everything—if you’re overstocked or under-forecasting demand, you’re taking a direct hit to margins. AI helps brands sense demand shifts earlier and simulate how different sourcing or tariff scenarios would impact costs.”

Albertsons now moves products to store shelves 15% faster

For Albertsons, one of the largest food and drug retailers in the U.S. with over 2,200 stores in 35 states, AI is used not just for forecasting and optimization, but to reimagine how stores interact with the supply chain in real time.

Chandrakanth Puligundla, tech lead and data analyst at Albertsons, gave an example of how the retailer uses AI to assist in allocating store labor for receiving and replenishment. 

“Models predicting daily inbound shipment volumes were built so that they match available store labor,” he explained. “That matching makes sure that the teams get staffed in a proper way for handling all deliveries without overstaffing or any delays.” Albertsons now moves products from the loading dock to store shelves about 15% faster during peak shopping seasons.

A new trend, he added, is the use of AI to analyze unstructured supplier information, such as emails and PDFs. This technology extracts key details about delivery changes, risks, and commitments, helping procurement teams avoid issues that are often overlooked by traditional systems. 

“In retail supply chains, AI excels at clarifying complexity, allowing frontline teams to respond quickly and effectively,” he said.

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人工智能 供应链管理 零售业 AI应用 沃尔玛 亚马逊
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