Walmart Moves Toward the Other Side of Sam's

Introduction: A Quiet Retail Revolution

While public attention has been fixated on Sam's Club's rapid expansion in the Chinese market, Walmart's hypermarket division has been undergoing a fundamentally different transformation. From store portfolio restructuring to a major ramp-up in private-label investment, from AI-powered supply chain overhauls to the reconstruction of omnichannel digital capabilities, Walmart is moving toward "the other side of Sam's" — a retail evolution path that relies more heavily on technology and emphasizes efficiency iteration.

This is not merely one company's strategic pivot; it is a microcosm of the systemic transformation reshaping the entire supermarket retail industry under the impact of AI and digitalization.

Behind the Store Adjustments: From Scale Expansion to Lean Operations

Over the past two years, Walmart China has been continuously optimizing its store footprint. A large number of underperforming hypermarkets have been closed or renovated, replaced by more compact, higher-productivity community-format and upgraded stores. Behind this strategy lies Walmart's reassessment of the Chinese retail landscape.

The traditional hypermarket model of "big and comprehensive" is facing unprecedented challenges. Instant retail from e-commerce platforms, price pressure from community group-buying, and the fragmentation of consumer shopping habits are all forcing brick-and-mortar retailers to rethink the core value of physical stores. Walmart's chosen path is clear: use fewer stores to deliver higher operational density while leveraging technology to turn each location into a "data-driven retail terminal."

Reportedly, Walmart has introduced a significant amount of smart equipment and AI decision-making systems during its store renovation process. From intelligent replenishment algorithms to computer-vision-based inventory management, from real-time dynamic pricing via electronic shelf labels to heatmap analysis of customer traffic flow, technology is redefining what a "store" fundamentally means.

Private-Label Upgrades: AI-Empowered Differentiated Competition

If store adjustments represent "subtraction," then the increased investment in private labels is Walmart's most important "addition."

Private labels have long been a core weapon for global retail giants to build competitive moats. Sam's Club has established strong member loyalty through private brands like Member's Mark, while Walmart's hypermarket-side private-label portfolio — including Great Value, Marketside, and others — is also undergoing accelerated iteration.

The defining feature of this round of private-label upgrades is the deep embedding of AI technology across the entire chain from product selection to R&D. Walmart uses big data analytics and AI predictive models to precisely capture shifting consumer trends and shorten the cycle from insight to shelf for new products. For example, through cross-analysis of social media data, search trends, and sales data, AI systems can identify potential hit product categories weeks or even months in advance, providing data-backed guidance for private-label R&D direction.

On the supply chain side, Walmart's AI-driven supplier management platform is playing an increasingly critical role. The platform monitors supplier capacity, quality metrics, and delivery efficiency in real time, using algorithms to optimize procurement strategies and minimize costs while maintaining quality. This enables private labels to achieve a competitive price advantage over leading national brands while sustaining or even improving profit margins.

Digital Omnichannel: Entering the Deep Waters of Online-Offline Integration

Walmart's transformation is also reflected in the continuous strengthening of its omnichannel capabilities. Deep partnerships with platforms such as JD Daojia and Meituan, along with iterative upgrades to its proprietary mini-program, have driven a steady increase in Walmart's online order share.

In this process, AI technology plays the role of a "central nervous system." Intelligent fulfillment systems perform real-time scheduling based on order density, store inventory, and delivery capacity, compressing average picking and delivery times to industry-leading levels. Personalized recommendation algorithms, based on users' purchase history and behavioral preferences, deliver individualized product displays across online channels, effectively boosting conversion rates and average transaction values.

Notably, Walmart globally is accelerating the deployment of generative AI applications. In the U.S. market, Walmart has already applied large language models to customer service conversations, product description generation, and internal knowledge management. These experiences and technological capabilities are gradually being transferred to the Chinese market, with the potential to further enhance operational efficiency.

Industry Mirror: The AI Transformation Blueprint for Supermarket Retail

Walmart's transformation is not an isolated case. Across China's entire supermarket retail industry, an AI-driven systemic transformation is accelerating.

Yonghui Superstores, after undergoing its own restructuring, has similarly made intelligent supply chains and data-driven category management core capability-building priorities. Freshippo (Hema) has positioned itself as a "data company" since its inception, and its practices in AI pricing and intelligent logistics have provided important references for the industry. While Pangdonglai's viral popularity stems more from its differentiated service philosophy, its highly efficient supply chain management also relies on digital tools.

From a broader perspective, the AI transformation of the supermarket retail industry is exhibiting several clear trends:

First, moving from localized applications to systemic reconstruction. AI is no longer just an efficiency tool for a single link in the chain; it is reshaping the entire process from procurement, warehousing, and logistics to marketing and customer service.

Second, private labels are becoming the best testing ground for AI deployment. Because retailers have end-to-end control over private labels from R&D to sales, AI technology can achieve its fullest value realization within this closed loop.

Third, the strategic value of data assets is being redefined. Retailers with massive consumer behavioral data are using AI to convert that data into precise commercial decision-making capabilities, forming the core competitive barrier of next-generation retail.

Outlook: The Next Decade of Retail Belongs to 'AI-Native'

Walmart's move toward "the other side of Sam's" is essentially an exploration of an AI-driven retail path distinct from the warehouse club model. Sam's Club's success is built on the flywheel of curated SKUs and membership, while the future of Walmart's hypermarket division may depend more on technology's penetration and transformation of every capillary of traditional retail.

It is foreseeable that future supermarket retail competition will no longer be solely a contest of "location selection, product selection, and talent selection," but a comprehensive showdown in data capabilities, algorithmic capabilities, and AI application capabilities. Retail enterprises that can be the first to complete the transition from "experience-driven" to "intelligence-driven" operations will seize the initiative in the next decade's industry shakeout.

For the AI industry as a whole, the vast depth of retail scenarios also represents enormous commercialization opportunities. From computer vision to natural language processing, from predictive analytics to generative AI, virtually every mainstream AI technology direction can find high-value deployment points in retail scenarios. Walmart's transformation story is not only a narrative of retail industry change but also a vivid footnote to AI technology's march into industrial depth.