Retail AI: Emulate Walmart's Strategy with Top Tools

To executives asking “How can AI be used in retail?”—Walmart’s example is a resounding answer. In Q3 2023, Walmart posted an 24% YOY growth exceeding expectations, largely due to its investment in retail AI initiatives. “There’s a great opportunity for us to be more anticipatory, and to be more relevant to [customers] and communicate in a way that shows that we know who they are, in a healthy way, while protecting privacy,” quipped CEO Doug McMillon during a 2024 earnings call.

McKinsey predicts that AI in retail commerce could add up to $600 billion in value annually, with retail giants like Walmart setting prime examples. The global retail artificial intelligence market is projected to reach $34.4 billion by 2028. Retail executives were already predicting AI would be table stakes in 2018—with that now certainly the case, how can medium to large brands and organizations leverage Walmart’s retail AI playbook?

Retail AI Adoption: “Table Stakes”

The phrase “table stakes” feels stark and immediate when examining two cautionary tales of once-dominant retailers: Sears and Toys "R" Us.

Sears, once the largest retailer in the world, filed for bankruptcy in 2018 after 132 years in business, a downfall largely attributed to its failure to adapt to changing consumer preferences and embrace digital technologies, including retail AI technologies. While ecommerce giants were leveraging AI for personalized marketing, inventory management, and supply chain optimization, Sears continued to rely on traditional retail methods, leading to poor inventory management, with stores often overstocked with unpopular items while running out of in-demand products. By failing to implement AI-powered customer analytics, Sears also missed out on valuable insights that could have helped them tailor their offerings to changing consumer preferences. By the time Sears attempted to catch up, it was too late – the company had already lost significant market share to more technologically advanced competitors.

Toys "R" Us met a similar fate in 2017. The toy retailer's inability to compete with Amazon's AI-powered recommendation engines and supply chain optimization led to its bankruptcy. While Amazon used sophisticated AI algorithms to predict toy trends, optimize pricing, and manage inventory across its vast network, Toys "R" Us struggled with an outdated ecommerce platform and inefficient supply chain. Without AI-driven demand forecasting, the company suffered frequent stock-outs of popular toys during crucial holiday seasons, driving customers to competitors. Moreover, Toys "R" Us couldn't match the personalized shopping experience offered by online competitors, who used AI to suggest products based on a customer's browsing and purchase history. Ultimately, traditional merchandising techniques proved unsustainable.

Retailers who fail to adopt AI risk losing market share, customer loyalty, and ultimately, their businesses. In contrast, McKinsey estimates the potential impact value of generative AI on retail at $400–$660 billion annually.

Table stakes indeed.

Walmart's Retail AI Strategy: A Case Study

Walmart's journey into AI in retail began in earnest in 2017 with the launch of its Store No. 8 tech incubator. Since then, Walmart has implemented retail AI comprehensively across its business. In inventory management alone, Walmart's AI systems predict demand, optimize stock levels, and reduce waste—improving profitability and aligning with growing consumer demands for sustainable retail practices.

Beyond inventory control, Walmart has deployed AI-powered supply chain optimization tools, enhancing customer satisfaction and reducing costs. It’s retail AI, Route Optimization, alone has helped the company avoid 30 million unnecessary miles of driving. This improvement in logistics efficiency has been crucial in Walmart's ability to compete with ecommerce giants like Amazon.

And as of March 2024, Walmart now offers its Route Optimization technology to all businesses as a Software as a Service (SaaS) solution.

On the customer-facing front, Walmart's AI-driven personalization engine has increased online sales conversions, demonstrating the power of AI in understanding and predicting consumer behavior. In-store, the introduction of AI-powered robots for floor cleaning and shelf scanning has freed up associates to focus on customer service. Walmart's foray into AI-powered negotiations with suppliers, using chatbots to automate deal-making, resulted in 1.5% average in cost savings plus 35 extra days of extended payment terms

In 2020, amidst a global pandemic that disrupted traditional retail, Walmart's ecommerce sales grew by a staggering 79%.

But Walmart's approach to retail AI isn't just about implementing isolated technologies; it's about creating a holistic, AI-driven ecosystem that touches every aspect of its business. From supply chain to customer service, from inventory management to supplier negotiations, Walmart's retail AI strategy has transformed the company into a tech-forward retail powerhouse. This approach serves as a blueprint for other retailers, showing that embracing AI isn't just about adopting new technologies—it's about reimagining the entire retail business model for the digital age.

Be Like Walmart: How to Implement Retail AI Solutions

1. Optimize Inventory and Supply Chain Management with AI

Walmart's AI-driven approach to inventory and supply chain management offers a blueprint for medium to large retailers. By implementing machine learning for demand forecasting, retailers can adopt similar systems to automate stock replenishment and develop real-time inventory tracking.

Mid-sized businesses and enterprises can leverage retail AI-powered tools specifically designed for their scale: 

• Blue Yonder's AI-driven Luminate Platform offers end-to-end supply chain optimization, from demand planning to warehouse management.
• Manhattan Associates provides SCALE, an AI-powered solution that helps retailers optimize inventory across channels.
• Relex Solutions offers AI-driven demand forecasting and automatic replenishment for more targeted inventory management.

These tools, while not requiring Walmart-level resources, still provide powerful AI capabilities that can significantly improve inventory accuracy, reduce waste, and optimize supply chain operations, allowing medium to large retailers to compete more effectively in the AI-driven retail landscape.

2. AI-Enhanced Customer Experiences, Online and In-Store

Walmart's success in enhancing customer experience through retail AI provides valuable lessons for other retailers. The company's AI-driven "Ask Sam" app helps associates quickly answer customer queries—a strategy that can be adapted by medium to large retailers to boost their customer service capabilities. Walmart's implementation of AI-powered personalized recommendations and targeted marketing campaigns can be mirrored to increase online sales conversion rates.

In-store, Walmart's "Scan & Go" technology, powered by computer vision, allows customers to skip checkout lines, demonstrating how retail AI can seamlessly blend online and offline shopping. By adopting similar AI-driven omnichannel strategies, retailers can create a unified and enhanced customer journey across all touchpoints.

3. Automate Supply Negotiations

Walmart's groundbreaking use of AI in supply negotiations offers a compelling case study for medium to large retailers. In 2021, Walmart deployed a generative AI chatbot from Pactum AI to negotiate with suppliers, successfully closing deals with 64% of suppliers in the pilot, far exceeding the 20% target. This initiative resulted in an average 1.5% cost savings and extended payment terms to 35 days. Subsequent deployments across multiple countries saw the chatbot closing deals with 68% of suppliers, generating an average savings of 3%.

Medium to large brands can implement similar retail AI-powered negotiation systems to optimize contract terms, reduce costs, and improve supplier relationships:

• Pactum AI, used by Walmart, offers a platform that uses advanced language AI to conduct automated negotiations at scale, handling thousands of supplier negotiations simultaneously.
• Keelvar provides AI-powered sourcing automation software that can handle complex negotiations and identify optimal supplier agreements.

For retailers looking to start smaller, platforms like SAP Ariba incorporate AI-driven insights into the negotiation process, helping buyers make more informed decisions. LevaData is another option, providing cognitive sourcing capabilities, enabling businesses to identify savings opportunities and optimize supplier relationships.

The Future of Retail AI

The retail AI revolution is already here. By following Walmart's example and implementing these steps, organizations can harness the power of retail AI to optimize operations, enhance customer experiences, and drive growth.

As Gary Hawkins, Founder and CEO of the Center for Advancing Retail & Technology, aptly puts it: "To win in retail, you have to win in tech."