Walmart's Gemini Deal: Building the Infrastructure Layer for Agentic Commerce

Walmart is placing a massive wager on the next technological paradigm in retail. The company frames its recent partnership with Google as part of a fundamental shift away from traditional search-and-click shopping. The transition from traditional web or app search to agent-led commerce represents the next great evolution in retail, according to incoming CEO John Furner. This isn't incremental improvement; it's a bet on a new S-curve where AI agents, not human users, initiate and orchestrate the entire shopping journey.

Walmart's strategy is to build the foundational infrastructure for this future. It's not chasing generic large language models. Instead, the company is deploying what it calls "purpose-built agentic AI", specialised tools trained on its vast proprietary retail data. This surgical approach contrasts with competitors using off-the-shelf solutions. The goal is to create systems that understand user intent and can take action on their behalf, moving from reactive search to proactive, predictive commerce. This is the core of what Walmart calls "agentic commerce in action."

This Gemini deal is the latest, most visible step in a multi-year effort to own this infrastructure layer. It follows an earlier partnership with OpenAI's ChatGPT, announced in October, which enabled "Instant Checkout" for purchases within the AI chatbot. Together, these moves position Walmart as a first-mover, actively rewriting the retail playbook. The company is building a dual-track strategy: one focused on its own AI tools like the Sparky chatbot and the "Wallaby" retail-specific LLM, and another on strategic partnerships to embed its offerings into the dominant AI platforms of the future. The bet is that by securing its place in the agent's workflow, Walmart ensures it remains the transactional endpoint for the next generation of shoppers.

The Infrastructure Layer: Universal Commerce Protocol and Data Leverage

The real strategic value of the Walmart-Gemini deal lies not just in a new feature, but in the creation of a potential industry standard. The partnership is built around an open standard called the Universal Commerce Protocol, which Walmart is developing and making accessible directly within Google's AI assistant. This protocol is the foundational infrastructure layer for agentic commerce. It provides a universal language for AI agents to discover, recommend, and transact with retailers, moving beyond the walled gardens of individual apps.

This setup creates a powerful symbiosis. For Google, the deal is a critical first-mover play to secure a foothold in the emerging agent economy. Gemini is on a roll, rapidly gaining users and benchmarks, but it still trails ChatGPT in overall adoption. By embedding Walmart's massive retail ecosystem into its core assistant, Google gains immediate access to a vast, ready-made user base and a proven fulfillment network. For Walmart, the benefit is equally profound. It gains a direct channel into Google's AI platform, reaching customers at the very beginning of their shopping journey, often before they even think about a specific retailer. This is a direct counter to the trend of discovery starting in an AI chatbot rather than on Walmart's own sites.

Yet, Walmart's scale and proprietary data give it significant leverage to shape this new protocol. The company is not a passive vendor; it is the architect of the standard. Its data on past online and in-store purchases and its unmatched assortment are the fuel that makes the protocol valuable. By controlling the protocol, Walmart ensures its data and fulfillment capabilities are prioritized within the agent's workflow. This is a classic infrastructure play: by building the rails, you dictate the terms of the future train.

The competitive context sharpens this calculus. This move positions Google directly against OpenAI, which already has its own Instant Checkout deal with Walmart. The protocol battle is now on. Walmart's strategy is to build a dual-track approach: it's partnering with both major AI platforms to maximize its reach while simultaneously establishing its own open standard. The goal is to become the indispensable data and logistics layer for any agentic commerce system, regardless of which AI engine a customer uses. In this race to own the infrastructure, Walmart's data moat and scale are its most potent weapons.

Exponential Adoption and Operational Impact

The partnership's aim is to capture a larger share of the customer's entire shopping journey, not just the final transaction. By embedding Walmart directly into Google's AI assistant, the goal is to increase engagement and conversion at the very start of the process. Gemini will automatically include Walmart and Sam's Club in-store and online products when it's relevant, surfacing items during natural conversations. This creates a continuous loop: inspiration in the chat leads to discovery, then to purchase, with the system recommending complementary goods based on past behavior. For Walmart, this is a direct path to boosting revenue from its advertising and online marketplace businesses, which are already key growth engines.

The potential for exponential adoption is built into this model. As AI agents become more capable, the number of interactions they can manage scales far beyond human capacity. Each conversation with a customer is a new data point and a new potential transaction. The Universal Commerce Protocol is designed to be the standard that makes this seamless, potentially allowing Walmart to scale its reach across multiple AI platforms without rebuilding its infrastructure each time. The company's vast data and fulfillment network provide the fuel for this engine, creating a flywheel where more interactions improve the AI's recommendations, which in turn drive more sales and more data.

Yet, the most concrete proof of AI's power may be in the back office. Walmart has already demonstrated that its internal agentic systems can drive dramatic efficiency gains. Agentic systems are increasingly embedded across its operations, from automating merchant data tasks to shortening fashion production timelines by 18 weeks. This isn't just a cost-saving measure; it's a fundamental acceleration of the product lifecycle. In a fast-moving retail environment, reducing time-to-market by nearly half a year is a massive competitive advantage. It allows Walmart to respond to trends faster, reduce markdowns, and capture more value from its assortment. This operational leverage is the hidden engine that supports the front-end customer experience.

This creates a clear tension in the valuation. Walmart's stock trades at a premium, with a price-to-earnings ratio nearing 40, reflecting high expectations for this growth. Yet, its core retail margins remain thin, a reality of its everyday low-price model. The investment in AI is a bet that the efficiency gains and new revenue streams will eventually widen those margins enough to justify the current multiple. The exponential adoption of agentic commerce could be the catalyst, but the company must deliver on both the customer-facing promise and the operational transformation to close the gap between its current profitability and its future potential.

Catalysts, Risks, and the Path to Monetization

The path from announcement to exponential adoption is paved with specific milestones. The first critical signal will be the launch timeline and initial user uptake. While the companies have not disclosed a date, the feature is expected to roll out soon in the U.S. The experience will start first in the U.S. and then expand internationally. Early adoption rates will be a direct read on the S-curve for agentic commerce. If users begin routinely discovering and purchasing through Gemini conversations, it validates the core thesis. A slow or underwhelming start would signal that the agent-led shift is still nascent or that the integration feels clunky. The real test is whether this becomes a habitual part of the shopping workflow.

The most significant risk is that this partnership enhances Google's ecosystem without significantly increasing Walmart's profitability or market share. Google is on a roll, rapidly gaining ground against ChatGPT after years of taking heat as the slow-moving leviathan in the AI race. By embedding its shopping experience into Gemini, Walmart is giving Google a powerful new tool to lock in users and capture more of the commerce pie. The danger is that Walmart becomes a valuable supplier to Google's platform, not a dominant player within it. The company must ensure the deal drives incremental revenue and market share, not just improves Google's competitive position. Its high valuation demands that this infrastructure bet directly translates to wider margins and a larger slice of the future retail market.

Watch for two key indicators of scaling: integration with Walmart's other AI tools and expansion to international markets. The company is building a suite of proprietary systems, from the Sparky chatbot to the "Wallaby" retail-specific LLM. Success will depend on stitching these tools together into a seamless, end-to-end agentic experience. Early signs of integration-like Sparky surfacing Walmart products within Gemini conversations-would show a unified front. Similarly, the international expansion is a crucial test of the Universal Commerce Protocol's universality. If the model works in other regions, it proves the infrastructure can scale beyond the U.S. market. If it stalls, it suggests local data, regulatory, or fulfillment hurdles are more complex than anticipated.

The bottom line is that this is a high-stakes infrastructure play. The catalysts are clear: a launch date, strong early adoption, and signs of integration. The primary risk is a one-sided benefit to Google. For Walmart, the path to monetization runs through proving that its data and logistics moat can be leveraged across multiple AI platforms to drive both efficiency and growth. The coming months will show if this is a foundational bet or a costly distraction.