Walmart, Amazon adopt opposing AI strategies for retail dominance

As the battle for retail dominance intensifies, Walmart and Amazon are adopting opposing AI strategies to reshape the shopping experience. Walmart is pursuing an open, partnership-based model, while Amazon is investing heavily in proprietary, in-house technology. This fundamental split reflects different bets on how to best leverage artificial intelligence for speed, scale, and customer engagement.

Analysis: Walmart Embraces Open AI Partnerships While Amazon Prefers Proprietary Approach

Walmart's AI strategy leverages partnerships with tech giants like OpenAI and Google, embedding its shopping experience into existing popular platforms. In contrast, Amazon's approach is proprietary, focusing on building its own AI infrastructure, from custom chips to foundational models, to control the entire customer journey.

Walmart's strategy centers on meeting customers on the platforms they already use. By integrating with leading AI models, it creates a seamless conversational commerce experience. An October 2025 partnership with OpenAI introduced "chat and buy" functionality directly within ChatGPT (Walmart Partners with OpenAI to Create AI-First Shopping Experiences). This was followed by a full catalog integration into Google's Gemini, offering features like reorder suggestions and delivery windows under three hours. Internally, this API-first mindset powers Sparky, a customer service agent, and four internal "super agents" for core operations like merchandising and supply chain, all guided by Walmart's vast retail dataset.

Amazon's Proprietary Flywheel: A Vertically Integrated Empire

Amazon, conversely, treats AI as a core component of its own infrastructure. Its massive investment includes a pledge of up to $50 billion for AWS to expand secure supercomputing capacity, leveraging custom Trainium chips and platforms like SageMaker and Bedrock (Amazon to invest up to $50 billion to expand AI and supercomputing). These proprietary systems, including the Nova family of foundation models, power everything from Alexa to Zoox autonomous driving. This commitment to internal ownership, backed by over $100 billion in 2025 capital expenditure, signals an ambition to control the entire AI stack, from silicon to software.

Strategic Trade-offs: Speed vs. Control

These opposing strategies create distinct advantages and disadvantages for each retail giant.

• Speed to Market: Walmart's partnership model allows for rapid deployment, integrating its services into existing AI assistants in weeks. Amazon's custom builds require longer development cycles.
• Differentiation: Amazon can achieve deeper, customized integrations, such as tailoring AI models to optimize Prime delivery. Walmart depends on the feature roadmaps of its third-party partners.
• Cost Structure: Walmart offloads massive compute costs to partners, while Amazon shoulders the full capital expenditure, aiming to capture cloud margins and achieve lower long-term costs at scale.
• Talent & Expertise: By partnering, Walmart leverages the expertise of established AI research teams. Amazon must compete directly to hire thousands of specialists for its in-house labs.

Market Outlook and Industry Signals

The broader retail industry appears to favor openness. A 2026 ITPro survey indicates that 79% of retailers see value in open-source or partnership strategies to avoid vendor lock-in. Still, with nearly half using proprietary tools for initial tests, the market points toward a hybrid future.

Walmart's strategy provides a roadmap for retailers without massive R&D budgets. Conversely, Amazon's vertically integrated stack is attractive to regulated sectors that require data sovereignty and built-in compliance. As both strategies mature, Walmart must prove its integrations can scale, while Amazon must demonstrate that its investment translates into a quantifiably superior customer experience.

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How are Walmart and Amazon approaching AI differently in 2025-2026?

Walmart is betting on open partnerships. In the past six months it has tied its catalog and checkout flow to OpenAI's ChatGPT and to Google's Gemini assistant, letting shoppers build baskets and pay without leaving those platforms. The retailer calls this a "hybrid approach": it owns the data and fulfillment, but the conversational layer is rented from specialists.
Amazon, by contrast, is pouring more than $100 billion of 2025 cap-ex into AWS data centers, custom Trainium chips, and closed services such as Amazon Bedrock and Nova models. The goal is to keep every inference, recommendation, and fulfillment optimization inside house walls, selling the same stack to governments and enterprises.

Which model reaches the customer faster?

Open partnerships win the sprint. Walmart's Gemini integration went from announcement to live shopping in three weeks and already covers three-hour delivery for millions of SKUs. Amazon's internal tools power Alexa and the website, but new GenAI features are still labeled "coming soon" for most third-party sellers; the heavy infrastructure spend will not show up in consumer-facing features until late 2026.

What do the two strategies cost, and who saves money?

Walmart pays zero cap-ex for the large language models; it only shares a small affiliate style fee when a basket closes on Google or OpenAI. Amazon's bill is the opposite: $50 billion earmarked for U.S. government-grade super-computing alone, plus the salaries of thousands of chip and model engineers. The bet is that owning the stack will be cheaper per transaction at planet-scale, but today Walmart reports 72 % lower AI operating costs than its internal 2024 benchmark.

Where does each approach shine or stumble?

Open ecosystem
- Plus: 79 % of retailers say open-source or open-partner models let them avoid vendor lock-in and plug in best-of-breed updates every quarter.
- Risk: Walmart must trust Google and OpenAI with customer prompts; any policy change could break the experience.

Proprietary stack
- Plus: Deep integration - Amazon can fuse logistics simulation, fraud detection, and video ads inside one reinforcement loop, something outsiders never see.
- Risk: Speed to market is slower; if a new architecture breakthrough appears, Amazon must re-train its own chips, a 12-18 month cycle.

What does the industry forecast look like for 2026-2027?

Analysts expect the retail AI market to triple from $11.6 B in 2024 to $40.7 B by 2030, with inventory agents and hyper-personalization eating the biggest share. Walmart's open network could let it ride every new model wave, but Amazon's closed garden may deliver higher margin per order once the $100 B investment depreciates. Most experts predict a hybrid future: even Amazon is quietly testing third-party models for non-core markets, while Walmart is building a tiny internal team to fine-tune partner models on its own grocery data.