Walmart’s December 9 transfer to Nasdaq wasn’t just a symbolic gesture. The US$905 billion retailer is making its boldest claim yet: that it’s no longer a traditional discount chain, but a tech-powered enterprise using AI to fundamentally rewire its retail operations.
But beyond the marketing spin and the parade of AI announcements, what’s genuinely transforming at the world’s largest retailer – and where are the gaps between ambition and execution?
The Agentic AI pivot: Purpose-built, not off-the-shelf
Walmart’s AI strategy diverges sharply from competitors chasing generic large language models. According to CTO Hari Vasudev, the company is deploying what it calls “purpose-built agentic AI” – specialised tools trained on Walmart’s proprietary retail data rather than one-size-fits-all solutions.
“Our approach to agentic AI at Walmart is surgical,” Vasudev wrote in a May 2025 blog post. “Extensive early testing proved that, for us, agents work best when deployed for highly specific tasks, to produce outputs that can then be stitched together to orchestrate and solve complex workflows.”
This translates to tangible applications, the company says: Walmart’s “Trend-to-Product” system cuts fashion production timelines by 18 weeks. Its GenAI Customer Support Assistant now routes and resolves issues autonomously without human intervention.
Developer productivity tools handle test generation and error resolution in CI/CD pipelines. Meanwhile, the company’s retail-specific LLM “Wallaby” – trained on decades of Walmart transaction data – powers everything from item comparison to personalised shopping journey completion.
The infrastructure underpinning this? Element, Walmart’s proprietary MLOps platform, designed to avoid vendor lock-in and optimise GPU use in multiple cloud providers. It’s an in-house “factory” that gives Walmart speed and flexibility competitors wrestling with third-party platforms can’t match.
Real numbers: Where AI delivers measurable impact
Walmart has been unusually transparent about specific ROI metrics, offering a rare glimpse into enterprise AI economics:
Data operations: GenAI improved over 850 million product catalogue data points – a task that would have required 100 times the headcount using manual processes, according to CEO Doug McMillon’s August 2024 earnings call.
Supply chain efficiency: AI-powered route optimisation eliminated 30 million unnecessary delivery miles and avoided 94 million pounds (42,000 tons) of CO2 emissions. The company won the prestigious Franz Edelman Award in 2023 for this technology – and has since commercialised it as a SaaS product for other businesses.
Store operations: Digital twin technology predicts refrigeration failures up to two weeks in advance, auto-generating work orders complete with visual models, wiring diagrams, and required parts. Sam’s Club’s AI-powered exit technology has reduced member checkout times by 21%, with over 64% of members now using the friction-free system in all locations.
Customer experience: Dynamic delivery algorithms analyse traffic patterns, weather conditions, and order complexity to predict delivery times down to the minute, enabling 17-minute express deliveries in markets the company has tested.
The human cost: “AI will change every job”
McMillon hasn’t sugarcoated the workforce implications. Speaking at a Bentonville workforce conference in September 2025, he said: “It’s very clear that AI is going to change literally every job. Maybe there’s a job in the world that AI won’t change, but I haven’t thought of it.”
But Walmart positions this as a transformation not an elimination. McMillon expects total headcount to remain flat even as revenue grows – meaning jobs will shift, not disappear. White-collar roles face the earliest disruption through chatbots handling customer service and supply chain tracking, while store and warehouse workers will eventually see tasks absorbed by autonomous systems.
The company is investing heavily in re-skilling programmes. “We’ve got to create the opportunity for everybody to make it to the other side,” McMillon said at the Bentonville conference. Automation equipment operator Chance at Walmart’s Palestine, Texas, distribution centre described the shift: “It used to be 85% physical. Now it’s 85% mental. I’m solving problems with my mind, not just my body.”
The Nasdaq gambit: Repositioning for tech valuations
Walmart’s exchange transfer was explicitly framed around its AI transformation. CFO John David Rainey stated the move reflects the company “setting a new standard for omnichannel retail by integrating automation and AI.”
The subtext? Walmart wants the valuation multiples tech companies command. At a P/E ratio of 40.3x – higher than Amazon and Microsoft – the market is partially buying the transformation story. Potential inclusion in the tech-heavy Nasdaq 100 index would drive passive fund investment regardless of AI execution.
Analysts are split on whether the premium is justified. Jefferies’ Corey Tarlowe argued the move signals Walmart is “less of a traditional retail corporation and more of a technology firm.” But sceptics note the company still derives revenue from razor-thin retail margins, not high-margin software or cloud services – despite commercialising tools like Route Optimisation.
Verdict: Genuine transformation with execution risk
Walmart’s AI strategy is neither pure hype nor guaranteed success. The company is making structural investments in proprietary infrastructure, deploying AI at genuine scale with published operational benefits, and acknowledging workforce implications most enterprises dodge.
But significant execution risks remain: managing fragmented agent ecosystems, preventing algorithmic bias at scale, competing against external shopping agents, and determining appropriate automation boundaries while maintaining accuracy.
The company’s candidness about challenges – “often, a co-pilot model, with humans and AI working as a team, is the most effective approach” – suggests leadership understands AI isn’t a silver bullet.
For enterprises watching Walmart’s playbook, the lesson is to build for specificity, not generality. Invest in proprietary data moats, plan for workforce transformation, not just cost reduction, and recognise that even with massive resources and technical talent, agentic AI remains early-stage technology with genuine limitations.
The question isn’t whether Walmart is using AI – it demonstrably is. It’s whether this surgical, infrastructure-heavy approach delivers sustainable competitive advantage, or if the company is automating itself into the same low-margin trap with shinier tools.
That answer won’t be clear for several years – but Walmart’s willingness to bet its US$905 billion in market cap on the transformation suggests leadership believes the former.
See also: Walmart and Amazon drive retail transformation with AI
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