Walmart gets a head start with GenAI and AI agents
Jul 30, 2025
Walmart isn’t just dabbling in AI. It’s pushing forward with conviction, using GenAI and AI agents to streamline operations, personalize customer experiences, and stay ahead of competitors. This commitment to operationalizing AI has solidified Walmart’s status as a first mover in retail.
Walmart is deploying GenAI and AI agents across 50 use cases already in production, ranging from associate coaching to real-time customer service and personalized promotions. The retailer’s in-house large language models (LLMs) and AI agents now support business teams in ways that go well beyond content generation.
Walmart is optimizing workflows, reducing manual burden, and making faster, more intelligent decisions at scale.
We’re past the experimentation phase with GenAI and AI agents
This is where the market is heading. McKinsey’s latest Global Survey on AI reports that 71% of surveyed organizations say they regularly use GenAI in at least one business function, up from 65% earlier in 2024.
Adoption is especially high among large enterprises, where AI is increasingly viewed as a differentiator, not a pilot program. GenAI is becoming operationalized, and AI agents are playing a role.
Walmart’s transformation shows how quickly this change is accelerating. Rather than purchasing off-the-shelf AI tools and layering them onto legacy systems, Walmart has developed its own foundation models and tailored agents that can be trained on proprietary data.
For instance, Walmart is rolling out four unified agents to simplify access to AI across its ecosystem: one each for customers, employees, engineers, and suppliers.
The customer-facing agent, called Sparky, is already live and expanding its capabilities, while the supplier-facing agent, Marty, will soon launch with functions like analyzing purchase analytics and initiating advertising campaigns.
Together, the agents consolidate dozens of previous tools into intuitive, centralized interfaces, improving usability and adoption across the business.
Walmart has reported efficiency gains, improved customer outcomes, and higher productivity among associates using AI-driven assistants.
Associates can now ask a virtual coach for help, get real-time guidance, and receive support on routine tasks. Meanwhile, customers benefit from more personalized search results, tailored promotions, and intelligent product recommendations, all powered by GenAI.
Opportunities are growing, but so are the risks
But AI adoption at scale introduces new risks. Global companies are also deploying GenAI and AI agents across their organizations, but many are encountering challenges related to data fragmentation, quality assurance, and alignment with real-world business logic.
Companies eager to tap into the speed and automation that agents provide are learning that outcomes depend entirely on the quality of the underlying data and the orchestration of those agents in real-world workflows.
Trustworthy data is foundational to managing risks. AI agents can only perform well if they’re trained on clean, contextualized, and accurate data. This is especially true in environments like retail, where real-time decisions depend on constantly shifting inventory, customer preferences, and supply chain dynamics.
Walmart’s success in building proprietary agents likely stems from its ability to harness high-quality internal data streams and align them with well-defined business tasks.
For organizations following Walmart’s lead, it’s important to move beyond sandbox environments. That means unifying data sources, standardizing formats, incorporating expert-labeled data, and continuously monitoring agent behavior in production.
The transition from experimentation to enterprise-scale deployment is both technical and operational. It requires new partnerships, new workflows, and new guardrails for safety, governance, and ROI.
An AI data foundry can help you scale GenAI and AI agents with confidence
An AI data foundry can help ensure that GenAI and AI agents deliver quality results. Centific works with AI teams to manage quality at scale by combining human domain expertise, automation, and customizable workflows tailored to each business objective.
From data annotation to streaming data pipelines and responsible agent orchestration, Centific helps businesses bring GenAI and agentic AI into production safely, efficiently, and with measurable impact.
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