Walmart pursues enterprise agentic AI strategy
Walmart Inc. is actively developing solutions based on a next-generation artificial intelligence model for use across its operations.
The discount giant is making a cohesive effort to integrate agentic AI into its enterprise. Agentic AI builds upon the prescriptive capabilities of generative AI to streamline enterprise workflows even further.
Generative AI, which is based on machine learning, can create new content and ideas and create recommendations based on analysis of volumes of data in near-real-time that were previously too big to evaluate.
Agentic AI goes a step beyond by analyzing massive amounts of data in near-real-time and then automatically taking action based on the results.
Walmart has been a leader in developing proprietary generative AI retail tools for the past few years and is now starting to build and pilot a variety of in-house-developed agentic AI solutions.
In a corporate blog post, Hari Vasudev, CTO, Walmart U.S., reviewed some highlights from Walmart’s agentic AI initiatives.
Transforming generative AI tools to agentic AI
According to Vasudev, Walmart is working on upgrading assistive generative AI applications to fully autonomous agentic AI agents. These include its customer support assistant which utilizes generative AI to immediately recognize customers beyond understanding shopper intent to taking actions, like finding orders and managing returns.
AI agents are now routing, resolving and acting autonomously to automate mundane customer support activities and free associates to focus on more complex tasks.
[READ MORE: Walmart will personalize customer experience with generative AI]
And Walmart’s generative AI shopping assistant now uses multi-agent orchestration, fallback handling and evolving voice/camera capabilities to better support customers.
In addition, Walmart is leveraging agentic AI to further optimize the performance of Trend-to-Product, a tool that analyzes and synthesizes global data and trends, pulling information from the Internet and influencers to help its fashion team create affordable on-trend products in six to eight weeks from first identifying a trend.
In-store optimization
Vasudev said Walmart’s agentic AI in-store optimization efforts are driven by the integration of agentic capabilities into a range of associate tools, automating day-to-day store tasks.
Developer productivity
Walmart is also utilizing agentic AI to accelerate developer productivity, with agents handling tasks such as test generation, error resolution and environment setup. This frees up Walmart developers to spend more time on strategic initiatives and innovative features.
Marketing to shopping agents
As consumers develop personal shopping agents that automate digital shopping tasks, Vasudev said Walmart is developing “new pathways” for agent discovery. These advertising strategies tailored for agents (which are less likely to respond to emotionally appealing messages) and the development of agent-specific search agent optimization.
According to Vasudev, Walmart won't replace existing advertising methods but rather complement them, much like it did when it introduced social media promotions.
Looking ahead
"For retailers, the potential for agentic AI is immense," Vasudev said in the post. "Imagine complex personal shoppers that understand nuanced preferences, dynamic store environments that adapt in real-time based on customer needs, and self-optimizing logistics networks that ensure products are always in the right place at the right time. This is why we're so invested in building the right foundation today, to not only meet but anticipate the needs of tomorrow."
