BREAKING: Google pushes retail into the agentic era with new AI shopping agents, and Walmart is the first big test. I have confirmed Google is switching on a suite of retail AI tools that let shoppers talk, plan, and buy in one flow. The move turns search, discovery, and checkout into one continuous conversation. It is a major step, and it lands today.
What Google is actually shipping
Google’s new retail agents are built to handle full shopping tasks. Not just search. A shopper can describe a goal, get options, weigh trade-offs, and buy, all in one thread. The agent keeps context across steps. It remembers size, budget, and brand limits during the session. It can also ask smart follow ups when details are missing.
Under the hood, the system runs on Gemini with retail add-ons. Retailers connect their product catalog, inventory, promos, and content through clean APIs. The agent uses that data to ground every answer in real items that are in stock. It can call tools to compare features, build a basket, apply coupons, and hand off to checkout. Retailers control the tone, the rules, and when the agent should route to a human.
Google is offering this as a set of managed services. That includes a conversation engine, a product reasoning layer, and prebuilt flows for search, bundling, and post sale help. Data controls are front and center. Retailers choose what is shared, what is logged, and what is never used for model training. The full stack plugs into apps, sites, and voice surfaces.
Walmart signs on, with Gemini in the aisle
Walmart is rolling out Gemini powered help for shopping and buying. In practice, that means natural language requests inside Walmart’s digital storefronts. Ask for a week of school lunches under a set budget. Ask for a TV for a bright room. Ask for a cordless drill that fits a brand you already own. The agent responds with clear picks, reasons, and live prices. When you accept, it builds the cart and guides checkout.
Early pilots focus on smoother search and faster decisions. Expect basket building that respects dietary needs, size and fit guidance, and quick swaps when items go out of stock. The experience is designed to cut the back and forth that slows shoppers down. Walmart is pushing for speed, clarity, and fewer taps.
Why this matters for the industry
Retail is picking an AI platform, not just a search box. Google wants to be the engine that powers the whole buying journey. That puts it up against a growing field of commerce AI providers. The real contest is about who can turn intent into orders with the least friction and the best trust.
This shift affects margins and growth. Better guidance can lift conversion and average order value. Smarter substitutions can save a sale when inventory is tight. Post sale answers can reduce support costs. But vendor choice now carries weight. Data governance, brand voice, latency, and cost per session all matter more than before.
If you pilot these agents, start with one high impact flow. Measure time to decision, cart adds, and drop off. Then expand.
What changes for shoppers
Shopping becomes a chat, not a maze of filters. You state the goal. The agent does the legwork, then checks with you before it buys. It can compare items, explain trade offs, and remember your choices for the current session. The hand off to checkout is tight. The agent explains what is in the cart and why.
This should help with complex buys. Think a home office bundle for a small space. Think party supplies for 10 guests with allergies. The agent can build a complete list, with options and prices, then let you edit. It can also set alerts for restocks or price drops if the retailer enables it. Voice support and multiple languages are on the roadmap for many partners.
Light technical view, without the buzzwords
Retail agents need speed. Google is aiming for sub second responses on simple queries, and snappy follow ups on harder ones. To get there, the system mixes fast lookups with deeper reasoning only when needed. Retailers can cache popular results and pin trusted answers for common questions.
Grounding is key. The agent pulls from the live catalog, store inventory, and policy data. That reduces wrong answers and bad recommendations. Promotions and eligibility rules are also part of the context. If the item is not available, the agent should propose a true match, not a guess.
AI can still get things wrong. Retailers must set guardrails, clear disclaimers, and easy handoffs to humans for sensitive cases.
Here are the four questions every retailer should ask before picking a partner:
- How is my product and customer data stored, and can I opt out of model training
- How fresh are inventory and price signals inside the agent
- What guardrails prevent unsafe or off brand responses, and how do handoffs work
- How do we measure lift with holdouts and A B tests that I control
The bottom line
Google just raised the bar for retail AI. A big box partner gives the launch real weight. The bet is clear, the next wave of shopping is agent led, task driven, and deeply tied to real inventory. For shoppers, the win is less friction and better choices. For retailers, it is time to pick a lane, set the rules, and build trust into every step. The race to own the shopping agent has started.
