In retail and dining, the customer experience almost always breaks at the same point: right when it shifts from “searching” to “solving.” A user discovers a product on the website, asks a question in the chat, switches to the app to check stock, ends up calling to correct a shipment… and repeats the same story three times. At NRF 2026, Google Cloud aimed to address this friction point with a solution that goes beyond the traditional chatbot: Gemini Enterprise for Customer Experience (CX), an “agentic” solution designed so that buying and after-sales support share context, data, and actions within a single intelligent interface.
The announcement positions Google Cloud at the center of a trend the industry is calling agentic commerce: assistants that don’t just respond, but perform multi-step tasks with user consent, connecting front-end (chat, voice, digital channels) with internal business tools. According to Google, the goal is to move from “decorative” conversations to actual problem resolution, from product discovery to refunds after an issue.
From static chatbots to a “digital concierge” that acts
Google Cloud presents Gemini Enterprise for CX as a layer capable of maintaining continuity throughout the customer lifecycle: what the user requested, purchased, shipped, failed, and needs correction. The idea is simple yet ambitious: that the assistant remembers the thread and can operate across systems to avoid “re-telling your case.”
This leap, according to the company, relies on new preconfigured and customizable agents built on the latest Gemini models, designed for quick deployment. The focus isn’t just on “responding better,” but on closing the loop: understanding intent, consulting catalog or logistics data, checking availability, and if appropriate, initiating actions like adding to cart or processing a return.
A shopping agent that reasons, sees, and executes
The most visible component is a Shopping agent that Google defines as capable of handling complex requests through advanced reasoning, combining filters, constraints, and preferences. The typical example is no longer “looking for a sofa,” but “searching for an emerald green velvet sofa that withstands pet hair and isn’t oversized,” with the agent cross-referencing dimensions, material attributes, and budget.
The other focus is multimodality: the agent can interpret image, video, or voice inputs. Google illustrates cases like a handwritten recipe photographed by the user so the assistant can identify ingredients and add them to the cart. The key differentiator here isn’t just “understanding,” but acting: the agent can execute consented actions, such as preparing a shopping basket, applying loyalty benefits, or completing a purchase with real-time data.
Names associated with these capabilities include Kroger, Lowe’s, and Woolworths, which have shared how they are exploring more personalized assistants for shopping and projects, promising to simplify complex decisions and reduce friction along the customer journey.
Customer Experience Agent Studio: support agents “in days” with quality control
The offering isn’t limited to shopping. Google Cloud also introduced Customer Experience Agent Studio, an environment for building, testing, and deploying multimodal support agents at scale, integrated with the Shopping agent so that each customer interaction begins with history and context instead of starting from scratch.
According to the product description, the studio incorporates an approach of “Artificial Intelligence that builds Artificial Intelligence”: transforming transcripts, internal documentation, and existing flows into operational agents with less manual engineering, supported by a visual “drag-and-drop” canvas for orchestrating tasks. The clear goal is to reduce onboarding time and enable rapid iteration in environments where each campaign or season shifts priorities.
Simultaneously, Google emphasizes a component that many agent platforms still treat as secondary: assurance and quality. Highlights include natural language analysis to detect trends (e.g., why average handling time increases for certain queries), as well as self-evaluation of conversations with “scorecards” tailored to context. Support for assisted human agents and simulations to accelerate training and onboarding are also part of the offering.
Restoration: From order to operation
Restoration appears as the second major scenario. Google integrates an improved Food Ordering agent within Gemini Enterprise for CX for conversational orders across multiple channels (web, app, phone, kiosks, or vehicle systems). The commercial appeal here is twofold: increasing conversion (with contextual upselling) and reducing friction by finding the best offer for the customer.
Papa John’s is the first client to deploy these omnichannel capabilities, with the agent also functioning as an “analyst” providing operational insights and enabling large-scale menu and price updates without heavy manual processes.
Privacy and compliance: the essential condition
In a context where agents can execute actions, trust is part of the product. Google emphasizes that the system incorporates mechanisms to comply with brand policies and legal requirements, and that customer data isn’t used to train models. In retail, where the line between personalization and excess is thin, the emphasis on consent and governance isn’t a detail: it’s the “permission to operate.”
Frequently Asked Questions
How does Gemini Enterprise for Customer Experience differ from a traditional customer support chatbot?
The key is that it doesn’t just chat: it maintains context across channels and can execute multi-step actions (with consent), connecting purchasing and support workflows.
What types of companies can deploy these agents, and what use cases are they best suited for?
Retailers and restaurants seeking to unify discovery, cart, orders, issues, returns, and omnichannel support with less friction.
How is user consent managed when the agent adds products to the cart or processes a refund?
The approach is based on “consented” actions: the agent proposes and requires authorization before acting, operating under policies and compliance requirements.
What does Customer Experience Agent Studio bring to a high-volume support team?
It enables faster creation and evaluation of multimodal agents, with analysis and quality control tools (trends, conversation scoring) and support for human agents’ training and onboarding.
via: google cloud