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COOKIE POLICY
With over 40% of shoppers saying AI is now their primary source of insight, today’s agentic commerce tools create unprecedented visibility into consumer purchase intent and decision-making patterns. Today’s AI agents excel at surfacing clear product data and creating frictionless shopping experiences. Smart retailers already recognize agentic commerce as a differentiation opportunity, and some major retailers are even taking defensive positions in response to this market change.
What’s at stake? Share of wallet from online shoppers who increasingly turn to AI for making purchases.
Progressive retailers are exploring AI partnerships and data-sharing agreements that let them offer streamlined, automated workflows while maintaining personalization capabilities and collecting shopper data. Tools can include agent-friendly authentication, structured feeds, and analytics frameworks.
At UDig, we see four strong options for deploying agentic commerce right now, depending on your business goals, planned resources, and appetite for risk.
AI-assisted shopping creates a hyper-personalized experience on a retailer’s website. AI essentially acts as an agent in the context of that merchant’s online space, helping guide the shopper experience based on their inputs. For example, Walmart offers Sparky in their shopping app to help users find relevant products, parse reviews, and more.
Using MCP protocol, the merchant creates a chat-based experience on their shopping app or website. Drawing on cookie-based user history or loyalty data, the AI assistant accesses the entire product catalog to create a curated shopping experience. All interaction data is stored and processed by the merchant to continually improve the user experience.
This approach is the fastest and easiest to implement, and UDig is already working with several clients on AI-assisted shopping initiatives. It’s a meaningful first step to take in exploring agnostic commerce.
AI browsers are already sharing products with shoppers, with or without the retailer’s participation. For example, a user can download the Comet browser from Perplexity or Atlas from OpenAI, then use that platform instead of Google or Microsoft Edge to search for products.
In the AI browser search bar, the user would write a prompt like, “Recommend a birthday gift for under $75 for my sister who likes to bake.” AI returns an itemized list customized for that user’s browsing history, then the shopper clicks through for checkout at the merchant website.
Although AI browser transactions require little to no work on the part of the retailer, this model has significant barriers to success. First, AI may return errors – for example, listing the price of an appliance accessory as the item price, which can mislead shoppers. The shopping experience is not a one-click checkout, which adds potential exit points and increases the chance of abandoned carts. And unless the shopper logs in or has a recognized cookie, the transaction and customer data aren’t saved.
The biggest challenge for retailers here will be to win placement in the AI results, which can be a mysterious moving target, much like SEO placement. UDig can help by establishing an ACP-based connection with AI browsers so that retailers can capture transaction data to integrate with their customer history and loyalty programs.
For a more robust AI integration, one option is turning to a software development kit (SDK) to create retailer-controlled experiences within frontier AI platforms. Retailers developing custom AI platforms can offer customers ease of use, but within the retailer’s full brand experience.
For example, a retailer can deploy custom UI components in ChatGPT, or rich product cards in Claude conversations, or branded checkouts within AI chat.
Shoppers would query the AI platform just as in AI-enabled browsing. But here, when shoppers engage with the retailer, the connection is made via invisible back-end coding while the shopper remains in AI. This transition is invisible to the shopper because AI is still handling the transaction (with user authorization in their AI settings).
Sites like Booking.com, Expedia, and Zillow have all created SDK protocol apps.
UDig works with clients to manage SDK development, integrate platforms, design the brand experience, and manage shopper data, ensuring that the retailer maintains control while deploying AI commerce.
Agentic commerce platforms (ACP) enable the capability for multi-retailer workflows and automation for one-click purchases. This comprehensive orchestration fully optimizes operational efficiency while reducing friction.
Here, data sharing must be coordinated between the retailers, AI platforms, and shoppers. The right coordination creates the ultimate curated shopping experience for the smoothest purchases. Errors and drop-offs are much less likely because purchasing is a one-click decision.
ACP platforms can include autonomous procurement, cross-retailer inventory optimization, and workflow automation. Each merchant controls and holds the shopper’s transaction history and loyalty data.
Working with retailers to develop a platform strategy, workflow design, and enterprise integration, UDig’s ACP platform strategy offers retailers both control and operational efficiency.
At UDig, we work with leading retail clients that are exploring today’s possibilities with AI-assisted commerce. One of them is already running an internal pilot with an AI-supported experience, offering a shopping agent to help users find what they need on the retailer’s website. Our goal is to remove friction from their processes so every interaction feels faster, simpler, and more human.
UDig is developing more AI-engagement strategies that balance accessibility with strategic control. We help clients optimize digital infrastructure for AI interaction and implement analytics that capture valuable insights from agent-mediated shopping.
Ultimately, we believe that building these new shopping experiences is about more than AI. It’s about designing technology around how people actually behave, making it easier for them to connect, create, and deliver impact.
With over 15 years at the forefront of technology innovation, I've dedicated my career to delivering strategic solutions that drive business growth. As the Chief Technology Officer of UDig, I lead our technology vision, architecting solutions that transform how organizations leverage technology to generate impact.
