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Home » How to transform your product data for the age of AI shopping
Consumer Goods & Services

How to transform your product data for the age of AI shopping

ThefuturedatainsightsBy ThefuturedatainsightsNovember 4, 2025No Comments2 Mins Read
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AI tools such as ChatGPT and Google Gemini are integrated into everyday life and are now agent model They are driving the next wave of retail disruption by digging deep into consumer motivations, shopping patterns, and even consumer purchasing decisions.

According to , this shift to agent commerce could represent a $900 billion to $1 trillion opportunity for U.S. retail alone by 2030. McKinsey & Company.

Soon, these agents may transform from simple conversational chatbots for everything from grocery shopping to travel planning to active buyers who go beyond traditional searches and site browsing.

Also: Walmart Introduces “Agent Commerce” Through OpenAI Partnership

This shift presents both challenges and opportunities for consumer goods companies and retailers, requiring them to focus not only on consumers but also on the algorithms that parse digital product information to influence what products people view and ultimately purchase.

The rise of AI-driven shopping

We’re moving from simply searching online to a more relationship-driven experience. When you work with an agent, you can better support your consumers by looking at their purchase history, brand metadata, and reviews to provide tailored and relevant recommendations.

“Unlike in the search engine era, answer engines like ChatGPT have ‘memory’. Once you tell them your size information (or any other product preferences, allergies, or anything else), they know it without you having to say it all the time,” said Scott Wingo, CEO of ReFiBuy. In his view, this creates a kind of hyper-personalized loop that allows brands, algorithms and consumers to evolve together.



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