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EXCLUSIVE Q&A: PwC explains the rise of shopping agents

Eric Shea
Eric Shea, principal, commercial & service excellence, PwC U.S.

Shopping agents are rapidly growing in usage among consumers, and retailers need to adapt.

Chain Store Age recently spoke with Eric Shea, principal, commercial & service excellence, PwC U.S., about how agentic AI is transforming the way consumers discover and shop for products, as well as how retailers should recalibrate their operations before shopping agents become even more prevalent. 

How are consumers using shopping agents?

Shopping agents are moving from novelty to everyday behavior, especially among younger consumers. The PwC ‘Future of Consumer’ survey found 54% of millennials expect to use AI to find and compare products, and 46% expect to use AI to complete purchases. Gen Z is close behind, and Gen Alpha is growing up AI native.

Agent usage also depends on the task.  Nearly half of consumers say they would use AI to track an order or delivery, but only 29% are comfortable using it to make a payment, according to the PwC ‘Customer Experience’ survey. That gap emphasizes the need for trust: consumers embrace AI when it saves time, but trust still governs transactions.

Why is product discovery shifting to agents?

Product discovery is being restructured. It’s faster, more personalized, and increasingly happening before a shopper even reaches a brand’s website. A shopper can ask an AI agent, ‘Where can I find the best vintage white T-shirt under $30’ and options are instantly surfaced, influenced by curated social content, reviews, and research. Agents reduce complexity in a world defined by choice overload and decision fatigue.

[READ MORE: Agentic AI may drive up to half of all online transactions by 2027]

Why should retailers not wait to offer shopping agents?

The shift is already in motion. Every era is defined by a platform change, from physical stores, to ecommerce, to mobile, and now AI agents. We saw this play out in the most recent holiday season. According to PwC analysis of Numerator, more than half of consumers shopped online this holiday, with online spending up nearly 7% year over year. 

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And most notably, generative AI referral traffic to major retailers grew 750% year over year according to Adobe, signaling a meaningful shift in how shoppers discover products.

Brands shouldn’t wait to pilot agentic capabilities; they should start now. These systems improve through real decisions and feedback loops. Early pilots allow brands to capture value while maintaining control. The same lesson applied to ecommerce: the winners weren’t the fastest movers on every platform, but the ones that built foundational capabilities early. The goal is to prepare for a world where the fastest-growing ‘customer’ may not be a person at all, but an agent.

What should retailers look for in a shopping agent solution?

Brands should build integrated commerce engines, not standalone chat tools. Effective agents connect product data, inventory, order management, payments, and marketing systems to deliver accurate recommendations and real-time fulfillment visibility.

Since trust is the foundation, brands must lead with accountability to protect consumer confidence. The strongest solutions embed governance, transparency, and clear consent into the experience from the start.

What will be biggest trends in shopping agents over the next six to 12 months?

Three forces will shape agentic commerce in the near term. The first is generational acceleration. Millennials are steadily adopting AI-enabled tools. Gen Z is even more comfortable with AI-driven discovery and influencer-led recommendations. As these habits normalize, agent-led shopping will accelerate from early adopters to mainstream.

Second is the trust race. 64% of consumers want guardrails when using AI to transact. The brands that make oversight simple and intuitive will lead.

Third is category convergence. Agents will increasingly connect signals across food, beauty, wellness, and household categories, accelerating the shift from category-based missions to outcome-driven ecosystems. As brands make product data machine-readable, agents can position products within broader life moments, not just isolated categories.

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