Canadian retailers have spent years trying to make sure shoppers can find them online. Chris Parsons says the next challenge is different: making sure artificial intelligence can understand them.
Parsons, founder and author of Retail Rewired, has released a new report titled The AI Moment of Discovery, arguing that retail is entering a new stage in how consumers begin the shopping journey. The report is based on Canadian shopper research from Caddle in partnership with the Retail Council of Canada, and examines how AI tools are influencing product discovery, research and purchase decisions.
For Parsons, the shift is significant because the starting point of shopping is changing.
For years, shoppers searched by keyword. They looked for “running shoes,” “barbecue,” “plaid pants,” or a particular brand they already knew. Increasingly, Parsons said, shoppers are describing situations and asking AI tools for guidance.
“I will say I’m going to a specific event, like I’m going to be speaking on stage in Boston in August. What should I wear to this event?” Parsons said in an interview. “Now all of a sudden, it will give me a full wardrobe, and it could be a bunch of individual items from different retailers that I would definitely maybe not have considered.”
That, he said, changes the customer journey. AI can introduce products, brands and combinations that may never have appeared in a traditional search journey shaped by habit, brand preference or keyword behaviour.
“It is really a moment of discovery because you’re finding brands, you’re finding new locations, you’re taking your bias out of it,” Parsons said.
From Shelf to Search to AI
Parsons frames the change as the latest stage in a longer evolution of retail discovery.
The first major model was Procter & Gamble’s “First Moment of Truth,” which focused on the moment when consumers encountered products at the shelf. Parsons said that era was shaped by the store environment, packaging, displays and the shopper’s decision in front of the product.
He later lived through the shift to Google’s “Zero Moment of Truth,” which moved influence earlier in the journey. Consumers began researching products before visiting a store, and retailers had to focus on search engines, meta tags, backlinks, keywords and digital content.
Parsons said he recognized the current AI shift because he had already seen those earlier moments reshape retail.
“After living through those two periods, I felt like we were in this new moment, and I called it the AI Moment of Discovery,” he said.
The distinction, he added, is that AI is helping customers form a starting point. Shoppers are asking for direction, and the answer can influence which brands enter the consideration set before a traditional search ever happens.
In the report, Parsons writes that the question is no longer simply whether customers can find a retailer. The new question is whether the retailer is part of the discovery that guides the customer.
Canadian Shoppers Are Already Using AI
The Retail Rewired report cites Caddle and RCC research showing that more than one in four Canadian shoppers now use AI to help make purchase decisions. The report also says AI accounts for 13 per cent of how shoppers discover products, placing it close to channels such as retailer websites, apps and flyers.
Parsons said retailers should take the numbers seriously because adoption tends to begin with certain groups before spreading more broadly.
Men are currently over-indexing in AI usage, while Gen Z leads all generations in adoption for shopping, according to the report. Parsons said that pattern is consistent with previous technology shifts, including mobile commerce, websites and online purchasing.
“This happens with every generation,” he said. “The mobile adoption was faster with a younger generation. Search and websites and purchasing online was faster with another younger generation, and they all eventually become natives to these tools.”
The report also found that 73 per cent of shoppers using AI rate it as helpful for purchase decisions, suggesting that the behaviour is moving beyond simple experimentation.
The Shift From Keywords to Situations
One of Parsons’ central arguments is that retailers need to stop thinking only in product categories and start thinking about situations.
A traditional retail website is often built around categories: apparel, footwear, home improvement, grocery, electronics or beauty. AI-driven discovery works differently. Shoppers ask questions based on what they are trying to accomplish.
They may ask what to wear to a specific event, what to buy for a family camping trip, how to upgrade a kitchen, or which protein powder is best for their needs.
That change has major implications for retailers because AI tools need enough context to understand when a product is relevant. A product page that only lists basic specifications may not be enough.
Parsons said retailers should look carefully at their product display pages, descriptions, tips, how-to content and user-generated content. AI systems need clear signals from multiple sources to understand why a product should be recommended.
“As we consider AI, I think what we need to consider first is where are the opportunities,” Parsons said. “The opportunities are in our product display pages, the content that we provide, the usefulness, the tips on cleaning products or how to use a product.”
He said retailers also need to consider how their products appear outside their own websites, including forums, product listings, promotions, reviews, video reviews and influencer content.
“All of these create this flywheel of an ecosystem so AI can discover,” he said.
Content Becomes Critical Again
Parsons said the rise of AI should remind retailers of a lesson the industry often repeats and then forgets.
“For the 20-something years that I’ve been in retail, we always say content is king, and then we go through periods where we kind of forget about that,” he said. “Then a new technology like AI comes about and guess what’s king again? It’s content.”
The issue is not just writing more copy. It is creating useful, structured and specific information that helps people and AI systems understand a product.
For example, Parsons said retailers selling a barbecue should not only list the product as a gas Napoleon barbecue at a certain price. They should provide recipes, maintenance advice, cleaning information, cover recommendations and other content that helps explain how the product fits into a customer’s life.
“Tell the audience more so they can discover,” he said.
That same idea applies to apparel, grocery, home improvement, electronics and other categories where shoppers increasingly want guidance, not just product listings.
Parsons said retailers also need stronger foundational data. Product descriptions, sizing charts, specifications and use cases all matter more in an AI-assisted shopping journey.
“AI is only good to discover — it’s garbage in, garbage out from the retailer,” he said. “If we’re not holistically writing for these new search options, then we won’t be discovered.”
Reviews Are Becoming AI Signals
Customer reviews are also becoming more important in an AI-driven discovery environment.
The report states that 78 per cent of shoppers say customer reviews are important to their purchase decision, while 88 per cent agree that reviews improve AI recommendation accuracy. It also says 94 per cent of shoppers believe AI tools would be more useful with verified reviews.
That creates a new layer of importance for review strategy. Reviews are still read by shoppers, but they may also be summarized and interpreted by AI systems that influence which products appear in recommendations.
Parsons said this means retailers need authority from beyond their own brand voice. User-generated content, video reviews, influencers and strong ratings all contribute to how AI understands a product.
“It needs authority, and it needs authority from different users, not just the retailer,” he said.
AI Could Also Change Retail Operations
While the report focuses heavily on discovery, Parsons said retailers should also think about how AI can improve internal operations.
He said the conversation should not be limited to job loss. In many cases, AI can reduce repetitive work and allow teams to spend more time on higher-value activity.
“It’s the efficiencies versus replacement of people,” Parsons said.
One example is flyer production. Parsons said traditional retail flyer creation can involve a lengthy process over several weeks. AI could compress that timeline and free teams to build more engaging experiences, including richer digital content or video components.
“What have we always wanted to do? Where did we want to get creative?” he said. “Maybe it’s infusing flyers with more digital components, with embedding it with videos or richer content into it that you just never had the time to do because you’re just so busy doing it the old way.”
Parsons also pointed to the potential for AI to improve data analysis. Earlier in his career at Walmart, he discovered a relationship between tuna promotions and toothpaste usage through basket analysis. The insight was that shoppers buying products such as tuna could end up using oral care products more frequently.
That kind of relationship took significant time to uncover manually, he said. AI could make it easier for retailers to identify unexpected connections across categories, particularly where traditional merchandising structures keep teams separated.
“Can you imagine what AI can do looking through basket analysis and understanding these categories that, unnaturally, you wouldn’t look at together?” Parsons said.
Retailers Should Not Ignore the Shift
Parsons said some retailers may be tempted to wait, especially while AI tools continue to evolve quickly. He cautioned against that approach.
He compared the moment to the rise of Amazon, when some retailers resisted engaging with the platform because they feared it would harm their categories. Parsons said that strategy ignored where customers were spending time.
“If that’s where your audience is, you have to find a way to communicate with them,” he said.
The same logic applies to AI, he added. Retailers do not need to solve everything immediately, but they should start looking for practical ways to reduce friction for customers, improve content, strengthen product information and automate repetitive internal work.
“We can worry about all of the red herrings and the red flags, or we can start to take some opportunities that are low-hanging fruit,” Parsons said.
The report’s practical advice includes mapping products to real customer situations, aligning brands to use cases, building signals that feed AI systems, showing up early in the discovery journey and designing content for synthesis.
For Parsons, the most important point is that AI discovery is already beginning to influence how shoppers start the journey.
Retailers that understand this shift may be able to shape the customer’s first set of options. Those that do not may find themselves excluded before the shopper ever reaches a store, website or search result.
As Parsons puts it in the report, the next moment is not coming. It is already here.
