Canadian retailers are steadily moving from curiosity about artificial intelligence to real implementation, although in a measured way that reflects broader economic conditions and long standing growth patterns. Rather than pursuing bold bets that could lead to sharp booms and busts, most banners are piloting focused AI tools behind the scenes and looking for clear productivity gains before exposing more AI directly to shoppers.
“The difference between Canada and the United States has always been that Canadian retailers are more cautious,” said Natalija Pavic, Senior Director of Product Marketing for KIBO Commerce, in a recent interview with Retail Insider. “You can see it when you compare a business like Sleep Country Canada to Mattress Firm. Sleep Country has tended to expand slowly and steadily, while Mattress Firm went through a pronounced boom and bust cycle.”
That same temperament, she argued, now shapes AI adoption in Canadian retail, influencing choices across merchandising, supply chain and customer experience.
Pilots take hold as Canadian retailers test AI in the field
The current phase is characterized less by headline grabbing AI front ends and more by quiet pilots inside larger enterprises. Pavic described a cohort of Canadian retail leaders that skew toward the enterprise side rather than mid market and are now testing AI in targeted use cases instead of trying to transform the entire business at once.
“We have several Canadian retailers in pilot right now,” she said. “We are seeing particular momentum in home goods, liquor and wine, and pharmacy. In those categories, AI is being used to support product recommendations, category guidance and more complex customer questions.”
In one example, she pointed to a large format retailer that combines pharmacy, seasonal, outdoor and electronics assortments and is experimenting with AI agents that can guide shoppers across very different departments. “They need AI agents that can handle complex product questions, help with item selection and provide high quality recommendations at scale,” she noted.
At the same time, she said that fully fledged AI personal shoppers are still rare in this market. “I have not yet seen strong adoption of the vision of a true personal shopper assistant in Canada,” she said. “It is discussed often, but I have not personally interacted with an implementation that feels mature and truly impressive in this market.”
The unseen work: merchandising, content and supply chain
If consumer facing experimentation is still limited, the back office is moving faster. Pavic expects the most immediate impact of AI adoption in Canadian retail to appear in what she calls the “unseen work” of merchandising, content creation and planning, where teams have been under pressure for years.
“The biggest gains in the near term are in productivity for merchandisers, marketers and planners,” she said. “There is a perception that AI will eliminate roles, but the reality inside most organizations is that teams are already stretched. I have never led a marketing team where I felt we had more capacity than we needed.”
In that context, she sees AI as a way to extend the function rather than shrink it. “AI can help marketers and merchandisers do things they simply did not have time to do before,” she explained. That can mean auto generating promotions and campaign variants, drafting product descriptions and category copy, or helping teams test more scenarios when they build assortments and planograms.
Operationally, Pavic pointed to order management, inventory visibility and delivery promise dates as key frontiers for practical deployment. “We are very focused on helping retailers optimize how they provide and deliver product,” she said. “That ranges from setting the right safety stock in the right distribution center to routing orders so that delivery commitments can be met, especially in critical periods like the holiday season.”
AI infused logic is now underpinning promise date estimation and fulfillment decisions, she added. In a market where identical branded products are available from multiple channels, she believes the network itself becomes a primary differentiator. “It is less a question of whether a shopper can find a product and more a question of who has the most reliable and efficient delivery network,” she said.
Budget pressure, vendor fatigue and the AI business case
Economic realities are also pushing executives to look at AI with fresh urgency. Pavic said it is common for conversations with Canadian retailers to begin with a clear statement that there is no budget available for major projects, only to evolve after a deeper discussion of total cost of ownership and technical debt.
“I often start meetings with retailers who say there is no budget for the year,” she said. “After we walk through where costs are sitting today and what AI can actually change, we sometimes end the conversation with the realization that doing nothing is more expensive than moving ahead with a focused AI initiative.”
She said rising license costs from large legacy software providers, combined with the complexity of older platforms, are pushing retailers to look for point solutions that can sit beside existing systems. In her view, this is one reason modular tools that enable AI adoption in Canadian retail are gaining traction.
“Many organizations invested in large scale digital transformation projects that took a year or more to complete and carried significant risk,” she said. “Some of those efforts have delivered value, but others have left leadership feeling cautious about signing up for another big bang project.”
KIBO’s response has been to emphasize modular offerings that can coexist with current platforms. “We have worked hard to make our products truly modular so that retailers can adopt specific capabilities without replacing everything they already have,” she said. “It gives chief information officers a way to fill gaps, start seeing benefit quickly and then migrate other pieces gradually as it makes sense.”
Rethinking data: from perfect unification to workable reality
Unifying data across channels, banners and back end systems has long been presented as a prerequisite for modern commerce. Pavic takes a more pragmatic approach, especially in light of advances in AI that can work with messy inputs.
“There is a narrative that unified data is the single most important foundation, and that often comes from vendors selling database technology and extensive professional services,” she said. “In practice, there are now AI tools that can operate on unstructured data and extract value without requiring you to fully normalize every field first.”
Rather than spending six months harmonizing data models, she encourages retailers to look at platforms that can automatically map sources and create workable linkages. “We partner closely with Google, and our agentic commerce capabilities are built on Google’s technology,” she said. “Their data lake style solutions can map disparate data sets automatically, which means you do not necessarily need a new team of data scientists just to get started.”
She believes that mindset shift is essential if retailers want to see benefits sooner. “There is a tendency to delay programs because the foundational work feels overwhelming,” she said. “The better question is often whether there are tools that can handle the reality of the data as it exists today so that you can begin to move the needle.”
From SEO to answer engines and agentic commerce
Pavic also spends her time thinking about how AI changes product discovery. Traditional search engine optimization remains relevant, particularly in Canada, where everyday consumer use of tools like ChatGPT and Gemini is still catching up to the United States. At the same time, she said the industry is already grappling with a future where answers, rather than blue links, become the default result.
“People are starting to talk about answer engine optimization as a complement to SEO,” she said. “Large language models can synthesize content from many sources to respond to a shopper’s question without always showing where each idea came from.”
That complicates some of the old playbook. Long form educational content still matters, but the benefit can be more diffuse when a model blends insights from many brands into a single answer. For Pavic, that puts renewed emphasis on fundamentals. “We are going back to core brand building,” she said. “It is about being recognized as a trusted source of information and having strong third party signals like reviews and independent rankings that models can see and interpret.”
She also urged retailers to think carefully about what happens when shoppers use AI tools as the primary interface for shopping. In her view, agentic commerce, where software agents interact on behalf of both shopper and retailer, will grow in importance.
“There are new protocols that allow retailers to expose inventory and checkout capabilities into AI environments,” she said. “If your products are recommended within a chat interface, you want to be the brand that can present a clear path to purchase rather than leaving that traffic to generic aggregators.”
Physical experiences as a Canadian advantage
Despite her focus on software, Pavic is clear that physical experience remains one of the most important differentiators for domestic retailers. With Canadian consumers spending a significant portion of the year indoors, she sees a real opportunity for more creative third spaces that combine retail, food, community and entertainment.
“For at least half the year, Canadians are looking for indoor spaces where they can spend time,” she said. “We do not have as many third spaces as we could, and that is an area where retailers can innovate in ways that are very difficult for purely digital competitors to replicate.”
She pointed to large format American concepts that integrate activities, dining and immersive environments under one roof as examples of what is possible. Closer to home, she highlighted small neighbourhood businesses that blend cafés with children’s play spaces as an illustration of how modest footprints can still create meaningful experiences.
“These concepts are simple in one sense, but they address a real need,” she said. “Parents need somewhere warm, comfortable and engaging to spend time with their children. Retailers and landlords who design around those needs can build resilience that is not subject to the same supply chain and price volatility as product alone.”
That matters even more as Chinese platforms and fast fashion brands deepen their reach into Canada. “China was once primarily the source of manufacturing,” she said. “Today, Chinese retailers are building direct relationships with Canadian consumers. If local banners do not differentiate through experience, service and brand, there is a risk that more heritage names will disappear.”
Marketplaces, dropship and nurturing smaller brands
Pavic believes one of the most promising responses is for Canadian retailers to position themselves as curated platforms for smaller and boutique brands, both online and in store. With tariffs, policy changes and global disruptions affecting supply, third party supply, dropship and marketplaces are becoming central themes in AI adoption in Canadian retail.
“At KIBO we are investing heavily in dropship and marketplace capabilities because we see them as critical to the future assortment strategy,” she said. “The current landscape often forces retailers to choose between very expensive enterprise marketplace platforms and extremely limited entry level tools. There is not enough in the middle.”
She sees an opportunity for Canadian banners to onboard local makers and small businesses that might currently sell primarily through marketplaces or craft platforms. “Retailers can create environments where those brands can be discovered and can benefit from the traffic and trust that established banners already have,” she said. “That can happen in physical spaces as well as through curated online marketplaces.”
The key, in her view, is to offer technology that makes onboarding and operations straightforward without demanding enterprise level budgets or multi year projects.
Smarter search as a practical AI entry point
Search is another area where Pavic sees clear and accessible use cases for AI that do not require a full scale transformation. “On many retail sites, search still does not work the way shoppers expect it to,” she said. “That is often because it is based purely on keyword matching or, at the other extreme, on heavy personalization without enough context.”
She advocates for approaches that combine vector search and semantic understanding to deliver more relevant results. “Instead of only looking for exact keyword matches, vector search represents products and queries in a multi dimensional space,” she explained. “That allows the engine to understand that a shopper searching for a red dress should see dresses first, with related but less relevant items appearing further down the results instead of being mixed together.”
Layered with natural language understanding, she said, this type of search can significantly improve the customer experience while remaining relatively modular and cost effective to implement. “It is often possible to gain a meaningful uplift in search performance without replacing the entire site or waiting for a broader digital overhaul,” she said.
For retailers still watching from the sidelines, Pavic’s core message is pragmatic rather than promotional. Begin where the pain is greatest, look for modular tools that integrate with current systems, and recognize that AI adoption in Canadian retail does not need to arrive as a single sweeping program.
