{"id":15736,"date":"2026-09-01T13:55:06","date_gmt":"2026-09-01T17:55:06","guid":{"rendered":"https:\/\/www.cqcd.org\/blogue\/ia-ecommerce\/"},"modified":"2026-09-02T14:21:03","modified_gmt":"2026-09-02T18:21:03","slug":"ia-ecommerce","status":"publish","type":"blog_article","link":"https:\/\/www.cqcd.org\/en\/blog\/ia-ecommerce\/","title":{"rendered":"AI and e-commerce: What retailers need to know about Canadians\u2019 changing shopping habits"},"content":{"rendered":" \n\n\n\n\n\n\n\n\n\n\n\n\n\n
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Artificial intelligence is no longer just a topic of innovation or strategic planning. It is already beginning to influence how consumers search for, compare, and choose products online.<\/p>\n

This is one of the key findings from the fourth edition of the eCommerce Trends Report, conducted by Novatize in collaboration with L\u00e9ger. This year\u2019s study highlights an important shift: AI is gradually becoming part of Canadians\u2019 shopping habits, particularly when it addresses a concrete need.<\/p>\n

According to the 2026 results, 52% of Canadians have already used an AI tool in an online shopping context, compared to 39% in 2025. Openness toward these tools is also growing, with 63% of respondents now saying they are likely to use AI as part of their shopping journey.<\/p>\n

\u201cAI in shopping is no longer a thing of the future: more than half of Canadians have already used it in an online shopping context.\u201d \u2014 Thavy Khamtan, Novatize<\/p><\/blockquote>\n

For retailers, the message is clear. The question is no longer whether AI will impact the retail sector, but rather where it can create meaningful value for customers.<\/p>\n\n<\/div>\n <\/div>\n <\/main>\n <\/div>\n <\/div>\n<\/section>\n\n\n \n\n\n\n\n\n\n\n\n\n\n\n\n\n

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\n AI is adopted when it simplifies the purchasing decision.\n <\/h2>\n\n \n\n\n\n\n\n\n\n\n\n\n\n\n
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Consumers are not using AI simply because it is trending. They are using it when it helps them make better purchasing decisions.<\/p>\n

The study identifies product or brand comparison as the leading use case, with 44% of Canadians saying they are likely to use AI to compare products, understand the differences between similar options, or evaluate one brand against another.<\/strong><\/p>\n

This finding is particularly important for retailers. It shows that AI is perceived as a decision-making tool, not just a conversational one. Customers are looking to save time, reduce uncertainty, and better understand what sets one option apart from another.<\/p>\n

In a context where online catalogs can contain hundreds or even thousands of products, this expectation becomes increasingly important. The broader the offering, the more customers need support to navigate, filter, compare, and choose.<\/p>\n\n<\/div>\n <\/div>\n <\/main>\n <\/div>\n <\/div>\n<\/section>\n\n\n \n\n\n\n\n\n\n\n\n\n\n\n\n\n

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\n Complex product categories are the most conducive to AI adoption.\n <\/h2>\n\n \n\n\n\n\n\n\n\n\n\n\n\n\n
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Not all product categories are affected in the same way. The results show that interest in AI is stronger in categories where the purchasing decision is more complex, technical, or high-stakes.<\/p>\n

Electronics<\/strong> leads the way, with 28% of Canadians saying they are likely to use an AI tool for this category. Appliances<\/strong> follow at 25%, while home and d\u00e9cor<\/strong> and health and wellness<\/strong> are tied at 22%.<\/p>\n

These results are not surprising, given that these are categories where consumers often need to compare multiple features, understand technical differences, assess compatibility with their needs, or make a more expensive purchase.<\/p>\n

For retailers, this means AI should not be deployed uniformly across every category. Instead, priority should be given to areas where it can genuinely help customers make a more informed decision.<\/p>\n

For example, an appliance retailer could use AI to help customers compare models based on available space, energy consumption, features, budget, and delivery times. A home improvement retailer could use it to guide product selection based on the type of project, the customer\u2019s level of expertise, or compatibility with other materials.<\/p>\n

In these cases, AI becomes a tool for clarification. It reduces friction at the point when customers need the most help.<\/p>\n\n<\/div>\n <\/div>\n <\/main>\n <\/div>\n <\/div>\n<\/section>\n\n\n \n\n\n\n\n\n\n\n\n\n\n\n\n\n

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\n What retailers can do in practice\n <\/h2>\n\n \n\n\n\n\n\n\n\n\n\n\n\n\n
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The growing adoption of AI does not mean that every retailer needs to quickly add an intelligent assistant to their website. A poorly targeted integration can even add complexity rather than simplify the customer experience.<\/p>\n

Instead, the first step is to identify the moments in the customer journey where customers need the most support.<\/p>\n

1. Prioritize complex decisions<\/strong><\/p>\n

Retailers should start with the categories where customers hesitate the most, compare options more extensively, or contact customer service more often before making a purchase.<\/p>\n

A few useful questions to ask:<\/p>\n