An AI-generated image of a man shopping in an electronics store.
Image created via Microsoft Copilot, powered by DALL E.

Canadian Retailers Are Using GenAI to Enhance the Customer Experience, Says KPMG

Canadian retailers are embracing generative artificial intelligence (AI) technology, with many integrating it into their organizations or planning to integrate in the near term to boost productivity, predict demand, and offer personalized experiences to customers, a new study from KPMG in Canada shows.

In a recent survey of executives from 135 Canadian retailers across numerous sectors, more than eight in 10 respondents (81%) said they must invest in generative AI to stay competitive, and the same number agreed they need to shift to a generative AI operating model in the next 12 months to stay competitive.

Nearly four in 10 (38%) said they already have a generative AI solution of some sort in place at their organizations, and another four in 10 (39%) are planning to implement their first generative AI solution within the next six months.

The most common uses for generative AI among retail respondents include detecting fraud by raising red flags for suspicious transactions (69%); predicting product demand and optimizing inventory levels (68%); offering personalized product recommendations in customer-tailored conversation styles (67%); powering product search engines by making it easier to understand customer search inquiries (67%); and inbound and outbound scheduling/truckload optimization (67%).

“It is clear Canadian retailers see generative AI as critical to their futures,” says Kostya Polyakov, Partner and National Industry Leader of KPMG in Canada’s Consumer and Retail practice. “The challenge is identifying use cases that add value to organizations since there are a myriad of ways retailers can use the technology to become more efficient, productive and profitable.

“Generative AI is a natural fit for retail: it can personalize the customer experience, allow more precise forecasting and improve the supply chain,” adds Polyakov. “More than 80 per cent of Canadian retailers we surveyed will be utilizing the tech this year. For the 20 per cent not there yet, they face a huge competitive disadvantage that will only grow as those using it find more and more ways to leverage its powers. Generative AI is not something for the future – it is now table stakes for Canadian retailers.”

While uses of large language models will continue to grow, it will be important for Canadian retailers to adopt a responsible use of generative AI framework inside their businesses to ensure this technology is used responsibly, adds KPMG.

The survey also found that 90% agree generative AI is helping to or will help grow their company’s revenue and/or market share growth. More than a third (39%) expect generative AI to boost revenue by six to 10%; while 26% see a 10 to 15 per cent per cent revenue boost; and 23% predict a three-to-five per cent gain. Forty-two per cent expect generative AI to improve sales return on investment (ROI) of between 10 to 20%; 41% expect a boost of between six to 10%.

Nearly nine in 10 (86%) respondents said generative AI can help to better inform their marketing campaigns and personalize shopping experiences for customers, and 88% agreed the technology can create stunning visuals for product launches and reduce photography costs. However, nearly eight in 10 (78%) expressed concern about how consumers would respond to AI-generated imagery, something Polyakov says retailers need to be mindful of in addition to the continually developing rules around intellectual property in light of generative AI.

An AI-generated image of a man shopping in an electronics store.
Image created via Microsoft Copilot, powered by DALL E.

“Consumers are increasingly using generative AI tools themselves, and many are savvy enough to be able to spot AI-generated material,” says Peter Hughes, National Customer Experience Practice Leader, KPMG in Canada. “Retailers need to think carefully about how they’re using the technology, because it could create reputational, legal and financial risks if not used properly and responsibly. Having proper guardrails and controls around the technology is a must.”

While respondents reported already using generative AI numerous ways in their organizations, less than half (46%) have applied the technology within their supply chains, with 34% of respondents planning to implement it in the future.

Of respondents using or planning to use generative AI in their supply chain, four in 10 (43%) said their primary reason is to unlock prescriptive analytic capabilities for customer or sales order fulfillment, such as tapping in-house and external data to identify SKUs and make recommendations to category managers to adjust pricing, promotions, assortment, and delivery and provide mitigation options. Other major drivers include: the ability to analyze information across disparate systems (35%); generating accurate sales predictions based on historical data, trends, seasonality (34%); and inventory optimization (34%).

“Generative AI has the potential to revolutionize supply chain management, logistics and procurement, but only if it’s underpinned by reliable, quality data – that’s where many organizations face challenges,” continued Polyakov. “Their data is not managed and organized in an optimal way.”

Indeed, two-thirds of respondents said one of the main challenges to implementing AI is having non-validated, inaccurate data inputs, which, if used to train the large language models that underpin generative AI platforms, could potentially lead to “hallucinations” or inaccurate or misleading outputs. Seven in 10 (71%) of respondents said their inability to access or leverage data is also a challenge in implementing generative AI.

“Retailers have access to enormous amounts of data – including customer data, sales data and supplier data to name a few – and that data can be leveraged for using generative AI,” Polyakov explains. “But to make that data useful for a generative AI system, retailers must make sure it’s clean, organized and structured. That’s a crucial part of any successful generative AI implementation.”

KPMG in Canada surveyed executive level C-suite decision makers at 135 Canadian retail companies, using Sago’s premier business research panel. The survey was conducted between April 30 and May 6, 2024. Thirty per cent of the companies surveyed have annual gross revenue between $400 million to $599.9 million; 23% have $1 billion or more; and 21% have between $200 million and $399.9 million. No respondents under $200 million in annual revenue were included in the survey. Twenty-nine per cent are in the grocery and supermarket sector, 22% are in the health, beauty, and drug sectors, and 17% are in the clothing and accessories sector. Thirty-seven per cent are based in Ontario, 24% in Quebec, 10% in B.C, and nine per cent in Alberta. The remaining respondents are from other regions across Canada.