Retailers are still testing generative AI strategies, according to a new report – Digital Commerce 360

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Retailers are increasingly adopting generative artificial intelligence (AI), but they don’t always have strategies to use it most effectively, according to a new report from Salesforce and the Retail AI Council. They surveyed 1,390 global retailers on their generative AI usage. 
“The AI revolution is about data, trust and customer experience,” said Rob Garf, general manager of retail and consumer goods at Salesforce, in the report.
“Looking at artificial intelligence in isolation, without understanding these elements as a package, will hurt a retailer’s ability to build loyalty and improve customer relationships,” he added. “This research we’re announcing today aims to help retailers better understand the need for a unified data strategy, the practical applications of generative AI and how that can be used to enhance the experience for both shoppers and associates.”
Salesforce provides technology services to retailers in the Digital Commerce 360 Top 1000, including to 69 retailers as an ecommerce platform, 56 for web hosting and cloud services, and 55 for its content delivery network. The Top 1000 is Digital Commerce 360’s ranking of the largest online retailers in North America by sales.
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Survey results revealed that retailers are willing to experiment with AI. 93% of surveyed retailers said they’re already using generative AI in some capacity for personalization. That includes creating personalized email copy and product recommendations.
81% of retailers in the survey said they have a dedicated AI budget. On average, about 50% of the total AI budget goes toward generative AI, they said. 
Retailers were most likely to say they plan to use generative AI for customer service, marketing, and store operations purposes. Customer service was the most popular use case. Retailers said they want to use AI to send personalized automated messages to customers more quickly than human customer service workers would be able to. 
Digital shopping assistants were the next most popular use case among retailers, the report found. Retailers want to use generative AI to make these assistants conversational and easy to use to help customers find the right products.
Despite the willingness to embrace generative AI, retailers are still working out issues in using data to make the technology as effective as possible. Many retailers are struggling to unify their data in a way that gives a comprehensive view of customers, the report said.
Just 17% of survey respondents said they have a complete, single view of their customers and that they’re harnessing data effectively. That’s a problem because generative AI is only as useful as the data it works with, Garf said. Incomplete data can lead to ineffective or inaccurate outputs, Salesforce said. It could also lead to biased results, the report said.
49% of retailers in the survey said they’re either in the preliminary stages, or considering creating complete customer data profiles. 67% of retailers said they can fully capture customer data, but only 39% are fully able to clean it. 42% said they can fully harmonize the data. 
Once they do have data, actually using it also poses a problem. 40% of retailers said they are struggling to use the data to make decisions. 47% said they’re facing problems making it accessible. 
Retailers are working to comply with ethical and security standards, they told Salesforce in the survey. That’s especially important because just 13% of customers completely trust companies to use AI ethically, and 63% are concerned about bias with the technology, according to Salesforce data.
50% of surveyed retailers said they have the ability to fully comply with security standards and data-privacy regulations. Half of retailers said prejudiced results from generative AI were a concern. 38% cited hallucinations and 35% cited toxicity as other risks from using the tool. 62% of retailers reported that they have guidelines to address transparency, data security and privacy in their generative AI use.
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