Modern Retail+ Research Data Sheet: Applications of AI in today’s retail world
This is the Modern Retail+ Research Data Sheet, a new monthly feature that takes an in-depth look at our survey data in relation to major trends in the marketing and media industries. In this month’s data sheet, we look at the state of AI and how it’s being applied for retailers. Among experts, such as the VP of emerging technology at Walmart Global Tech, whom Modern Retail interviewed, many noted the way AI allows retailers to gain a better understanding of their customers.
In 2024, marketers and retailers significantly increased their adoption of AI. However, despite initial ambitions to build AI systems in-house, many brands have shifted to working with third-party vendors, recognizing the efficiency and cost benefits of building on existing infrastructure provided by industry tech leaders like Amazon, Google and Microsoft.
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Adoption of NLP and AI tools was up in 2024
Across the board, marketers’ adoption of AI technology has steadily increased over the last three years.
“From a consumer perspective, [Walmart’s proprietary GenAI platform Wallaby] has a good understanding of our products and what it is that we sell and we serve,” said Desirée Gosby, vp of emerging technology for Walmart’s Walmart Global Tech division. “An example of that would be having a deep understanding of our brand. We have ‘Great Value’ as a brand within Walmart. And in the generic sense, everybody wants to get a great value. But knowing in the context of Walmart that you’re actually talking about our brand specifically is important to us to make sure we’re communicating correctly with our customers.” –Desirée Gosby, vp of emerging technology at Walmart Global Tech
Where retailers are investing now
Retailers are investing in AI for applications including loss prevention, predictive inventory analytics, automated checkouts, customer service, chatbots and personalized product recommendations.
Marketers continue to work with third-party vendors for AI solutions
“We had these grand ambitions upfront of feeling like we need to build [AI] in-house, and I think that’s because a lot of clients and brands viewed this wave of AI like the internet in 2000, going from zero to one. The true headstarts lived in the Amazons, the Microsofts with the OpenAIs, the Googles, the Metas. They had such a massive head start because they’ve been using this technology as part of their infrastructure. … To build it yourself, you need owned server farms, to have the expertise of data scientists. It was just an exorbitant cost. Instead, you could take this nice layer built by a tech giant and then build your custom layer on top, and still have the same benefits at an absolute fraction of the cost.” –Matt Maher, founder of M7 Innovations