AI Drives Retail Transformation Through Six Key Dimensions

Key Quotes

"We created a search and created this universe of factors and different ways AI is being implemented. We didn't have a framework until we had the entire universe of all of these AI use cases. Once we did, then we were able to compartmentalize them and the different groups; we came up with six groups that we were able to cluster."

Simeon Gutman explains the methodology used to analyze AI implementation across companies. Gutman highlights that a comprehensive search was necessary to develop a framework for categorizing the diverse applications of AI before ranking companies. This approach aimed to provide an objective basis for assessment.

"Walmart has full scale AI deployment. They're integrated across their business. They've introduced GenAI tools. That's like their Sparky shopping assistant. As well as integrated to in-store features. They talked about it. It's been driving a 25 percent increase in average shopper spend."

Simeon Gutman provides Walmart as a prime example of extensive AI integration. Gutman points out that Walmart's use of AI spans multiple business functions, including customer-facing tools like the "Sparky" assistant, and has demonstrably impacted key performance indicators such as average shopper spend. This illustrates the tangible benefits of broad AI adoption.

"I would say; I'd characterize adoption in the Food and broader Staples space today is still relatively early innings. I think most companies are still standing up the data infrastructure, experimenting with various tools. We're seeing companies pilot early use cases and start to talk about them."

Megan Clapp assesses the current state of AI adoption in the Food and Staples sector. Clapp indicates that the industry is in its nascent stages, with companies primarily focused on building foundational data systems and exploring initial AI applications. This suggests significant room for future growth and impact.

"Hershey, for example, they're using algorithms to reallocate advertising spend by zip code, based on the real time sell through. So, they can just be much more targeted and more efficient, honestly, with that advertising spend."

Megan Clapp offers a specific example of AI's impact on marketing within the Food sector. Clapp explains how Hershey utilizes algorithms to dynamically adjust advertising expenditures based on real-time sales data, leading to more precise targeting and improved efficiency. This demonstrates a practical application of AI for optimizing marketing efforts.

"The larger debate is a little bit of sales cannibalization and a potential bit of retail media cannibalization. So, your first point is Agentic theoretically opens up a bigger e-commerce penetration and just more commerce. And once you go to more e-commerce, that could be beneficial for some of these companies."

Simeon Gutman discusses the potential downsides of agentic commerce, specifically sales and retail media cannibalization. Gutman acknowledges that while agentic AI could expand e-commerce reach and overall commerce volume, which may benefit some companies, there are also risks of cannibalizing existing sales channels. This highlights the complex trade-offs involved in adopting new AI-driven commerce models.

"There are two ways that we think about just sort of AI spending mattering for our growth forecasts. One part is literally the spend, the investment in the data centers and the chips and so on. And then the other is just the rise in productivity. So, does the labor or does the human capital become more productive?"

Arunima Sinha outlines how AI investment influences economic growth forecasts. Sinha explains that AI's impact is considered through two primary lenses: direct investment in AI infrastructure and the resulting increase in labor productivity. Sinha emphasizes that both factors contribute to overall economic expansion.