GenAI Is Poised to Alter Trajectory of Grocery Operations
While generative AI (GenAI) has been around since The Beatles hit the scene in the 1960s, the technology came screaming into everyday consciousness over the past year and is quickly capturing the attention of individuals and enterprise-level businesses alike. At a base level, GenAI allows users to generate new content, such as text, images, videos and sounds, by inputting a particular prompt, and it constantly learns from data models to get even smarter.
The simplicity of today’s user interfaces and the ability to create brand-new content in mere seconds have made GenAI particularly buzzworthy, and OpenAI’s introduction of ChatGPT in late 2022 served as a major catalyst for the technology’s increased adoption. GenAI’s applications in food retail run the gamut from assisting with assortment planning to managing supply chain logistics and providing customer assistance, and advancements in the space are poised to permanently alter the trajectory of grocery operations.
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Future-Forward Applications
Many food retailers are working toward adopting GenAI into their tech stacks, and Azita Martin, VP of retail, CPG and QSR at Santa Clara, Calif.-based software company NVIDIA, is seeing forward movement in employee-facing use cases that help promote both creativity and productivity, including everything from basic in-store tasks to higher-level marketing and campaign generation.
According to Martin, today’s GenAI advancements can add a lot of value on the associate side in regard to e-commerce and mobile apps, especially in relation to writing product descriptions. When trained properly, GenAI can easily identify particular product attributes that customers seek out, and write a comprehensive product description. Content managers can then double-check the generated descriptions and make small changes instead of writing them from scratch.
Vijay Raghavendra, CTO at Palo Alto, Calif.-based SymphonyAI, believes these types of applications can help grocers solve perennial labor issues by automating mundane and repeatable duties, thereby freeing up associates to spend their time helping customers and completing other value-added tasks. Even job functions like category management can harness the power of GenAI to make more informed choices regarding changes to assortment, customer impact and more, Raghavendra explains.
On the consumer-facing side, Martin observes that shopping advisors are likely to be in the next wave of retail-specific GenAI applications. These pop-up assistants can help online shoppers choose products that fit certain criteria, find recipes that use particular ingredients, and even enhance omnichannel shopping by helping customers locate items in physical stores.
Martin believes that all of these use cases are adding to GenAI’s eventual ability to replace search as we know it. “It’s the next-generation, sophisticated search that is more personalized, more visual and a lot more accurate,” she explains.
Taking the Leap
As for retailers taking the plunge, Walmart is in the throes of examining its relationship with GenAI, and recently shared the positive benefits that the technology can have on the customer shopping experience, as well as how it can help associates do their work more effectively. To help increase productivity and unlock transformation for its campus associates in the United States, the Bentonville, Ark.-based company launched the My Assistant feature, a desktop and mobile app that can speed up the drafting process, serve as a creative partner, summarize large documents, and more.
Instacart is also harnessing the power of GenAI with a plug-in that allows its customers to shop via food- and recipe-related conversations with ChatGPT, and then have suggested ingredients added to their cart and delivered directly to their door. In the future, San Francisco-based Instacart plans to roll out even more GenAI capabilities, one of which would help people shop recipes or ingredients that are on sale or in season.
[Read more: "Google Cloud Brings Powerful GenAI Tools to Retailers"]
Preferabli, an AI-driven software company based in Syracuse, N.Y., built GenAI for the grocery industry and trained its preference models using its proprietary database, with hundreds of characteristics for every product. Users can enter any wine in the world, and Preferabli will respond with other wines that taste like the reference wine. The company’s latest release can be anchored in any inventory.
“Preferabli GenAI makes it possible for a shopper to free-form type something they like or want to eat and have that begin a journey of discovery within their experience, deeply enhancing any grocery platform focused on its shopper preferences,” says Andrew Sussman, co-founder and CTO of Preferabli.
“Preferabli’s ability to pair any wine or spirit in inventory with any food or recipe changes the game,” continues Pam Dillon, co-founder and CEO. “When food experiences come alive in this way, basket sizes have a way of increasing very quickly.”
Taking Stock of Where GenAI Stands
While SymphonyAI’s Raghavendra believes that the technology is a game-changer that effectively democratizes access to important insights, he cautions that it’s not the silver bullet some believe it to be. “It does not solve all problems,” he emphasizes. Instead, Raghavendra recommends being aware of the potential challenges of adopting GenAI and ensuring that it fits together with both existing infrastructure and long-term business goals.
Similarly, NVIDIA’s Martin says that the enterprise-grade deployment necessary to bring GenAI into large businesses is being underestimated, as is the necessity of maintaining customized data models to ensure that information is flowing correctly.
Regardless of potential hurdles, Raghavendra is adamant about the importance of GenAI in improving business outcomes now and in the future.
“I really believe that if you do not embrace this technology, and be aware of what it can and can’t do and where you will apply it, it becomes an existential problem for you,” Raghavendra asserts. “Your competitors are going to be using this technology to enable their merchants, their demand planners, across the different parts of the grocery ecosystem to make better decisions, faster decisions, and you’re going to be at a disadvantage.”
