NRF 2025: Retail’s Big Show – AI is an everyday tool
Yup, AI has become plumbing.
As NRF 2025: Retail's Big Show made clear, artificial intelligence has reached a crucial tipping point in retail. In my follow-up column to last year's Big Show, I wrote that AI had become “accepted and assumed,” but not yet “plumbing” (something that is assumed to be part of the infrastructure and only noticed when it breaks).
In my preview column for this year’s NRF 2025: Retail’s Big Show, I went a step further and said that AI was no longer the shiny, new thing, but still not quite plumbing. Based on what I saw and heard at the conference, AI has finally become plumbing in the retail technology environment. It is universally adopted and an expected component of the retail IT enterprise.
Following are three ways AI is serving as a practical enabler, rather than a showy attention-grabber.
A store employee's best friend
The biggest surprise of the entire conference was how many different exhibitors were offering some variety of AI-enabled assistant for store associates.
Mostly delivered via app located either on an employee’s own mobile device or retailer-owned mobile device (though the service can also be offered through fixed devices such as in-store kiosks), these AI assistants provide employees with instant access to nearly limitless volumes of all types of information.
Data available at employee fingertips includes product information, enterprise inventory availability (in-store, at other stores, in a warehouse or fulfillment center, etc.), customer reviews, and store policies and procedures.
In addition to enabling associates to provide substantially higher levels of customer service, proponents of AI store employee assistants say they also allow employees to perform at a much higher level with far less training, resulting in improved efficiency and enhanced employee satisfaction.
And for Gen Z and Gen Alpha associates who grew up using mobile devices to navigate and streamline their everyday lives, offering this type of AI-based mobile assistance meets their expectations and can aid in recruitment and retention at stores.
AI agents of fortune
In tandem with the near-ubiquitous presence of AI-enabled store assistant technology was the surprisingly low profile of agentic AI, the latest wave of AI evolution which builds upon the prescriptive capabilities of generative AI to streamline enterprise workflows even further.
Agentic has been the leading buzzword in AI for the past few months, and the fact it was widely available but not heavily promoted on the exhibit floor signals that retailers now view advanced intelligent enablement of their enterprises as a routine proposition.
Generative AI, which is based on machine learning, can create new content and ideas and create recommendations based on analysis of volumes of data in near-real-time that were previously too big to evaluate.
Agentic AI goes a step beyond by analyzing massive amounts of data in near-real-time and then automatically taking action based on the results. For example, an agentic AI pricing solution could adjust prices based on factors specific to a local store or an agentic AI chatbot could automatically issue a customer refund or flag a complaint for fraud depending on its deep-dive analysis of the situation.
The thinking person’s device
Finally, AI is increasingly finding its way into devices themselves. Several exhibitors were displaying smart camera technology which automatically determines a customer’s age, avoiding the need for associates to verify if an ID is legitimate or ask embarrassing age-related questions for shoppers buying restricted products like alcohol or tobacco.
This type of embedded AI is distinct from Internet of Things or RFID-enabled functionality that monitors and transmits status data and instead turns “dumb” devices into thinking, analytical machines.
[READ MORE: 2025: The year RFID breaks through]
Another good example is the increasingly sophisticated "smart carts" that track customer location in the store, products that are examined, placed in or removed from the cart, and then link to data such as shopping lists, recipes, previous shopping behavior and loyalty program activity to create a highly tailored and targeted in-store customer experience that resembles the personalization and guidance of online shopping.