The 4 Biggest Retail and Technology Trends at NRF’s Big Show 2025
The annual National Retail Federation (NRF) Big Show in New York City wrapped up Tuesday evening, bringing to an end 3 full days of keynotes, conference sessions and exhibitor talks about almost everything under the retail sun.
While the show covered plenty of ground, some topics were notably more prevalent this year and would seem to be setting the course for retail in 2025. In this blog article, I’ll explore the 5 biggest retail and technology trends that surfaced at NRF’s Big Show 2025, and what they mean for retailers.
First, the list:
- A transformation in customer experience
- The two workforces of the future
- Social commerce and community commerce
- Dynamic and intelligent supply chains
Want to see how AI is powering a supply chain revolution? You can now watch the full video of Blue Yonder’s Big Ideas Session from NRF 2025: The supply chain revolution: Can your organization succeed in the age of AI?
Now, let’s dig in.
A transformation in customer experience
Some readers will have been surprised that we’ve so far avoided the term artificial intelligence (AI), but the reason it’s not a trend in and of itself is largely because it has become truly embedded in retail businesses in the past year. The focus is now on precisely how the revolution is rolling out in specific business areas. A recurring theme in talks and keynotes was the importance of ‘remaining human’ or ‘humanizing’ the retail use of AI, and nowhere more so than when the topic was customer experience (CX).
We heard about Saks deploying new LLM chatbot technology to act as a virtual sales assistant, and SharkNinja’s CIO Velia Carboni said that while she acknowledged the huge productivity gains that AI solutions can offer in terms of “doing our jobs more easily and focusing on value add”, the “more exciting part” is the value added in CX. She cited AI’s ability to leverage vast amounts of customer data in order to “get shoppers excited about the experience as well as the product”.
Amazon’s CEO Worldwide Stores Doug Herrington gave a laundry list of CX improvements his team has driven with AI:
- LLM-driven review summaries capture insights from hundreds of reviews into easily digestible bullets to save customers time in seeing the pros and cons of a product.
- Product titles get re-written on the fly by another generative AI tool, which tweaks product titles based on the user’s search terms to make it clear that they’re relevant.
- Another model ingested size charts, customer purchase and return data, as well as feedback from return reasons and customer reviews, to generate sizing and fit recommendations for customers buying apparel and footwear based on their previous history and other customers’ experience of a given product.
Moving on from AI for a moment, DICKS spoke about the role of geolocation in bringing out a new dimension to the store experience. Customers with the DICKS app receive targeted messaging through an app notification when the geofence at a DICKS location detects that they’ve walked into the store, driving a new kind of store experience enabled by the app and digital commerce. (More on the overlap of digital and physical later…)
And from a supply chain perspective, an interesting trend that cropped up across several talks was the notion of localized assortment: harnessing granular demand data on a store-by-store or region-by-region basis to tailor assortment planning and inventory to better match what customers really want from a retail store. Tailored Brands’ CTO Scott Vifquain noted that while it’s perhaps interesting in the abstract to know that men’s shirt sizing is trending downwards nationally, what’s really useful is the ability to tailor (excuse the pun) the sizes carried by an individual store in response to specific demand data from that store—something only made possible at scale by the power of AI.
The two workforces of the future
AI agents are having a moment. For a while the excitement and hype around generative AI seemed to critics like a fever pitch that couldn’t be sustainable, and anyway how useful can a chatbot be outside of customer support? “Agentic AI” is here to settle these debates.
In the course of the show, AI agents turned up embedded in software solutions from merchandising to inventory, and in more standalone roles like sales assistant, store assistant for associates, or managing returns and refunds with customers. Where once it was reasonable to ask what use cases there were for this new breed of AI, it’s now apparent the answer is almost all of them.
But while this new generation of digital workers is debuting and sometimes operating autonomously, there’s still plenty of emphasis on the real people driving retailers forward every day: their associates in stores, head offices, fulfilment and distribution centers, and so on. They still need to be the ones making decisions, engaging with customers face to face, and taking strategic control.
In that vein, PacSun discussed deploying new LLM chatbot technology to act as a store associate helper: “your best coworker in your back pocket”, according to Shirley Gao, PacSun’s Chief Digital and Information Officer.
In Blue Yonder’s Big Ideas session, we heard from Nik Haggerty, the Head of Retail, Supply Chain & ERP Technology at Chalhoub Group, who spoke about the value that AI drives for employees using the example of clearance pricing. Where previously it would require intensive analysis of sell-through, current stock, pricing, last year’s results and forecast accuracy to generate a decision on markdowns, AI can now rapidly perform that analysis and allow users to choose from a set of paths forward.
“That person’s role is then shifted from being in a hamster wheel cranking out analysis to having a decision augmented in front of them, which we’re really excited about.”
Rob Bogan (Chief Technology Officer, DXL Group) echoed that sentiment.
“We want merchants to be merchants. Back in the day, they would spend a month as data analysts getting ready for a line review, and then in the line review they couldn’t answer a strategic question because they’ve been so mired in the data.”
Rob cited specifically the value of the assistant/agent model for merchants and planners: “the magic is in having an LLM, a natural language model, where a merchant or planner can ask questions like ‘what are the 10 items with the best attributes that I should think about for the next fall season?’ And a human could do that work, but it would take two to three days. So now we get them back to being actual merchants.”
Social commerce and community commerce
The explosive success of TikTok Shop—which has seen the short-form video app overtake Sephora, Shein and Qurate Group in terms of monthly consumer spending in the last year following 196% year-on-year growth—was raised multiple times across the conference. That interest was amplified perhaps by TikTok’s at-the-time uncertain future in the US (it is now set to be banned), but the sheer potential for retailers who can harness the short-form and live-streaming algorithms of platforms like TikTok, Instagram Reels and Youtube Shorts is clear.
However, ‘true’ social commerce, i.e. shopping within the social app rather than ads linking out to retailer sites or apps, seems to be still at an early stage of maturity, even though it’s growing at twice the rate of e-commerce in the US according to data presented by Emarketer’s Principal Analyst for Retail & E-commerce, Sky Canaves.
The CX, in TikTok’s case at least, seems remarkably on-point. Data from a survey by The New Consumer, presented by founder Dan Frommer, shows that:
- 60% of Gen Z and 50% of Millennials who are aware of TikTok use it every day
- 50% of TikTok’s active users have now shopped through TikTok
- The shopping platform earns 91% user satisfaction
- 90% of users say they’d shop again
- 87% say it’s a natural extension of the TikTok experience
However, retailers can still be cautious about the prospect of jumping into social commerce.
Fernando Rosa, President of Havaianas Brazil, noted that there remains a lack of trust and higher risks of counterfeiting and/or imitation of brand presence. He added that internationally, the availability of different social commerce channels is different, and even though Brazil is the second biggest nation in the world in terms of active social media use, TikTok Shop is not yet live there.
Something retailers across the show mentioned frequently was the importance of building community around their brands. Rare Beauty’s Chief Marketing Officer Katie Welch particularly emphasized this, but it was also touched upon by Havaianas’ Fernando Rosa, Linda Li (H&M Americas’ Head of Customer Activation & Marketing), as well as SharkNinja’s CIO Velia Carboni.
The throughline for these retailers is that the way they think about CX encompasses content, creators and community to drive long-term brand engagement, even when their products don’t necessarily lend themselves to frequent repeat purchases (as in the case of SharkNinja’s blenders and vacuum cleaners). This approach can help to drive down customer acquisition and re-acquisition costs as consumers are voluntarily returning to brand channels for style tips, recipes, how-to guides and content from creators they follow elsewhere too.
Dynamic, intelligent supply chains
It’s an oft-repeated mantra, and perhaps tautological, but having the right product in the right place at the right time was a recurrent ambition for retailers at NRF’s Big Show this year. Multiple vendors and retailers aimed at reducing total inventory at the same time as improving availability and reducing lost sales. Plenty of this focused on accurate demand insights and forecasting, but as Scott Vifquain (CTO of Tailored Brands) notes, the ability to actually execute against a forecast, at scale, is critical:
“People think better forecasts equals better decisions, but that’s only partly true. If you look at our SKUs across our stores and DCs, you effectively have 20 million decisions to make every day.”
Once again, the role of AI is to allow supply chain teams to automate much of that decisioning process. Nik Haggerty, in his conversation with Blue Yonder’s Chief Innovation Officer, Andrea Morgan-Vandome, described this new kind of interaction as “augmented decisions”, where one layer of AI reasons against the business data to determine a set of options for the user, who remains in control of which strategic direction to take.
Shaun Bunch, Chief Supply Chain and Retail Officer at Northern Tools + Equipment, was one of those present who highlighted the critical importance of network design and logistical execution, and how retailers are increasingly pushing to improve these areas of their supply chain through technology.
“Network design, and the flow of inventory through that network—that’s where a lot of the push is.”
Agentic AI is already present in this space in the form of One Network’s NEO agent, which flags exceptions and issues to users, as well as offering prescriptions to fix them, such as adding extra inventory to an order to prevent a likely out-of-stock in a store or DC, or re-routing a shipment to avoid weather-related delays—and ultimately executing these changes when instructed by the user.
This type of AI-powered supply chain tech illustrates what Nik Haggerty describes as a long-term ambition for Chalhoub Group: moving towards managing the supply chain by exception. In essence, much of the functional work is absorbed by AI and agents, leaving the people to power strategic decisions, understanding the market and their customer better, and to respond with their expertise and human understanding when issues arise—whether following the recommendation of an AI agent or not.
You can now watch the full video of Blue Yonder’s Big Ideas Session; The supply chain revolution: Can your organization succeed in the age of AI? and find out more about our AI-powered supply chain solutions.