Navigating a Transformative Era for the Retail Industry
Last week I was lucky enough to be able to attend NRF’s Big Show, the premier event for retail leaders focused on the latest technologies shaping the industry. Here are some of the biggest trends from the floor and presentations.
You Have More Data than Ever – Often in Real Time
We’re moving closer and closer to a time when everything about your business becomes a structured data point. While we’re not quite there yet, technologies like 2D barcodes, RFID tags, computer vision, and IoT – among others – are providing more of these data points than ever before, covering everything from the supply chain to retail operations.
More and more of this data is also being provided in real time. 2D barcodes and RFID tags can help to identify the exact item that was sold so you know it should (or shouldn’t) be walking out the door. Computer vision in stores is doing real-time stock counts and identifying customers that need help to alert an associate of their location. Even paper towel dispensers in bathrooms are reporting their status, alerting staff exactly when they need to be replaced.
Making sense of all this information – and deciding what to do with it – is an increasing challenge. With more data points come more opportunities for analytics, and understanding where to focus to realize the most value from your investment is critical.
Agentic AI is Here
Whether it’s a virtual personal shopper, a customer-service chat bot, or a retail associate assistant, the rise of the AI agent is upon us. “Agentic” AI refers to allowing AI to make changes to your systems by interacting with specified tools. For example, a virtual personal shopper may have tools for searching products, getting product information, adding products to a user’s cart, and checking the user out.
When AI is given the opportunity not just to analyze your data but to take action on it, incredible opportunities arise for improvements to customer experience, associate experience, and productivity.
Hyper-personalization is Now Possible
The additional data you have about your customer combined with technological advancements in computer vision and AI are increasing opportunities to create more tailored experiences for your customers. These experiences are beyond just understanding customer preferences and can range from dynamically altering product descriptions to providing virtual showrooms.
Back to our virtual personal shopper, this type of agent can learn from a customer’s purchase history to understand their preferences and use that to help drive their recommendations. It can even dynamically alter romance text for each user, highlighting the information that they find important and restating it with language and tone that might be more appealing to them. This tailored shopping experience can rival or even surpass the in-store experience, increasing sales, customer satisfaction, and brand loyalty.
You Need a Framework for Getting AI into Production
With ease of use comes proliferation. The ubiquity of AI tools and the velocity with which you can build with them will lead to a glut of proofs-of-concept as you start to experiment. In order to realize value from this experimentation it’s imperative that you have a framework in place to take these projects from proof-of-concept to production. Such a framework needs to focus not only on quantifying the value that each project can create, but also on how to build a technical foundation that ensures you’re realizing compounding value as you deliver more and more of them. Each project shouldn’t be delivered in a vacuum – they should work towards a cohesive vision of AI use across your organization.
It’s also imperative that you have appropriate guardrails in place for vetting projects that get deployed. Think about the potential opportunity risk of deploying an agent that has a flaw in it – these agents could incorrectly paraphrase product information or return the wrong status for an order. There needs to be an evaluation process for ensuring that these agents are performing as intended before they get published to the organization – or to the world.
Your AI Will Only Be as Good as the Data You Feed It
Humans are often inherently distrusting of data. I can’t tell you how many times we’ve put a very accurate forecast in front of a business partner only for them to say “but how do I know it’s right.” Sometimes we see things that just don’t make sense and we know to pass over them, discount them, or modify them in our heads to fit our needs. Humans will be skeptical of bad data – AI agents won’t. AI will take this data at face value unless told otherwise, and if you give the ability to take actions – crafting marketing campaigns, placing orders, rerouting shipments, etc. – you risk those actions being made based on incorrect logic. This can be catastrophic not only for your AI implementation, but for the business as a whole.
Are you a retailer struggling with where to implement analytics and AI or wondering how to get started? We offer a range of services to help you successfully navigate the AI revolution, from helping you craft your AI strategy to delivering game-changing AI-driven business outcomes. Reach out to us at [email protected].
* This content was originally published on Nousot.com. Nousot and Lovelytics merged in April 2025.
