From supply to shelf-life management: how AI makes supermarkets smarter

Artificial intelligence in supermarkets is no longer a futuristic strategy, but a reality among us. Its use goes far beyond self-service kiosks: today, technology executes a series of routine activities in the sector, bringing speed, accuracy, and fluidity across departments.
Supply, category management, pricing, and product expiration tracking are some of the tasks driven by AI. This makes the supermarket more efficient and frees up staff to focus on strategic and humanized efforts, such as in-person service and physical planogram execution.
Supermarket owners who learn to leverage technology in their favor optimize processes and significantly expand business margins.

AI in supermarkets: how does it work?
There are several AI solutions tailored to supermarket routines. One example is Web Jasper, a benchmark in Category Management and Trade Marketing software. In a conversation with ASSERJ, Michel Jasper, CEO of the company, explains that the workflow begins with integration into ERP data, such as sales, inventory, and operations.
"From this data, the system uses business rules, Category Management, and artificial intelligence to analyze the category's status and generate recommendations. The software identifies, for instance, that a specific product has low turnover, that another is gaining traction, that there is excess inventory, or that a category needs re-organization. With this, the retailer creates or adjusts the planogram, defines the assortment, and guides store execution," the executive clarifies.
Michel points out that the technology also analyzes point-of-sale images to audit execution, identifying stockouts or display discrepancies. "The workflow can be summarized as: data, analysis, decision, planogram/execution, audit, and finally, learning. This allows the supermarket to move away from purely reactive work toward continuous, automated, data-driven management," he highlights.

What does AI do for the supermarket operator?
One of the main fronts addressed by AI systems like Web Jasper is shelf-life management. With this tool, managers don't need to manually check every SKU: the system identifies and supports the clearance of items before they expire, reducing loss and waste. But the capabilities don't stop there!
Michel Jasper highlights the main solutions AI offers to supermarket operators:

• Category Management: "Uses retail data to support decision-making regarding assortment, display, and category strategy. The core objective is moving from 'where to place the product' to 'what is the best strategy for that category in that supermarket?'"
• Supply / Replenishment: "Helps identify excess inventory and supports better product distribution in the store."
• Shelf-Life Management: "Supports the monitoring of items near expiration and guides actions on those products."
• Planograms: "Allows creating and managing product placement on shelves while accounting for specific rules per category, store, or cluster. The solution also enables working with seasonal planograms and integrating ERP data."
• AI Auditing: "The technology analyzes shelf images and verifies planogram execution, identifying display issues and stockouts. This allows tracking not just what was planned, but what is actually happening in the store."
• Trade Marketing Management: "Allows managing the relationship between manufacturers and retailers, including features like JBP (Joint Business Plan), helping turn agreements and commercial strategies into execution plans."

Currently, Web Jasper is already used by several retail chains in Rio de Janeiro, such as Supermarket, Zona Sul, Armazém do Grão, and Terê Frutas.
Sérgio Lema, an IT professional at Zona Sul, shares that the chain is currently running a pilot project with WebJasper in one of its stores, and the project is in the category mapping phase. Although there are no definitive data yet regarding the direct impact on sales or margins, the outlook is promising for operations.
"We believe the tool will bring long-term benefits to standardizing shelf layouts," says Sérgio. He highlights that Zona Sul also has multiple initiatives underway involving tools that, in one way or another, use artificial intelligence to optimize processes and boost productivity.
"We are piloting enterprise AI platforms to build custom agents. We have initiatives running on N8N, as well as multiple individual enterprise licenses for Gemini, ChatGPT, Claude, and CoPilot for strategic employees," Sérgio exemplifies.

Real benefits of AI for the point of sale
According to Michel Jasper, using AI boosts sales and profitability in supermarkets. "Better category organization can improve turnover, margin, and space productivity," he states. Another highlight is stockout reduction, one of the industry's biggest challenges. "Technology allows us to spot supply issues and support staff in correcting execution," Jasper notes.
Category management also becomes more efficient as technology converts data into practical recommendations, leading to superior assortment management at the POS. "[AI] helps understand which products should stay, enter, or leave the category, avoiding an excess of low-relevance SKUs," the CEO explains.

Anyone who thinks technology only applies to the digital world is mistaken: AI improves the use of physical space, ensuring a more effective shopping journey. "Planograms help define where, how, and in what quantity each product should be displayed," he says. For chains with many dispersed stores, it establishes tailored strategies per unit, category, or cluster without relying solely on manual processes, ensuring greater operational standardization.
It is worth emphasizing that AI drives agility by automating tasks that traditionally take hours of analysis. "Planograms, for instance, can generate a category layout suggestion in seconds," Jasper clarifies.

However, it is important to note that this is not about replacing human work, but providing a tool to encourage sharper, smarter decision-making. "The platform integrates ERP data, business rules, category insights, and AI capabilities to turn data into actions," the specialist concludes.