The Sentient Store: AI Remaps the Retail Experience for People

NEUHAUSEN, SWITZERLAND – December 09, 2025

The familiar frustrations of brick-and-mortar shopping—the endless search for a specific item, the ghost town of a sales floor when you need help, the checkout line that snakes around the corner—are challenges retailers have grappled with for decades. While e-commerce giants have mastered the art of tracking every click and scroll to personalize online journeys, physical stores have largely operated on instinct and historical sales data. Now, a new wave of artificial intelligence is promising to change that, transforming the physical retail space into a responsive, data-rich environment that learns from the people within it.

Leading this charge is Sensormatic Solutions, a retail technology portfolio of Johnson Controls, which has unveiled a powerful new system called Store Guest Behaviors Analytics. By deploying a network of smart sensors and cameras, the platform aims to provide retailers with the kind of granular, real-time insights that have long been the exclusive domain of their online counterparts, potentially heralding a new era of efficiency and customer satisfaction.

How AI is Learning to Shop

At the heart of the new system is a sophisticated blend of hardware and AI. Overhead sensors, known as Orbit AI, and discreet Video AI cameras are installed throughout a store. These devices use a technology called Re-Identification (Re-ID) to anonymously follow the paths of shoppers as they navigate the aisles. This isn't about knowing who you are, but rather understanding what you do.

The system generates a detailed, anonymous map of in-store activity. Retailers can see the most common paths customers take from the entrance to the checkout, a metric known as "path-to-purchase." They can identify which displays and promotional endcaps cause shoppers to pause and engage—measuring "dwell time"—and which are consistently ignored. It can also pinpoint "hot zones" of high traffic and "cold zones" that are underutilized, providing a clear blueprint for optimizing store layout and product placement.

"The key is capturing and analyzing those in-store insights to streamline store operations and maximize profitability," explained Tony D’Onofrio, president of Sensormatic Solutions, in the company’s announcement. The technology gathers and reports on real-time activity, helping retailers respond dynamically to what's happening on the floor.

This isn't merely theoretical. LIDS, the popular sports apparel and headwear retailer with over 2,000 locations, is an early adopter. "This new technology gives us a clearer picture of how shoppers move through our stores and helps us make smarter decisions to improve their experience," said Erika Long, director of operations at LIDS. The partnership demonstrates a practical application of AI to solve long-standing retail puzzles, moving the concept from a tech conference buzzword to a tool actively shaping the shopping floor.

The Promise of a Seamless Experience

For the average shopper, the impact of this technology may be felt without ever being seen. The data collected is designed to directly address the most common pain points of the in-store experience. Industry studies reveal a stark reality: as few as 9% of consumers report being satisfied with their physical shopping trips, citing a growing gap between their expectations and what retailers deliver.

By analyzing traffic flow, retailers can make data-driven decisions about staffing. The AI can identify peak shopping times down to the hour, ensuring more employees are available to assist customers and operate cash registers, potentially shortening the dreaded checkout queues that lead to an estimated $38 billion in lost sales annually in the U.S. alone.

Furthermore, understanding how shoppers interact with the store's layout allows for more intuitive merchandising. If data shows that customers frequently circle a department looking for a related item located elsewhere, a retailer can reorganize to create a more logical flow. This leads to a less frustrating and more efficient trip for the consumer, who can find what they need faster. The goal is to create an environment that feels less like a maze and more like a curated journey, subtly guided by the collective behavior of thousands of previous shoppers.

Innovation with an Eye on Privacy

In an age of heightened awareness around data collection, the concept of being tracked in a store immediately raises red flags. However, this is where Sensormatic Solutions is drawing a critical line. The company emphasizes that its Re-ID technology is built with privacy at its core, deliberately avoiding the use of Personally Identifiable Information (PII).

Instead of facial recognition or other biometric data, the system relies on generic, anonymous attributes like the color of a person's clothing to differentiate individuals during a single visit. Once a person leaves the store, that anonymous identifier is gone. This method allows the system to understand that the person in the blue jacket who looked at hats later went to the t-shirt aisle, without ever knowing or storing who that person is. Furthermore, the AI is trained to distinguish between customers and employees, ensuring that staff movements don't skew the shopper data.

This privacy-centric approach is not just an ethical choice; it's a strategic one. With stringent regulations like Europe's GDPR and California's CCPA setting a global standard for data protection, technologies that can deliver powerful analytics without harvesting personal data are positioned for wider adoption. It represents a move toward responsible innovation, where the benefits of AI can be harnessed without compromising the fundamental right to privacy, building a foundation of trust that is crucial for consumer acceptance.

Redefining the Role of the Retail Worker

Beyond the customer experience, the infusion of AI into store operations is set to profoundly reshape the retail workforce. The immediate concern with any automation technology is job displacement, but the reality may be more of a transformation. By automating the analytical work of monitoring traffic and identifying patterns, AI frees human managers and employees from repetitive, data-heavy tasks.

Instead of manually creating schedules based on last year's sales, a manager can use AI-driven forecasts to optimize staffing for the week ahead. This allows them to spend more time on the floor, coaching employees and engaging with customers. For frontline staff, the shift is even more significant. As AI and other technologies handle routine tasks, the value of human interaction grows. The role of a retail associate evolves from a transactional clerk to a brand ambassador, a product expert, and a customer experience specialist.

This transition necessitates a focus on reskilling and upskilling. Employees will need training in digital literacy and how to work alongside AI-driven systems. More importantly, soft skills—empathy, complex problem-solving, and personalized service—will become the most valuable assets a retail worker can possess. The most successful retailers will be those who invest in their people, empowering them with technology to deliver the kind of nuanced, high-touch service that no algorithm can replicate. This human-centric approach turns technology into a tool that augments, rather than replaces, the workforce, creating more engaging and fulfilling roles.

The line between the digital and physical worlds continues to blur, and innovations like Store Guest Behaviors Analytics are writing the next chapter for brick-and-mortar retail. By embracing data while respecting privacy, retailers have an opportunity to not only survive but thrive, creating smarter stores that are more efficient for businesses, more enjoyable for shoppers, and more empowering for the employees who are the heart of the in-store experience.