Loss prevention: AI is revolutionizing shoplifting detection
Loss prevention is a central concern for executives of retail chains, particularly in grocery, DIY and pharmacy. According to the NRF report The Impact of Retail Theft & Violence, shoplifting incidents rose by 93% between 2019 and 2023, considerably increasing the pressure on retailers' margins. Faced with this trend and the rise in shrinkage, traditional security solutions are showing their limits. This is where at-risk gesture detection technology comes in, using AI-powered video analysis, an innovative lever that turns loss prevention into a proactive and intelligent approach. By analyzing at-risk gestures in real time using dedicated GPUs and AI algorithms, this solution flags at-risk situations before they turn into outright losses.
This anti-theft technology does not simply spot obvious theft gestures: it also identifies ambiguous gestures that are frequently associated with theft. At-risk gesture detection software enables security teams to intervene more effectively, without disrupting the customer shopping experience. By focusing on genuinely at-risk situations, detection optimizes human resources and reduces losses.
For executives, this means better control of shrinkage-related losses and a concrete return on investment thanks to automation. A technology that combines economic performance and operational efficiency.
Managing shrinkage with data and real-time decision-making
Beyond security, at-risk gesture detection contributes to the overall streamlining of operations. By collecting data continuously, intelligent solutions offer unprecedented visibility into in-store dynamics. Managers can thus identify sensitive areas, adjust customer journeys, redeploy teams and improve aisle layouts to reduce opportunities for theft. The work of the Loss Prevention Research Council (LPRC) confirms the effectiveness of this evidence-based approach for strengthening asset protection at the point of sale.
This not only strengthens loss prevention, but also optimizes labor costs and refines merchandising strategies. Executives have concrete tools to make informed decisions based on real data, not assumptions. As highlighted in the McKinsey report The State of AI 2025, 88% of organizations already use AI in at least one business function. Retail is no exception, and loss prevention is an area where the return on investment is particularly tangible.
This data-driven approach also makes it possible to establish more relevant security key performance indicators (KPIs) and track their evolution over time, ensuring agile and scalable management of the prevention strategy.
Non-intrusive security: protecting assets without harming the customer experience
One of the major strengths of intelligent detection solutions lies in their non-intrusive nature. Unlike intrusive methods, such as bag searches or the insistent presence of agents in the aisles, gesture analysis technology works without bothering customers. It strengthens security without harming the atmosphere of the store. In the most advanced approaches, video analysis is performed in high resolution on dedicated GPUs, making it possible to capture details that low-resolution solutions simply cannot distinguish, a decisive factor for detection reliability.
For retail chains that rely on customer loyalty, this is a major competitive advantage. By protecting assets without compromising the shopping experience, the solution avoids tension and inconvenience for customers, while continuously analyzing at-risk gestures. The combination of artificial intelligence and security agents makes it possible to pair the speed of AI detection with human judgment for an appropriate response.
In short, security becomes a non-intrusive yet essential component of the customer journey, supporting brand image and contributing to a calm atmosphere across the entire store network.
Towards an agile and measurable loss prevention strategy
Executives leading store networks know that it is no longer enough to react: they must anticipate. By integrating an AI-based at-risk gesture detection solution, they equip themselves with a strategic tool capable of evolving their loss management model towards greater precision, agility and intelligence. Speed matters: the highest-performing solutions, such as Oxania's, automatically send the alert less than 10 seconds after an at-risk gesture is detected, with no human intervention: a decisive advantage that allows field teams to react at the right moment.
The combination of computer vision expertise and a fine-grained understanding of retail challenges makes it possible to offer solutions calibrated for the complex environments of supermarkets, pharmacies and DIY stores. Easily integrated with existing cameras, these technologies adapt to the specific needs of each retail brand while delivering measurable results. According to research by the ECR Retail Loss Group, in-store losses have increased by a third on average compared with pre-pandemic levels, a finding that makes adopting these tools all the more urgent.
At-risk gesture detection technology thus becomes a true accelerator of operational performance, a valuable asset for streamlining resources, improving customer satisfaction and securing revenue over the long term.
