Blog Retail Reinvented: Using AI To Drive ROI
By Mark Kilgore / 19 Feb 2025 / Topics: Analytics Computer vision
By Mark Kilgore / 19 Feb 2025 / Topics: Analytics Computer vision
Shrink remains a critical concern for retailers, costing the industry $112.1 billion annually. A recent surge in theft is exacerbating retail shrink, now accounting for 65% of total shrink and representing the largest contributor to losses.
Additionally, retail job vacancies remain high due to factors such as high turnover rates, seasonal demand, and broader labor market constraints in service industries. Talent churn continues to plague the industry, with turnover rates remaining high year after year. Delivering robust service to customers becomes even more challenging when staff leave for higher pay or due to job dissatisfaction. Together, these challenges significantly impact associate experience — leading to understaffed stores, lost productivity, and degraded customer experience.
Fortunately, AI lets retailers do more with the infrastructure and people they have in place today. With help from AI, retailers have the power to augment and support their existing staff by introducing new intelligence into their operations and workflows. Many stores already have a powerful asset at their disposal: in-store cameras. AI-enabled computer vision can analyze video from these security cameras and initiate appropriate actions to improve loss prevention, reduce costs, intelligently manage inventory to avoid stockouts, and strategically place merchandise and staff to enhance sales.
Incorporating AI into your existing in-store camera infrastructure can act as the ‘central nervous system’ of the in-store experience, detecting certain incidents that happen in the store — whether that’s theft, low stock of a particular item, or underutilized space given customer traffic patterns. All image processing happens on a small appliance thanks to edge technologies, which means less latency and more security. By connecting to core retail workloads — such as Point of Sale (POS) or merchandising — in the cloud and on premises, AI-enabled cameras deliver store-level analytics that continually enhance the consumer and associate experience, reduce operational costs, and increase sales.
There are a variety of AI use cases retailers might pursue spanning shrink, slip and fall, and inventory optimization — to name just a few. Rather than tackling multiple use cases at once, retailers can start with a single use case and build upon it. The benefits of the first use case typically fund the deployment of the digital platform across the store footprint. For example, if a 500-store retailer begins its AI journey with the goal of improving loss prevention, a mere 30 Basis Point (BPS) improvement in shrinkage could generate roughly $3M in annual cost savings. Using those cost savings, the retailer can then fund additional use cases.
For a 500-store chain, a fully integrated in-store AI computer vision solution has the potential to deliver:
Insight can help you use AI to drive ROI for your retail business through cost reduction and improved customer experiences. We start with a discovery workshop to identify the AI use cases that will drive the most impact for your business. By piloting an initial use case, we then help you prove ROI and build out subsequent use cases. To do this, we partner with innovative software and hardware providers and our experts deliver everything from solution architecture and installation to configuration and solution management.
Managing Director, Insight
Mark is a managing director and retail practice lead at Insight, bringing a wealth of retail industry expertise to his role. Leveraging his deep industry knowledge and collaborative approach, he strengthens the alignment of Insight's capabilities to our clients' needs — resulting in measurable improvement in business outcomes, better financial performance, and strengthened competitive position for our retail clients.