INTERVIEW Predict, stock and succeed Kyndryl’s Kayla Broussard explains how AI helps retailers to analyse customer buying habits and improve inventory management, and shares her tips for easily adopting the technology Over 70 per cent of customers expect personalised services from retailers, according to McKinsey & Company. Furthermore, 76 per cent report feeling frustrated when their experiences lack a personal touch. The key to meeting these expectations lies in leveraging artificial intelligence technology. “With AI, retailers can offer a personalised shopping experience with hyper-relevant product recommendations to each customer,” says Kayla Broussard, chief technology officer for retail at Kyndryl. “This is not just about addressing them by name but also understanding their shopping patterns and preferences, which can be as detailed as predicting what products they might need based on past purchases or their size and colour preferences. This level of personalisation significantly enhances customer satisfaction and loyalty, which are key drivers of retail success today.” AI is making an impact across all sectors for retail. For example, AI-powered tools help retailers to plan store layouts by analysing customer traffic patterns from heat maps to ensure that high-demand products are placed in high-traffic areas. Store managers can also monitor stock numbers, analyse purchases and order more products with the help of AI. “One of the revolutionary aspects of AI is its ability to integrate across various points of sale and inventory systems to provide a unified, real-time view of inventory levels,” says Broussard. “This helps retailers to maintain the right amount of stock based on predicted demand, reducing the cost of overstocking. It also allows for predictive restocking, where AI inventory management algorithms forecast when stock will run low and automatically trigger replenishment orders.” Loss prevention is another critical area where AI is driving real change. “Using machine learning models, AI can identify patterns that might indicate fraudulent BY AMBER HICKMAN “ AI systems are only as good as the data they process” 166
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