It has been only two years since generative artificial intelligence (AI) burst into our lives. The integration of AI in various business sectors is uneven: there are numerous legal and ethical nuances that concern top managers and experts, making it difficult to fully leverage this technology. However, in some industries, AI is already being utilized extensively today. One such sector is retail. According to McKinsey & Company, AI is increasingly mentioned in the earnings reports of major retailers. This is not surprising: analysts predict that the use of AI in retail operations could add between $240 billion to $390 billion to the industry, equivalent to an increase in sector margins by 1.2–1.9 percentage points.
In 2024, most retailers began actively experimenting with the implementation of AI in their operations. Yet, only a few have managed to unlock the full potential of this technology. After surveying over 50 top executives in the retail sector, McKinsey experts found that most companies are actively piloting and scaling AI-related technologies. Only two leaders can boast of tangible results.
The McKinsey study revealed that many retailers face challenges when implementing generative AI, as this technology requires a fundamental reconfiguration of business processes and workforce principles. Other issues also slow down innovation adoption: the low quality of data available to retailers, privacy risks for customers, a lack of organizational resources, and high costs associated with the full functioning of AI.
Retail companies that have successfully found the right application for generative AI share two characteristics. First, they use this technology only in specific areas of their operations, closely monitoring the changes that AI brings. Second, if they do scale AI implementation, they do so gradually, starting with pilot projects. This approach proves to be effective, according to McKinsey. The pursuit of quick results, on the other hand, often ends in failure.
Retail operations are unpredictable. A vast number of factors that are difficult to track influence commerce. This is why analytics and forecasting in retail are extremely complex tasks. AI has the potential to revolutionize this process: instead of manually analyzing data, employees across the company—from the CEO to the store manager—will be able to utilize ready-made reports generated by AI. This will help them assess the effectiveness of the marketing tools employed by the company.
Consider, for example, an electronics store chain that faced an unexpected decline in TV demand: sales were 6% lower than projected. The company's managers and analysts spent a week searching for the root cause and proposed several theories: it was either the rainy weather, supply chain disruptions for TVs, or a weak advertising campaign. An AI-based system could have helped employees determine the exact cause by analyzing not only the mentioned factors but also additional ones, such as competitors' marketing promotions that may have influenced TV sales. Furthermore, the AI platform could have suggested scenarios for the company's management to resolve the situation.
AI tools, therefore, can become valuable assistants for employees and enhance their productivity. For instance, the Argentine online retailer Mercado Libre uses AI to assist its software developers. By automating routine tasks based on AI, Mercado Libre allows its employees to focus on more engaging and creative work.
In June 2023, the Swedish retailer Lindex announced the implementation of an AI system to support its store employees. The program, which learns from sales data, provides staff with personalized recommendations for store operations and daily task management.
Companies that have successfully integrated AI need to move towards scaling, or they risk falling behind their competitors or losing customers. To do this, they must identify areas that require transformation first. Customer engagement, marketing, and employee productivity—these aspects can all be significantly improved with the help of AI. Of course, the implementation of AI largely depends on the qualifications of technical specialists, but it is essential to train anyone interested in the principles of this technology, whether they are top managers or sales consultants. This will help retain talented employees and unlock the full potential of the new technology. Ultimately, successful AI scaling requires capable employees from various departments of the company who have a clear understanding of why this innovation is necessary for your business.
No matter how talented your employees are, companies will need an external developer specializing in AI technologies. McKinsey experts advise against rushing into selecting a provider—first, it is crucial to understand which one aligns with your company's needs. The quality of the data on which AI is trained is also critical for successful implementation. Therefore, it is extremely important for retailers to systematize data collection and ensure its accuracy, McKinsey concludes.