How Generative AI can transform the Retail Industry

Retailers can leverage Gen AI for tasks like product research, customer service, and supply chain management.

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The retail sector often leads in adopting advanced technology to drive up shoppers’ experience while bringing higher efficiency and productivity. Sophisticated technologies like virtual trials, self-checkouts, image analytics at the shelf, supply chain control towers, and computer-assisted ordering models, etc have always been key topics in retail discussions. This trend is largely driven by the widespread adoption of AI (Artificial Intelligence), ML (Machine Learning), and data analytics in the industry; a movement that Generative AI will only accelerate. 


According to a Google Cloud survey, around 72 per cent of retail decision-makers are ready to implement GenAI technologies in 2024. With Generative AI, retailers can move beyond traditional data analysis, tapping into vast amounts of unstructured data—from social media interactions and online customer reviews to in-store video analytics. This shift allows them to uncover deep insights into consumer behaviour, preferences, and market trends that were previously limited. With such unending potential, Gen AI could elevate the retail sector’s profitability by 20%. In fact, some of these initiatives are already under several stages of implementation.

Innovative cost savings & enhanced efficiencies

Knowledge task automation is the most tangible benefit of Gen AI that retailers can derive immediately. For instance, retail is a consumer-facing business that requires deep research and understanding of the product, consumers, and the competition. The use of Gen AI for product research assistance and competitive insights is on the rise. Moreover, content creation tasks related to communications & marketing are rapidly being re-shaped by Gen AI tools. It also throws open potential use cases for consumer-facing activities. For instance, the use of Gen AI-powered chatbots can ensure a better customer experience through removal of the language constraints while enabling users to converse with these chat assistants in a very human way. Solutions like Carrefour’s ‘Hopla’ and Macy’s ‘On Call’ show that customers’ interactions with brands have been enriched through AI tools. So, leveraging Gen AI tools, many human resources can be freed for other critical work, leading to cost savings.


A faster & better way to consumer experience & insights

Gen AI tools like ChatGPT can enhance consumer support to the next level by responding to queries, explaining products, offering product recommendations, showing multiple options, and more. Even Gen AI’s ability to do visual searches with high precision can enhance sales from online stores. Take the case of Walmart. The retail giant leverages GenAI to better understand consumer intent basis the query, and the consumer engagement with its items. Walmart then attempts to create a product recommendation basket that follows the ‘Mutually exclusive, collectively exhaustive (MECE)’ principle and collectively attempts to address all potential consumer needs. Similarly, World’s largest coffeehouse chain, Starbucks has been leveraging AI-powered algorithms to serve customers through personalised product recommendations, faster serving time & better experience for many years. Gen AI can take this ability to a greater depth because of its ability to crunch vast amounts of data and provide insights in real time. Fashion and apparel retailers are attempting to drive Gen AI into the very core of their product design and development process, attempting to bring down the time to market on new products. Gen AI in such cases is enabling faster ideation, faster insights into trends and fads, and helping drive faster content creation and finalization through the product design life cycle.

Better demand forecasting


Generative AI can change the game in demand forecasting - a key component of retail strategy. Retailers have long struggled with accurately predicting demand due to causal and event-driven factors. But Generative AI can augment traditional models, which typically rely on large volumes of historical sales data, by incorporating a variety of other factors, including weather, holidays, and social media trends, into its analysis. The ability of Generative AI to draw patterns from vast amounts of unstructured data could be an asset in not just better predictions but also helping enterprises adopt more dynamic pricing strategies. In short, Generative AI offers a powerful boost to understand and meet consumer demand.

Optimising supply chain through better risk management:

Efficient responses to market signals and quick time to recover in the face of operational disruptions are key capabilities that define an agile and responsive supply chain. Gen AI can score over traditional methods of supply chain operations through faster identification of market signals and risk events and quickly create efficient response protocols for the same. Gen AI can also help quickly analyze the historical efficacy of responses in the face of a black swan event or a sudden surge in demand and assist in framing response recommendations. 


While leveraging Gen AI, retailers can transform their operations for the better. However, they need to be careful about designing the platform. Due to the newness of the technology, a certain degree of anomalies can’t be ruled out from current Gen AI models. To avoid such instances, retailers are better off collaborating with experienced technology players. 

The interest around Gen AI technology and its experimentation are on a rise. But the world is at an early stage of realising its true potential. Nevertheless, retail industry is at the forefront of driving its adoption. An EY survey shows 71% of retailers in India plan to adopt AI in the next 12 months, and a big part of such adoption is likely to be in the Gen AI space. So, the retail industry is on the verge of a transformative era in the coming years.

By Sandeep Kumar, SVP and Head, Business Consulting, ITC Infotech