GenAI in Retail

In the rapidly evolving world of digital commerce, technological advancements are constantly reshaping how businesses operate and engage with customers. Generative AI (GenAI) has emerged as one of the most promising innovations, offering a new frontier for enhancing customer experiences, optimizing operations, and driving revenue growth. To gain deeper insights into the impact and potential of GenAI in the retail sector, we spoke with Nurcan Bıçakçı Arcan, Global Chief Marketing Officer at Akinon. In this interview, she shares her perspective on how GenAI is poised to revolutionize digital commerce, its current adoption landscape, and what retailers should consider as they embark on their GenAI journey.

How do you see the role of GenAI in digital commerce? Is it really the next big thing?
Generative AI (GenAI) is a transformative technology with the potential to drive significant innovation and efficiency across various business functions. From a strategic perspective, I see GenAI as a tool to enhance customer experiences, optimise operations, and create new revenue streams. I recognise its ability to personalise marketing efforts, streamline customer service through advanced chatbots, and generate insights from large datasets. These capabilities improve decision-making processes.

In the digital commerce industry, I anticipate GenAI to revolutionise how businesses interact with customers. Enabling hyper-personalised shopping experiences by analysing consumer behaviour and preferences in real-time will add exciting enhancements. Let’s also mention that advanced search capabilities will be one of the very first implementations of GenAI in the commerce industry. These should lead to more relevant product recommendations and tailored marketing campaigns. This personalised approach can increase customer satisfaction and loyalty, ultimately driving higher sales.

I also see GenAI as a means to improve operational efficiency. Automated content and text creation, inventory management, and dynamic pricing adjustments are areas where GenAI can reduce manual effort and enhance accuracy. GenAI can also assist in detecting fraud, analysing market trends, and optimising supply chain logistics.

What about its adoption? Are retailers already utilising the technology or are they just experimenting – or not even at that stage?
Gartner predicts, by 2027, 90% of Tier 1 retailers will successfully execute at least one business-transforming GenAI use case – so in 2 years. For sure, it is on Tier 1 retailers’ agendas. They are trying to identify the best use cases that will provide them with improvements both on customer experience and operational efficiency. They are trying to develop accurate and actionable customer behavior models that would best fit their needs. In parallel, they are working on how they could improve the accuracy and efficiency of their commerce operations in an environment where we see the proliferation of channels which makes it difficult to operate efficiently.

Others are more in the discovery phase. We still have many retailers who are in the transition phase from monolithic platforms to next-gen, composable platforms. Until the technology is mature enough and all their core functions are properly working, they will not be able to – and they shouldn’t –  adapt GenAI models.

What are your recommendations to retailers? What should they consider in their GenAI journey?
First of all I recommend a very close collaboration between technology and business functions to identify their maturity and business needs. The technology needs to be mature enough to start thinking about potential GenAI models. Once the technology is ready, they can start with an ideation process in which they consider revenue generation, profitability, cost-cutting opportunities and risk tolerances. There is no ‘one size fits all’ approach here. One can benefit from a use case whereas the other one needs to implement another use case. So I strongly recommend retailers to focus on their own needs and start small with trials. Gartner predicts likely successful retail use cases will include enhanced search and upselling, social media customer sentiment, supply chain optimization and conversational chat interfaces. However, as I mentioned, every retailer has unique needs and readiness to address these needs with GenAI.