In the ever-evolving retail landscape, staying ahead of the curve is not just an advantage; it’s a necessity. Businesses are constantly seeking innovative solutions to enhance customer experiences and drive revenue growth. One such innovation that has been gaining significant traction in recent years is generative artificial intelligence (GenAI). By leveraging sophisticated algorithms and vast datasets, generative AI enables retailers to create compelling and personalized experiences for
es for their customers like never before.
From designing bespoke products to crafting targeted marketing campaigns, the potential applications of generative AI in retail are limitless.
Recent examples
Recently, companies like Walmart, Lowe’s and Ikea have rolled out solutions that incorporate generative AI with other new technologies like augmented reality (AR).
In the case of Walmart, customers can now use a virtual try-on feature to purchase prescription eyewear online through the Walmart app or directly on Walmart.com, while Lowe’s ‘Style Studio’ designed exclusively for Apple Vision Pro takes advantage of
unique capabilities of spatial computing to help customers visualize and design their dream kitchens from the comfort of their own homes.
Ikea on the other hand, has launched a new AI assistant available exclusively on the OpenAI GPT Store.
The tool gives users personalized furniture and decor suggestions based on factors such as room dimensions, personal style, sustainability preferences, budget, functional requirements, and more.
Nuanced perspectives
According to Deepika Giri, associate vice president at IDC, at least 79 per cent of retail organizations believe that GenAI models that leverage their own business data will give them a significant advantage over competitors.
“GenAI being applied for overall customer experience using customer behavior data certainly amplifies the omnichannel customer experience through chatbots, assistants, IVRs (interactive voice response), and online shopping advisors,” she told Inside Retail.
But she went on to say that the efficacy of any AI solution is only as good as the data that powers it.
“Hence, in order to maximize AI potential, any organization must build a robust data value chain across all its business processes, for example, in [the areas of] order to cash or procure to pay,” she said.
According to her, this requires the complete end-to-end integration of business processes like supply chain and procurement so that GenAI can deliver on its full potential. Giri said this is a crucial step for organizations to take in order to become AI-ready.
The bigger picture
According to Anthony Mittelmark, chief technology officer for retail at Fujitsu, the use of generative AI is without doubt the most significant technological advancement shaping the retail industry today.
He said GenAI is being used to create content at new levels of speed for products, merchandising and advertising.
“We’re also seeing brands use this to drive hyper personalization. There is also a growing use of AI for voice ordering and other functions aimed at improving customer experience and efficiency,” he told Inside Retail.
Mittelmark expects retailers to adopt more in-store technology that employs Internet of Things (IoT) devices to support sales and provide personalized customer experiences, including cameras, sensors, fixtures, p-of-sale screens and smart carts.
Nonetheless, before retailers can maximize the potential of any data, he said, they must critically understand if they are ready to leverage the data to provide better and more personalized experiences.
“For example, the data needs to be structured in a way that can be easily accessed and analyzed. From here, retailers may identify that they need to buy and access other forms of data to augment the existing data they have to provide a more competitive and personalized experience,” he added.
The future
Mittelmark believes that AI will also replace Robotic Process Automation (RPA), enabling retailers to build agents where they can combine multiple tasks into a programmed prompt and allow the agent to execute and approach the tasks as one, singular task.
“From a wider business perspective, AI provides real-time responses, finds gaps, and uncovers data patterns, which ultimately drives better insights-based strategy and decision-making,” he noted.
Eventually, he thinks AI will manage customer service, oversee stock levels, and examine trends and customer behaviors at a much greater scale than we’re seeing now.
Mittelmark does have some advice for retailers.
He believes that to embrace AI within their business, retailers need to clearly articulate the problems they want to solve and the opportunities they want to unlock and support this with the metrics that drive either resolution or success.
“Retailers need to start with the question: why? They shouldn’t be simply jumping on the bandwagon because it’s the trend. The ‘why’ needs to focus on improving consumer experience and employee experience,” he pointed out.
He also said that ‘proof of concepts’ should be tested before real-world execution, to ensure the AI-technology/solutions can actually deliver the outcomes they are expecting.
“While it might seem counterintuitive, retailers shouldn’t feel pushed to own everything in their technology stack. However, they do need to be thorough and strategic in all stages of procurement,” he said.