Early AI adoption help the incumbents and new entrants thrive in the perpetually competitive retail context
Factory 4.0 concept: Collaboration of industrial robots in smart warehouse. (Representational image)
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While technology adoption was trickling in at a snail-like pace over the years, the post-COVID 19 retail world has witnessed a massive AI disruption as more and more businesses (both offline and online) are ramping up AI automation to tap consumers’ changing shopping patterns. Customers are increasingly looking for personalized, hassle-free shopping experiences; global retailers are hence on the edge of perpetual AI integration to align their products/services with customer preferences or expectations. Having surpassed 2 billion US Dollars in 2020, the AI in Retail Market size is anticipated to rise at “more than 30% CAGR between 2021 and 2027,” reports Global Market Insights.
Retailers can use AI tools and solutions to collect and analyze data on sales, demographics, consumer behavior, etc., to automate product prices, manage pricing strategies, and offer personalized recommendations. Recent research suggests the undeniable importance of AI in increasing online, in-store, mobile, and omnichannel sales, managing and enhancing in-store and digital experiences, improving customer service, payments, logistics services, and optimizing supply-chain and operational efficiency. Though AI paves the way for a promising future, many traditional and online retailers have failed to keep pace with the ever-upgrading emerging tech adoption. In this article, the authors suggest a few operational areas that call for early AI adoption, along with example use-cases, to help the incumbents and new entrants thrive in the perpetually competitive retail context.
For example, Japanese clothing brand Uniqlo launched its UMood campaign in Australia that used neuroscience to offer customized clothing recommendations to its customers. First, the company used technology-enabled headsets to capture the buyer’s neurological responses. Then, AI is used to analyze these responses and match a buyer’s mood to perfect clothing.
[This article has been reproduced with permission from the Indian School of Business, India]