Please use this identifier to cite or link to this item: http://hdl.handle.net/11718/24796
Title: Innovative disruptions in retail through artificial intelligence
Authors: Naidu, Aishwarya
Goyal, Bhanu
Keywords: Artificial intelligence;Cashier free stores;Boosting sales
Issue Date: 2020
Publisher: Indian Institute of Management Ahmedabad
Abstract: Often companies and entrepreneurs create markets where no customers existed earlier, and traditional business models are shaken up. Most of these disruptions today are occurring with the advent of Artificial intelligence. It is creating seamless experiences in both B2B and B2C transactions. Companies are feeling a growing necessity for monitoring and superior surveillance (Something that ‘Amazon Go’ is trying to do) at physical stores for improved productivity, supply chain optimization, enhanced user experience and better Return on Investments (RoI). The 2017- 2022 market forecast report expects the global artificial intelligence retail market to grow at a CAGR of 38.3%. Customers are seeking customized and personalized services and products, and this is also leading to people shifting rapidly from brick-and-mortar stores to online retailing platforms. With this, artificial intelligence is helping the retailers fulfil the expectations of their customers by aligning their offerings to gain competitive advantage over competitors. In a world where millions of brands and products exist, machine learning retail software is making the customer's way to product search more and more simplified, even if the customer does not know its name or where it is sold. Store operations are becoming more streamlined with reduced inventory losses and hence, automating the store manager’s work by providing efficient backend services. This is further assisting in improving the quality of the products. AI-powered logistics systems are helping to predict demands by using historical data like trends, locations, purchase habits etc. Warehouse management are becoming increasingly efficient with real time database on available inventory.
URI: http://hdl.handle.net/11718/24796
Appears in Collections:Student Projects

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