The use of Artificial Intelligence (AI) in retail offers intelligent solutions that are leading a digital transformation in the retail industry, with a focus on enhancing customer experience. The thriving e-commerce sector and dynamic shift in shopping patterns and customer preferences are projected to drive the demand for artificial intelligence in retail during the forecast period, 2019–2026.
AI provides an opportunistic approach towards bridging the gap between virtual and physical sales channels. For instance, ‘Pepper’, the world’s first personal robot developed by the French company Aldebaran Robotics, can interact with customers and understand human emotions. Developments such as these underline companies’ efforts towards enhancing brand engagement. In 2016, Pepper partnered with b8ta to enhance brand engagement and drive traffic and sales as a dynamic in-store brand ambassador. The partnership yielded a 70% increase in foot traffic, offering a futuristic approach towards front-end experience in retail locations.
Prevalence of Online Shopping & Burgeoning e-Commerce Sector to Drive Growth of Online Segment
On the basis of type, the AI in retail market is segmented into online and offline. The flourishing e-commerce sector is bolstering the online segment’s market share by driving online shopping. The online segment is expected to hold the largest market share throughout the forecast period. Based on component, the market can be segmented into solutions and services. Intensifying competition in the marketplace and the subsequent implementation of strategies by players to strengthen their market presence are expected to drive the demand for AI-powered solutions and services in retail.
Automated Merchandising Solutions and In-Store Visual Monitoring and Surveillance to Gain Prominence in the Coming Years
By technology, Artificial Intelligence (AI) in retail market can be segmented into machine learning, natural language processing, analytics, and others. The rising demand for predictive analysis, machine learning, deep learning, and others are expected to influence market growth positively in the coming years. On the basis of application, the AI in retail market can be segmented into predictive merchandising, programmatic advertising, in-store visual monitoring and surveillance, and others. Automated merchandising solutions and in-store visual monitoring and surveillance are likely to register the most significant growth during the forecast period.
Google & IBM, Among Other Technology Giants, to Drive Market Growth in North America
North America is expected to witness dynamic growth in the artificial intelligence in retail market during the forecast period, 2019–2026. Early adoption of advanced technologies and the presence of technology giants such as Google and IBM, which are investing in AI are expected to provide impetus to market growth in the region. In March 2019, McDonald’s acquired Dynamic Yield to offer customers a better in-store and remote personalization experience, building significant technology investments for growth.
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Asia-Pacific to Surpass Europe with Transformative Changes Disrupting Traditional Business Models
As per recent studies, Asia-Pacific is expected to surpass Europe as the disruption of traditional business models across the retail industry has offered transformative changes for shopping online or offline to redefine customer experience. Retailers in countries such as China, Japan, and the rest of Asia-Pacific are gaining traction from emerging markets of the Middle East and Africa. With technological advancements crossing borders, LAMEA’s AI in retail market is expected to witness a marked improvement in adoption during the forecast period.
Some of the key players in the global artificial intelligence in retail market are Accenture, Amazon Web Services Inc., Google LLC, Infosys Limited, Intel Corporation, IBM Corporation, Microsoft Corporation, Numenta Inc., NVIDIA Corporation, Oracle Corporation, Salesforce.com Inc., SAP SE, Sentient Technologies, and ViSenze Pte Ltd.
Artificial Intelligence in Retail Market Segmentation
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