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Report
Artificial Intelligence In Retail Market - Growth, Trends, Covid-19 Impact, and Forecasts (2023 - 2028)
Market Report I 2023-01-23 I 120 Pages I Mordor Intelligence
The global artificial intelligence in retail market is expected to register a CAGR of 35% in the forecast period (2021 - 2026).
The COVID-19 outbreak has accelerated the significance of online shopping channels, as consumers are considering online platforms as their primary shopping channel. This has given retailers and consumer good organizations a great opportunity to adopt sustainability initiatives that integrate with their digital presence. Therefore, retailers are using the e-commerce platform and online marketplaces to capitalize on this changing trend.
Key Highlights
Artificial Intelligence is driving faster business decisions in marketing, e-commerce, product management, and other business areas by decreasing the gap from insights to action. According to the United States Department of Commerce, retail sales in the United States are expected to reach USD 5.99 trillion in 2023.
Machine learning and deep learning technologies are majorly used technologies for AI. Organizations in the retail industry use machine learning and deep learning technology to offer a more personalized experience to the end-users and provide an interactive environment for them.
According to a study by IBM Corporation, the adoption of AI in retail and consumer products industries is expected to leap from 40% of companies currently to more than 80% in three years. Additionally, investment in artificial intelligence (AI) technology by the retail industry is growing. In addition, a study by Juniper, global retail spending on AI would reach USD 7.3 billion annually by 2022, up from a predicted USD 2 billion in 2018. Investments in AI-powered predictive and prescriptive analytics would more than double in that time frame.
However, a reluctance to adopt technological developments is expected to slow down the market growth. Also, a lack of a skilled workforce to adopt the integration of AI in retail is hindering market growth.
Artificial Intelligence in Retail Market Trends
Product Optimization Segment is Expected to Hold Significant Share
Product recommendation and planning will be the growing area for AI in the retail sector. The advancement in Big Data analytics will drive the growing adoption of artificial-enabled devices and services across different industrial domains and verticals.
There is a range of different technologies involved in AI and Big Data, including machine learning, natural language processing, deep learning, and more for automated machine-driven decisions.
According to the Consumer Technology Association, AI has different benefits in the retail industry like cost-saving, increased productivity, faster resolution of business problems, faster delivery of new products and services, increase in innovation which is rapidly making its way into many advanced solutions, including autonomous vehicles, smart bots, advanced predictive analytics, in the retail space. This factor is expected to improve customer analytics and behavior experience raising the significance of product optimization.
In February 2020, Baker Hughes and C3.ai has announced the launch of BH3 Production Optimization, an AI-based application that allows well operators to view real-time production data, better project future production, and help optimize operations for improved oil and gas production rates.
North America Accounts for the Largest Share
North America is expected to dominate the market with the largest market share mainly because of the presence of several developed economies, such as the United States and Canada, focusing on enhancing the existing solutions in the retail space. North America hosts the primary AI solution providers and is an early adopter of AI technology.
Many retailers in this region have deployed AI-based solutions to optimize their supply chain operations and inventory. AI is helping retailers in managing and maintaining their customers and understanding the buying patterns of the consumers. To engage customers and improve sales turnover, AI technologies are being adopted by both online and offline retail businesses.
Many US-based companies like NVIDIA Corporation, Intel Corporation, Salesforce, Sentient Technologies, Microsoft Corporation, Google Inc., IBM Corporation, Amazon Web Services, are extensively involving themselves in product innovation and optimization.
For instance, in April 2020, Kenco Logistics, North America's third-party logistics provider, has announced the introduction of DaVinci AI, a product that provides advanced analytics capabilities spanning the entire supply chain. This innovative product enables solutions to produce predictive insights that drive prescriptive actions, transforming the supply chain.
In August 2020, Mastercard has announced a new suite of frictionless solutions for retailers for their physical shopping experience. Applicable and adaptable to any retail environment from restaurants to pharmacies. Mastercard's AI Powered Drive Through solutions deliver low touch, high engagement experiences for retailers and the end consumer.
Artificial Intelligence in Retail Market Competitor Analysis
Artificial intelligence in the retail market is fragmented. The growing adoption of IoT, Big Data analytics, and e-commerce marketing provide lucrative opportunities for artificial intelligence in the retail market. Overall, the competitive rivalry among existing competitors is high. Moving forward, acquisitions and collaborations of large companies with startups are expected, which are focused on innovation. Some of the key developments in the area are:
October 2020 - SAP SE announced that it is expanding its cloud solutions portfolio, initially launched in June 2020, to the retail industry. The company builds and runs portfolio applications on its open cloud platform, using AI and advanced analytics to support improved user experiences and digitalization and automation of operations. SAP and its partners would deliver solutions for the core business of retailers, like machine learning algorithms, to uncover previously undetected customer needs and create more relevant personalized offers.
January 2020 - European company SAS enhanced its intelligent planning suite with AI and cloud agility to help companies localize assortments, optimize inventory, automate forecasting, and maximize profits.
Additional Benefits:
The market estimate (ME) sheet in Excel format
3 months of analyst support
1 INTRODUCTION
1.1 Study Assumptions and Market Definition
1.2 Scope of the Study
2 RESEARCH METHODOLOGY
3 EXECUTIVE SUMMARY
4 MARKET INSIGHTS
4.1 Market Overview
4.2 Industry Attractiveness - Porter's Five Forces Analysis
4.2.1 Bargaining Power of Suppliers
4.2.2 Bargaining Power of Consumers
4.2.3 Threat of New Entrants
4.2.4 Intensity of Competitive Rivalry
4.2.5 Threat of Substitute Products
4.3 Industry Policies
4.4 Impact of COVID-19 on the Market
5 MARKET DYNAMICS
5.1 Market Drivers
5.1.1 Rapid Adoption of Advances in Technology Across Retail Chain
5.1.2 Emerging Trend of Startups in the Retail Space
5.2 Market Restraints
5.2.1 Lack of Professionals as well as In-House Knowledge for Cultural Readiness
5.3 Market Opportunities
6 AI IN RETAIL MARKET SEGMENTATION
6.1 By Channel
6.1.1 Omnichannel
6.1.2 Brick and Mortar
6.1.3 Pure-play Online Retailers
6.2 By Component
6.2.1 Software
6.2.2 Service (Managed and Professional)
6.3 By Deployment
6.3.1 Cloud
6.3.2 On-Premise
6.4 By Application
6.4.1 Supply Chain and Logistics
6.4.2 Product Optimization
6.4.3 In-Store Navigation
6.4.4 Payment and Pricing Analytics
6.4.5 Inventory Management
6.4.6 Customer Relationship Management (CRM)
6.5 By Technology
6.5.1 Machine Learning
6.5.2 Natural Language Processing
6.5.3 Chatbots
6.5.4 Image and Video Analytics
6.5.5 Swarm Intelligence
6.6 Geography
6.6.1 North America (United States and Canada)
6.6.2 Europe (United Kingdom, Germany, France, and Rest of Europe)
6.6.3 Asia Pacific (China, Japan, India, and Rest of Asia Pacific)
6.6.4 Latin America
6.6.5 Middle East
7 COMPETITIVE LANDSCAPE
7.1 Company Profiles
7.1.1 SAP SE
7.1.2 IBM Corporation
7.1.3 Microsoft Corporation
7.1.4 Google LLC
7.1.5 Salesforce.com Inc.
7.1.6 Oracle Corporation
7.1.7 ViSenze Pte Ltd
7.1.8 Amazon Web Services Inc.
7.1.9 BloomReach, Inc.
7.1.10 Symphony RetailAI
7.1.11 Daisy Intelligence
7.1.12 Conversica Inc.
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