Product Code: 62327
The Artificial Intelligence in Retail Market was valued at USD 1.80 billion in 2019 and is expected to reach USD 10.90 billion by 2025, at a CAGR of 35% over the forecast period 2020 - 2025. AI will drive faster business decisions in marketing, e-commerce, product management and other areas of the business by decreasing the gap from insights to action.
- The machine learning and deep learning technologies are expected to have the most significant market share during the forecast period. Organizations in the retail industry are using machine learning and deep learning technology to offer a more personalized experience to the end users as well as to provide an interactive environment to them. Moreover, the growing trend of rising technology adoption can be associated with the need for streamlining retail operations, minimizing efforts, and increasing revenue mostly for e-commerce retailers.
- The use of artificial intelligence in retail spans every aspect of the industry. Whether the goal is to optimize the supply chain, use existing data to increase conversion, or customize shopping experiences with predictive modeling and micro-targeting or pricing, AI can help meet these challenge in the retail space.
- The AI equipped retailers with sharper forecasting tools will help in making smarter business decisions. The use of algorithms increases visibility into ROI implications, translating to results like lower costs and higher sales. AI has brought real disruption to the retail sector by improving efficiency, as well as prediction.
Scope of the Report
The application of artificial intelligence (AI), big data and analytics will push the business access towards a data-driven model by expanding the types of data that can be analyzed, and raise the level of sophistication of the resulting insight. The Artificial Intelligence in retail market is being divided as software, services with different applications like supply chain & logistics, product optimization, in-store navigation, payment & pricing analytics, inventory management, customer relationship management. All these applications are being deployed either in the cloud or on-premise.
Key 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 the automated machine-driven decisions.
- According to 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 significance of product optimization.
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 the 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 the product innovation and optimization.
- For instance, in April 2019, Warby Parker, an US-based company practices an innovative way. By the use of Artificial intelligence, it's providing its customer to try the virtual Try-On that allows them to try on virtual frames through augmented reality, a technology that overlays computer-generated images (frames) onto real-world images (your face).
The artificial intelligence in retail market is fragmented. The growing adoption of IoT, big data analytics, e-commerce marketing, provide lucrative opportunities in artificial intelligence in retail market. Overall, the competitive rivalry among existing competitors is high. Moving forward, acquisitions and collaboration of large companies with startups are expected, which are focused toward innovation. Some of the key developments in the area are:
- May 2019 - SAP SE announced a series of innovations to SAP S/4HANA to make it easier to add artificial intelligence (AI) and robotics, and to customize apps. This will help companies improve business results, automate business processes and make accurate predictions for better decisions.
- April 2019 - Amazon Web Services, Inc. allows developers to create applications that speak in Arabic and build speech-enabled products and services, including cars, internet of things devices, appliances, automated contact centers, language learning platforms, translation apps, and newsreaders. The artificial intelligence-powered Polly uses deep-learning technologies to synthesize speech that sounds like a human voice.
Reasons to Purchase this report:
- The market estimate (ME) sheet in Excel format
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Table of Contents
- 1.1 Study Deliverables
- 1.2 Study Assumptions
- 1.3 Scope of the Study
2 RESEARCH METHODOLOGY
3 EXECUTIVE SUMMARY
4 MARKET INSIGHT
- 4.1 Market Overview
- 4.2 Industry Attractiveness - Porter's Five Force Analysis
- 4.2.1 Threat of New Entrants
- 4.2.2 Bargaining Power of Buyers/Consumers
- 4.2.3 Bargaining Power of Suppliers
- 4.2.4 Threat of Substitute Products
- 4.2.5 Intensity of Competitive Rivalry
- 4.3 Value Chain / Supply Chain Analysis
- 4.4 Industry Policies
- 4.5 Technology Snapshot
- 4.5.1 Machine Learning
- 4.5.2 Deep Learning
- 4.5.3 Neuro-Linguistic Programming
5 MARKET DYNAMICS
- 5.1 Introduction to Market Drivers and Restraints
- 5.2 Market Drivers
- 5.2.1 Rapid Adoption of Advances in Technology Across Retail Chain
- 5.2.2 Emerging Trend of Startups in the Retail Space
- 5.3 Market Restraints
- 5.3.1 Lack of Professionals as well as In-House Knowledge for Cultural Readiness
6 MARKET SEGMENTATION
- 6.1 By Product
- 6.1.1 Software
- 6.1.2 Service
- 18.104.22.168 Managed
- 22.214.171.124 Professional
- 6.2 By Deployment
- 6.2.1 Cloud
- 6.2.2 On-Premise
- 6.3 By Application
- 6.3.1 Supply Chain & Logistics
- 6.3.2 Product Optimization
- 6.3.3 In-Store Navigation
- 6.3.4 Payment & Pricing Analytics
- 6.3.5 Inventory Management
- 6.3.6 Customer Relationship Management (CRM)
- 6.4 Geography
- 6.4.1 North America
- 6.4.2 Europe
- 6.4.3 Asia-Pacific
- 6.4.4 Latin America
- 6.4.5 Middle East & Africa
7 COMPETITIVE LANDSCAPE
- 7.1 Company Profiles
- 7.1.1 Amazon Web Services, Inc.
- 7.1.2 Google LLC
- 7.1.3 Daisy Intelligence
- 7.1.4 IBM Corporation
- 7.1.5 Microsoft Corporation
- 7.1.6 Plexure Ltd.
- 7.1.7 Versium Analytics Inc.
- 7.1.8 Findmine Inc.
- 7.1.9 SAP SE
- 7.1.10 Salesforce.com Inc
- 7.1.11 Conversica Inc.
- 7.1.12 BloomReach Inc.
- 7.1.13 Sentient Technologies Holdings Limited
- 7.1.14 Focal Systems Inc.
- 7.1.15 ViSenze Pte Ltd
8 INVESTMENT ANALYSIS
9 MARKET OPPORTUNITIES AND FUTURE TRENDS