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America's AI In The Retail Market - Growth, Trends, And Forecast (2020 - 2025)

Published on: Jun 2020 | From USD $3750 | Published By: MORDOR INTELLIGENCE | Number Of Pages: 120

America's AI in the retail market is expected to register a CAGR of 30% during the forecast period, 2020-2025. Artificial intelligence (AI) is driving faster business decisions in marketing, e-commerce, product management, and other areas of the business 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.

- 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.
- Machine learning and deep learning technologies are expected to have the most significant market shares, 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. According to a study by IBM, the adoption of AI in the retail and consumer products industries is projected to leap from 40% of companies today to more than 80% in three years.
- The use of artificial intelligence in retail spans across 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 modelling and micro-targeting or pricing, AI can help meet these challenges in the retail space.
- The retailers in the United States are adopting AI for security and efficiency in the store. The security breaches in stealing the consumer data are growing in the region, thus pushing the companies to use AI as the solutions. For instance, in 2019, Adidas confirmed unauthorized third party access to customer data on the United States website.
- According to SOTI, online retail sales in the United States is projected to surpass USD 740 billion in 2023 as people in the region are more comfortable using an alternative delivery option of goods. Thus, AI plays a crucial role in shaping online retail sales in the country by streamlining the processes.
- Latin America is slowly adopting the AI in retail due to different countries having different taxation systems, even between countries in the same regionAmerica's AI in the retail market is expected to register a CAGR of 30% during the forecast period, 2020-2025. Artificial intelligence (AI) is driving faster business decisions in marketing, e-commerce, product management, and other areas of the business 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.
- 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.
- Machine learning and deep learning technologies are expected to have the most significant market shares 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. According to a study by IBM, the adoption of AI in the retail and consumer products industries is projected to leap from 40% of companies today to more than 80% in three years.
- The use of artificial intelligence in the retail sector spans across 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 challenges in the retail space.
- The retailers in the United States are adopting AI for security and efficiency in the store. The security breaches in stealing the consumer data are growing in the region, thus pushing the companies to use AI as the solutions. For instance, in 2019, Adidas confirmed unauthorized third party access to customer data on the United States website.
- According to SOTI, online retail sales in the United States is projected to surpass USD 740 billion in 2023 as people in the region are more comfortable using an alternative delivery option of goods. Thus, AI plays a crucial role in shaping online retail sales in the country by streamlining the processes.
- Latin America is slowly adopting AI in retail due to varying taxation systems, even between countries belonging to the same region that is often fraught with duties. Additionally, the slow adoption of smartphones is posing a hurdle for companies to penetrate with AI in the retail ecosystem. According to GSMA, the mobile penetration rate in Latin America was only 67%, in 2018.
- With the recent outburst of COVID-19, the retail industry is facing significant supply chain disruption in the region and other problems. However, the usage of AI can help deliver goods to the customer by making a centralized AI unit that stores all the data about demand generation. It can also use a drone that uses the AI algorithm to deliver the most vital and essential supplies, such as medicine and protective gear, among others, to the consumer. are often fraught with duties, and slow adoption of smartphones are making difficulties for companies to penetrate with AI in the retail ecosystem. According to GSMA, the mobile penetration rate in Latin America was only 67% in 2018.
- With recent outburst of COVID-19, the retail industry is facing significant supply chain disruption in the region and other problems. But using the technology of AI, it can deliver the goods to the customer, by making a centralized AI unit that stores all the data pertaining to demand generation and can use a drone that uses AI algorithm to deliver the most vital and essential supplies such as medicine and protective gears and others to the consumer.

Key Market Trends

Machine Learning Technology is Expected to Grow Siginificantly

- Machine learning is one of the key technologies that is expected to create value for retailers as more and more businesses take advantage of Big Data. Retail companies are using advanced analytics to get insights into consumers buying behavior. Additionally, it also helps retailers in merchandise planning and size optimization.
- Moreover, AI is revolutionizing shopping experiences by making them more personalized, efficient, fruitful, and relevant. Amazon introduced the Amazon 4-star retail store that will showcase 4-star products rated based on its product recommendation engine that identifies trending products and customer's favorites.
- According to IBM, 62% (global) of retailers reported that the use of information (Big Data and analytics) is providing an edge for their organizations. Such non-relational databases are ideal for real-time applications that generate huge amounts of data, making them suitable for deploying machine learning algorithms.
- The US-based Prism Skylabs offers solution for retail outlets, that use the data from their existing surveillance cameras and use predictive analytics to enhance merchandising, store design, and inventory management. Camera data feeds into an algorithm which can, for example, analyze how customers move around the space to help retailers optimize the layout of their store, ensuring the best chance of making sales. The tool is ideal for small and medium enterprises.
- In the Latin American region, AI is expected to be one of the major enablers of retail businesses given the rapid proliferation of mobile networks and expansion of research capabilities in AI in the region. Santiago-based startup Arara has been working on building AI solution for diverse retail business cases. The company has been able to raise USD 500,000 in funding and has promised to develop solutions that will increase sales by 30% by predicting purchase intentions.

Food and Grocery to Augment Significant Growth

- AI in the food and grocery retail market helps in the pricing and promotion of the products in the store. For instance, Harps Foods in Springdale, Ark., has been working with Daisy Intelligence, to improve pricing and promotions in its circular. Daisy analyzed two years of transactional information and pricing from Harps, with the goal of growing the retailerís sales by 3%.
- Many foods and grocery retailers in the region have deployed AI-based solutions to optimize its supply chain operations and inventory. AI is helping the retailers in maintaining and managing their customers and understanding the buying patterns of them. AI technologies are adopted by both online and offline retail businesses to engage customers and improve sales turnover. For instance, Fresh Thyme, a grocery retailer in the region, adopted the technology for its 75 retail locations uses AI to fix the fresh supply chain of foods.
- In April 2019, Walmart unveiled a new store for the future that includes AI-enabled cameras and interactive displays, a concept called Intelligent Retail Lab in the Walmart market in Levittown, New York. The AI-enabled cameras monitor's inventory levels to determine, if staff needs to bring out meat from the back-room refrigerators to re-stock the shelves, or if some items are sitting too long on the shelf and need to be pulled out.
- Moreover, AI is helping food retailers with personal advertisement promotion by using the loyalty program to build up database of a consumerís purchases over time. AI leverage the data to understand, which product to promote to get the customer to store.

Competitive Landscape

The market for America's AI in retail is consolidated due to the presence of a few companies offering the solutions. The major players in the market are Microsoft Inc., SAP SE, Amazon Web Services Inc., and IBM Corporation, among others. Some of the recent developments by the companies are as follows:

- March 2020 - Amazon.com Inc. announced a new business line to sell its proprietary technology behind its cashier-less convenience stores to other retailers. The highly anticipated business further underscores Amazonís strategy of building internal capabilities Ė like warehouses to help with package delivery and cloud technology to support its website - and then turning these into service offerings for others.
- January 2020 - SAS has enhanced its intelligent planning suite with AI and cloud agility to help companies localize assortments, optimize inventory, automate forecasting, and maximize profits. Leading companies, such as Carrefour and Nestle, rely on analytics leader SAS, and its proven portfolio of software and services to succeed despite fierce competition.
- December 2019 - The AWS Partner Network introduced the AWS Retail Competency that is expected to help retailers find top APN Partners with highly specialized solutions and consulting practices powered and vetted by AWS. The AWS Retail Competency validates industry leaders with proven customer success and technical proficiency in services, like artificial intelligence (AI), machine learning (ML), voice, Internet of Things (IoT), visual recognition, robotics, and more.

Reasons to Purchase this report:

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1 INTRODUCTION
1.1 Study Deliverables
1.2 Study Assumptions
1.3 Scope of the Study

2 RESEARCH METHODOLOGY

3 EXECUTIVE SUMMARY

4 MARKET DYNAMICS
4.1 Market Overview
4.2 Market Drivers
4.2.1 Hardware Advancement Acting as a Key Enabler for AI in Retail
4.2.2 Disruptive Developments in Retail, including AR, VR, IOT, and New Metrics
4.2.3 Rise of AI First Organizations
4.2.4 Need for Efficiency in Supply Chain Optimization
4.3 Market Restraints
4.3.1 Lack of Professionals, as well as In-house Knowledge for Cultural Readiness
4.4 Industry Value Chain Analysis
4.5 Porter's Five Forces Analysis
4.5.1 Threat of New Entrants
4.5.2 Bargaining Power of Buyers/Consumers
4.5.3 Bargaining Power of Suppliers
4.5.4 Threat of Substitute Products
4.5.5 Intensity of Competitive Rivalry
4.6 Industry Policies
4.7 Assessment of Impact of COVID-19 on the Industry

5 AI Adoption in the Retail Industry
5.1 AI Penetration with Retailers (Historical, Current, and Forecast)
5.2 AI penetration by Retailer Size (Large and Medium)
5.3 AI Use Cases in Operations
5.3.1 Logistics and Distribution
5.3.2 Planning and Procurement
5.3.3 Production
5.3.4 In-store Operations
5.3.5 Sales and Marketing
5.4 AI Retail Startups (Equity Funding vs Equity Deals)
5.5 Road Ahead for AI in Retail

6 MARKET SEGMENTATION
6.1 Channel
6.1.1 Omnichannel
6.1.2 Brick and Mortar
6.1.3 Pure-play Online Retailers
6.2 Solution
6.2.1 Software
6.2.1.1 On Premise
6.2.1.2 Cloud
6.2.2 Service
6.3 Application
6.3.1 Apparel and Footwear
6.3.2 Food and Grocery
6.3.3 Electronics and Home Appliances
6.3.4 Home Improvement
6.3.5 Other Applications
6.4 Technology
6.4.1 Machine Learning
6.4.2 Natural Language Processing
6.4.3 Chatbots
6.4.4 Image and Video Analytics
6.4.5 Swarm Intelligence

7 COMPETITIVE LANDSCAPE
7.1 Company Profiles
7.1.1 Amazon Web Services Inc.
7.1.2 Microsoft Corporation
7.1.3 SAP SE
7.1.4 Google LLC
7.1.5 IBM Corporation
7.1.6 Salesforce.com Inc.
7.1.7 Oracle Corporation
7.1.8 ViSenze Pte Ltd
7.1.9 Sentient Technologies Holdings Limited
7.1.10 Sophos Inc. (Thoma Bravo)

8 INVESTMENT ANALYSIS

9 MARKET TRENDS AND FUTURE OPPORTUNITIES

SECONDARY RESEARCH
Secondary Research Information is collected from a number of publicly available as well as paid databases. Public sources involve publications by different associations and governments, annual reports and statements of companies, white papers and research publications by recognized industry experts and renowned academia etc. Paid data sources include third party authentic industry databases.

PRIMARY RESEARCH
Once data collection is done through secondary research, primary interviews are conducted with different stakeholders across the value chain like manufacturers, distributors, ingredient/input suppliers, end customers and other key opinion leaders of the industry. Primary research is used both to validate the data points obtained from secondary research and to fill in the data gaps after secondary research.

MARKET ENGINEERING
The market engineering phase involves analyzing the data collected, market breakdown and forecasting. Macroeconomic indicators and bottom-up and top-down approaches are used to arrive at a complete set of data points that give way to valuable qualitative and quantitative insights. Each data point is verified by the process of data triangulation to validate the numbers and arrive at close estimates.

EXPERT VALIDATION
The market engineered data is verified and validated by a number of experts, both in-house and external.

REPORT WRITING/ PRESENTATION
After the data is curated by the mentioned highly sophisticated process, the analysts begin to write the report. Garnering insights from data and forecasts, insights are drawn to visualize the entire ecosystem in a single report.

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