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Market Snapshot

CAGR:5.99

2023

2032

Source: Market Expertz

Study Period	2019-2032
Base Year	2023
Forcast Year	2023-2032
CAGR	5.99

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Report Overview

The Artificial Intelligence (AI) in Retail Market is projected to exhibit robust growth with a Compound Annual Growth Rate (CAGR) of 6.78% between 2022 and 2032. The market's value is anticipated to surge by USD 28,546.92 million during this period. The expansion of the market hinges on various factors, including the increasing adoption of AI-driven technologies in retail operations, the demand for personalized customer experiences, and the need for optimizing supply chain and inventory management. Artificial Intelligence in the retail sector refers to the integration of machine learning, data analytics, and other AI technologies to enhance customer interactions, automate tasks, and gain valuable insights for better decision-making.

Artificial Intelligence in Retail Market Overview:

Drivers:

A pivotal driver propelling the growth of the AI in retail market is the escalating demand for personalized customer experiences. AI technologies enable retailers to analyze vast amounts of customer data, including purchasing history, preferences, and behavior, to offer tailored product recommendations and promotional offers. This personalization enhances customer engagement, loyalty, and ultimately leads to higher sales.

Furthermore, AI-driven technologies enable retailers to optimize their supply chain and inventory management. Predictive analytics and machine learning algorithms assist in demand forecasting, minimizing stockouts, reducing excess inventory, and improving overall operational efficiency. This, in turn, leads to cost savings and improved customer satisfaction.

Trends:

An influential trend shaping the AI in retail market is the integration of AI-powered chatbots and virtual assistants. These AI-driven tools revolutionize customer service by providing instant responses to inquiries, offering product recommendations, and guiding customers through the purchasing process. The 24/7 availability of virtual assistants enhances customer support and engagement, contributing to higher customer satisfaction levels.

Moreover, the adoption of AI in visual merchandising and product placement is gaining momentum. Computer vision algorithms analyze store layout, customer movement, and product interactions to optimize store design and product positioning. This technology ensures that the most relevant products are prominently displayed, leading to increased sales and improved shopping experiences.

Restraints:

Challenges associated with data privacy and security are significant obstacles impeding the AI in retail market's growth. The collection and processing of vast amounts of customer data raise concerns about data breaches and misuse. Retailers need to invest in robust cybersecurity measures and comply with stringent data protection regulations to maintain consumer trust and adhere to legal requirements.

Additionally, the high upfront costs of implementing AI technologies and the need for specialized skill sets are barriers for many retailers. The integration of AI requires significant investment in infrastructure, software, and training, which may deter smaller retailers with limited resources from adopting these technologies.

Artificial Intelligence in Retail Market Segmentation By Application: The application of AI in customer service and engagement is anticipated to witness substantial growth during the forecast period. AI-powered chatbots, virtual assistants, and automated customer support systems are increasingly being adopted by retailers to provide real-time assistance to customers. These technologies enhance response times, resolve queries, and offer personalized recommendations, thereby improving the overall shopping experience.

Furthermore, AI's application in inventory management and demand forecasting is gaining traction. Retailers utilize AI algorithms to analyze historical data, seasonal trends, and external factors to accurately predict demand and optimize inventory levels. This leads to minimized stockouts, reduced overstocking costs, and streamlined supply chain operations.

Artificial Intelligence in Retail Market Segmentation By Type: The surge in demand for AI-powered recommendation systems is fueling the growth of the recommendation engine segment. Retailers leverage recommendation algorithms to analyze customer preferences and browsing history, providing tailored product suggestions to shoppers. These systems enhance cross-selling and upselling opportunities, driving higher sales volumes.

Moreover, AI-driven visual recognition technologies are gaining prominence. These technologies enable retailers to analyze images and videos to extract valuable insights about customer behavior, product interactions, and store layout. Visual recognition enhances product placement strategies and helps retailers understand customer preferences visually.

Regional Overview:

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The Asia-Pacific (APAC) region is expected to contribute significantly to the global AI in retail market's growth, accounting for 38% of the forecasted market expansion. The APAC region's growth is propelled by the presence of key market players such as Alibaba Group, JD.com, and Rakuten. These companies have been at the forefront of AI adoption in the retail sector, employing AI technologies to enhance customer experiences, optimize supply chains, and automate various retail processes.

China, in particular, has been a trailblazer in AI adoption across industries, including retail. The country's robust e-commerce landscape and tech-savvy consumer base provide a fertile ground for AI-driven retail innovations. Furthermore, the increasing penetration of smartphones and internet connectivity in countries like India is driving the adoption of AI-powered mobile commerce solutions.

Artificial Intelligence in Retail Market Customer Landscape: The AI in retail market analysis encompasses the customer adoption journey, ranging from early adopters to late adopters. The report delves into adoption rates across different regions, considering factors that influence penetration. Additionally, key factors driving price sensitivity and purchase decisions are explored to aid companies in refining their growth strategies.

Major Companies in the Artificial Intelligence in Retail Market: Market players are employing various strategies, including partnerships, acquisitions, geographical expansion, product/service launches, and collaborations, to bolster their market presence.

Amazon Web Services Inc.: Offers AI-powered solutions like Amazon Personalize for tailored product recommendations and Amazon Forecast for demand forecasting.
IBM Corporation: Provides AI-driven solutions such as IBM Watson for personalized shopping experiences and inventory optimization.
Salesforce.com Inc.: Offers Salesforce Einstein, an AI-powered platform that assists retailers in customer engagement, marketing, and analytics.
Alibaba Group Holding Limited: Utilizes AI technologies for personalized recommendations, supply chain optimization, and unmanned stores.
NVIDIA Corporation: Provides AI hardware and software solutions for enhancing visual recognition, natural language processing, and data analytics in retail operations.

The market report conducts a comprehensive qualitative and quantitative analysis of key market players, assessing their strengths, weaknesses, and overall business environment. Companies are categorized based on their focus, industry impact, and degree of dominance within the AI in retail market.

Segment Overview:

The artificial intelligence in retail market report forecasts revenue growth at the global, regional, and country levels, offering insights into emerging trends and opportunities from 2019 to 2032.

Application Outlook (USD Million, 2019 - 2032)

Customer Service and Engagement
Inventory Management and Demand Forecasting
Visual Merchandising and Product Placement
Others

Type Outlook (USD Million, 2019 - 2032)

Recommendation Engine
Visual Recognition
Natural Language Processing
Others

Geography Outlook (USD Million, 2019 - 2032)

North America

The U.S.
Canada

Europe

U.K.
Germany
France
Rest of Europe

APAC

China
India

South America

Chile
Argentina
Brazil

Middle East & Africa

Saudi Arabia
South Africa
Rest of the Middle East & Africa

TABLE OF CONTENTS: GLOBAL ARTIFICIAL INTELLIGENCE (AI) IN RETAIL MARKET

Chapter 1. MARKET SYNOPSIS

1.1. Market Definition

1.2. Research Scope & Premise

1.3. Methodology

1.4. Market Estimation Technique

Chapter 2. EXECUTIVE SUMMARY

2.1. Summary Snapshot, 2016 – 2027

Chapter 3. INDICATIVE METRICS

3.1. Macro Indicators

Chapter 4. ARTIFICIAL INTELLIGENCE (AI) IN RETAIL MARKET SEGMENTATION & IMPACT ANALYSIS

4.1. Artificial Intelligence (AI) in Retail Segmentation Analysis

4.2. Industrial Outlook

4.3. Price Trend Analysis

4.4. Regulatory Framework

4.5. Porter’s Five Forces Analysis

4.5.1. Power Of Suppliers

4.5.2. Power Of Buyers

4.5.3. Threat Of Substitutes

4.5.4. Threat Of New Entrants

4.5.5. Competitive Rivalry

Chapter 5. ARTIFICIAL INTELLIGENCE (AI) IN RETAIL MARKET BY Type INSIGHTS & TRENDS

5.1. Segment 1 Dynamics & Market Share, 2019 & 2027

5.2. Online Retail

5.2.1. Market Estimates And Forecast, 2016 – 2027 (USD Million)

5.2.2. Market Estimates And Forecast, By Region, 2016 – 2027 (USD Million)

5.3. Offline Retail

5.3.1. Market Estimates And Forecast, 2016 – 2027 (USD Million)

5.3.2. Market Estimates And Forecast, By Region, 2016 – 2027 (USD Million)

Chapter 6. ARTIFICIAL INTELLIGENCE (AI) IN RETAIL MARKET BY Deployment Mode INSIGHTS & TRENDS

6.1. Segment 2 Dynamics & Market Share, 2019 & 2027

6.2. Cloud

6.2.1. Market Estimates And Forecast, 2016 – 2027 (USD Million)

6.2.2. Market Estimates And Forecast, By Region, 2016 – 2027 (USD Million)

6.3. On-Premises

6.3.1. Market Estimates And Forecast, 2016 – 2027 (USD Million)

6.3.2. Market Estimates And Forecast, By Region, 2016 – 2027 (USD Million)

Chapter 7. ARTIFICIAL INTELLIGENCE (AI) IN RETAIL MARKET REGIONAL OUTLOOK

7.1. Artificial Intelligence (AI) in Retail Market Share By Region, 2019 & 2027

7.2. NORTH AMERICA

7.2.1. North America Artificial Intelligence (AI) in Retail Market Estimates And Forecast, 2016 – 2027, (USD Million)

7.2.2. North America Artificial Intelligence (AI) in Retail Market Estimates And Forecast By Segment 1, 2016 –2027, (USD Million)

7.2.3. North America Artificial Intelligence (AI) in Retail Market Estimates And Forecast By Segment 2, 2016 –2027, (USD Million)

7.2.4. North America Artificial Intelligence (AI) in Retail Market Estimates And Forecast By Segment 3, 2016 –2027, (USD Million)

7.2.5. U.S.

7.2.5.1. U.S. Artificial Intelligence (AI) in Retail Market Estimates And Forecast, 2016 – 2027, (USD Million)

7.2.5.2. U.S. Artificial Intelligence (AI) in Retail Market Estimates And Forecast By Segment 1, 2016 –2027, (USD Million)

7.2.5.3. U.S. Artificial Intelligence (AI) in Retail Market Estimates And Forecast By Segment 2, 2016 –2027, (USD Million)

7.2.5.4. U.S. Artificial Intelligence (AI) in Retail Market Estimates And Forecast By Segment 3, 2016 –2027, (USD Million)

7.2.6. CANADA

7.2.6.1. Canada Artificial Intelligence (AI) in Retail Market Estimates And Forecast, 2016 – 2027, (USD Million)

7.2.6.2. Canada Artificial Intelligence (AI) in Retail Market Estimates And Forecast By Segment 1, 2016 –2027, (USD Million)

7.2.6.3. Canada Artificial Intelligence (AI) in Retail Market Estimates And Forecast By Segment 2, 2016 –2027, (USD Million)

7.2.6.4. Canada Artificial Intelligence (AI) in Retail Market Estimates And Forecast By Segment 3, 2016 –2027, (USD Million)

7.3. EUROPE

7.3.1. Europe Artificial Intelligence (AI) in Retail Market Estimates And Forecast, 2016 – 2027, (USD Million)

7.3.2. Europe Artificial Intelligence (AI) in Retail Market Estimates And Forecast By Segment 1, 2016 –2027, (USD Million)

7.3.3. Europe Artificial Intelligence (AI) in Retail Market Estimates And Forecast By Segment 2, 2016 –2027, (USD Million)

7.3.4. Europe Artificial Intelligence (AI) in Retail Market Estimates And Forecast By Segment 3, 2016 –2027, (USD Million)

7.3.5. GERMANY

7.3.5.1. Germany Artificial Intelligence (AI) in Retail Market Estimates And Forecast, 2016 – 2027, (USD Million)

7.3.5.2. Germany Artificial Intelligence (AI) in Retail Market Estimates And Forecast By Segment 1, 2016 –2027, (USD Million)

7.3.5.3. Germany Artificial Intelligence (AI) in Retail Market Estimates And Forecast By Segment 2, 2016 –2027, (USD Million)

7.3.5.4. Germany Artificial Intelligence (AI) in Retail Market Estimates And Forecast By Segment 3, 2016 –2027, (USD Million)

7.3.6. FRANCE

7.3.6.1. France Artificial Intelligence (AI) in Retail Market Estimates And Forecast, 2016 – 2027, (USD Million)

7.3.6.2. France Artificial Intelligence (AI) in Retail Market Estimates And Forecast By Segment 1, 2016 –2027, (USD Million)

7.3.6.3. France Artificial Intelligence (AI) in Retail Market Estimates And Forecast By Segment 2, 2016 –2027, (USD Million)

7.3.6.4. France Artificial Intelligence (AI) in Retail Market Estimates And Forecast By Segment 3, 2016 –2027, (USD Million)

7.3.7. U.K.

7.3.7.1. U.K. Artificial Intelligence (AI) in Retail Market Estimates And Forecast, 2016 – 2027, (USD Million)

7.3.7.2. U.K. Artificial Intelligence (AI) in Retail Market Estimates And Forecast By Segment 1, 2016 –2027, (USD Million)

7.3.7.3. U.K. Artificial Intelligence (AI) in Retail Market Estimates And Forecast By Segment 2, 2016 –2027, (USD Million)

7.3.7.4. U.K. Artificial Intelligence (AI) in Retail Market Estimates And Forecast By Segment 3, 2016 –2027, (USD Million)

7.4. ASIA-PACIFIC

7.4.1. Asia Pacific Artificial Intelligence (AI) in Retail Market Estimates And Forecast, 2016 – 2027, (USD Million)

7.4.2. Asia Pacific Artificial Intelligence (AI) in Retail Market Estimates And Forecast By Segment 1, 2016 –2027, (USD Million)

7.4.3. Asia Pacific Artificial Intelligence (AI) in Retail Market Estimates And Forecast By Segment 2, 2016 –2027, (USD Million)

7.4.4. Asia Pacific Artificial Intelligence (AI) in Retail Market Estimates And Forecast By Segment 3, 2016 –2027, (USD Million)

7.4.5. CHINA

7.4.5.1. China Artificial Intelligence (AI) in Retail Market Estimates And Forecast, 2016 – 2027, (USD Million)

7.4.5.2. China Artificial Intelligence (AI) in Retail Market Estimates And Forecast By Segment 1, 2016 –2027, (USD Million)

7.4.5.3. China Artificial Intelligence (AI) in Retail Market Estimates And Forecast By Segment 2, 2016 –2027, (USD Million)

7.4.5.4. China Artificial Intelligence (AI) in Retail Market Estimates And Forecast By Segment 3, 2016 –2027, (USD Million)

7.4.6. INDIA

7.4.6.1. India Artificial Intelligence (AI) in Retail Market Estimates And Forecast, 2016 – 2027, (USD Million)

7.4.6.2. India Artificial Intelligence (AI) in Retail Market Estimates And Forecast By Segment 1, 2016 –2027, (USD Million)

7.4.6.3. India Artificial Intelligence (AI) in Retail Market Estimates And Forecast By Segment 2, 2016 –2027, (USD Million)

7.4.6.4. India Artificial Intelligence (AI) in Retail Market Estimates And Forecast By Segment 3, 2016 –2027, (USD Million)

7.4.7. JAPAN

7.4.7.1. Japan Artificial Intelligence (AI) in Retail Market Estimates And Forecast, 2016 – 2027, (USD Million)

7.4.7.2. Japan Artificial Intelligence (AI) in Retail Market Estimates And Forecast By Segment 1, 2016 –2027, (USD Million)

7.4.7.3. Japan Artificial Intelligence (AI) in Retail Market Estimates And Forecast By Segment 2, 2016 –2027, (USD Million)

7.4.7.4. Japan Artificial Intelligence (AI) in Retail Market Estimates And Forecast By Segment 3, 2016 –2027, (USD Million)

7.4.8. AUSTRALIA

7.4.8.1. Australia Artificial Intelligence (AI) in Retail Market Estimates And Forecast, 2016 – 2027, (USD Million)

7.4.8.2. Australia Artificial Intelligence (AI) in Retail Market Estimates And Forecast By Segment 1, 2016 –2027, (USD Million)

7.4.8.3. Australia Artificial Intelligence (AI) in Retail Market Estimates And Forecast By Segment 2, 2016 –2027, (USD Million)

7.4.8.4. Australia Artificial Intelligence (AI) in Retail Market Estimates And Forecast By Segment 3, 2016 –2027, (USD Million)

7.5. MIDDLE EAST AND AFRICA (MEA)

7.5.1. Mea Artificial Intelligence (AI) in Retail Market Estimates And Forecast, 2016 – 2027, (USD Million)

7.5.2. Mea Artificial Intelligence (AI) in Retail Market Estimates And Forecast By Segment 1, 2016 –2027, (USD Million)

7.5.3. Mea Artificial Intelligence (AI) in Retail Market Estimates And Forecast By Segment 2, 2016 –2027, (USD Million)

7.5.4. Mea Artificial Intelligence (AI) in Retail Market Estimates And Forecast By Segment 3, 2016 –2027, (USD Million)

7.6. LATIN AMERICA

7.6.1. Latin America Artificial Intelligence (AI) in Retail Market Estimates And Forecast, 2016 – 2027, (USD Million)

7.6.2. Latin America Artificial Intelligence (AI) in Retail Market Estimates And Forecast By Segment 1, 2016 –2027, (USD Million)

7.6.3. Latin America Artificial Intelligence (AI) in Retail Market Estimates And Forecast By Segment 2, 2016 –2027, (USD Million)

7.6.4. Latin America Artificial Intelligence (AI) in Retail Market Estimates And Forecast By Production Process, 2016 –2027, (USD Million)

7.6.5. Latin America Artificial Intelligence (AI) in Retail Market Estimates And Forecast By Segment 3, 2016 –2027, (USD Million)

Chapter 8. COMPETITIVE LANDSCAPE

8.1. Market Share By Manufacturers

8.2. Strategic Benchmarking

8.2.1. New Product Launches

8.2.2. Investment & Expansion

8.2.3. Acquisitions

8.2.4. Partnerships, Agreement, Mergers, Joint-Ventures

8.3. Vendor Landscape

8.3.1. North American Suppliers

8.3.2. European Suppliers

8.3.3. Asia-Pacific Suppliers

8.3.4. Rest Of The World Suppliers

Chapter 9. COMPANY PROFILES

9.1. Amazon Web Services

9.1.1. Company Overview

9.1.2. Financial Performance

9.1.3. Product Insights

9.1.4. Strategic Initiatives

9.2. IBM

9.2.1. Company Overview

9.2.2. Financial Performance

9.2.3. Product Insights

9.2.4. Strategic Initiatives

9.3. Google

9.3.1. Company Overview

9.3.2. Financial Performance

9.3.3. Product Insights

9.3.4. Strategic Initiatives

9.4. Microsoft

9.4.1. Company Overview

9.4.2. Financial Performance

9.4.3. Product Insights

9.4.4. Strategic Initiatives

9.5. Intel

9.5.1. Company Overview

9.5.2. Financial Performance

9.5.3. Product Insights

9.5.4. Strategic Initiatives

9.6. ViSenze

9.6.1. Company Overview

9.6.2. Financial Performance

9.6.3. Product Insights

9.6.4. Strategic Initiatives

9.7. Oracle

9.7.1. Company Overview

9.7.2. Financial Performance

9.7.3. Product Insights

9.7.4. Strategic Initiatives

9.8. Nvidia

9.8.1. Company Overview

9.8.2. Financial Performance

9.8.3. Product Insights

9.8.4. Strategic Initiatives

9.9. SAP

9.9.1. Company Overview

9.9.2. Financial Performance

9.9.3. Product Insights

9.9.4. Strategic Initiatives

9.10. Salesforce

9.10.1. Company Overview

9.10.2. Financial Performance

9.10.3. Product Insights

9.10.4. Strategic Initiatives

RESEARCH METHODOLOGY

A research methodology is a systematic approach for assessing or conducting a market study. Researchers tend to draw on a variety of both qualitative and quantitative study methods, inclusive of investigations, survey, secondary data and market observation.

Such plans can focus on classifying the products offered by leading market players or simply use statistical models to interpret observations or test hypotheses. While some methods aim for a detailed description of the factors behind an observation, others present the context of the current market scenario.

Now let’s take a closer look at the research methods here.

Secondary Research Model

Extensive data is obtained and cumulated on a substantial basis during the inception phase of the research process. The data accumulated is consistently filtered through validation from the in-house database, paid sources as well reputable industry magazines. A robust research study requires an understanding of the overall value chain. Annual reports and financials of industry players are studied thoroughly to have a comprehensive idea of the market taxonomy.

Primary Insights

Post conglomeration of the data obtained through secondary research; a validation process is initiated to verify the numbers or figures. This process is usually performed by having a detailed discussion with the industry experts.

However, we do not restrict our primary interviews only to the industry leaders. Our team covers the entire value chain while verifying the data. A significant number of raw material suppliers, local manufacturers, distributors, and stakeholders are interviewed to make our findings authentic. The current trends which include the drivers, restraints, and opportunities are also derived through the primary research process.

Market Estimation

The market estimation is conducted by analyzing the data collected through both secondary and primary research. This process involves market breakdown, bottom-up and top- down approach.

Moreover, while forecasting the market a comprehensive statistical time series model is designed for each market. Macroeconomic indicators are considered to understand the current trends of the market. Each data point is verified by the process of data triangulation method to arrive at the final market estimates.

Final Presentation

The penultimate process results in a holistic research report. The study equips key industry players to undertake significant strategic decisions through the findings. The report encompasses detailed market information. Graphical representations of the current market trends are also made available in order to make the study highly comprehensible for the reader.

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Artificial Intelligence Ai In Retail Market Size, Type Analysis, Application Analysis, End-Use, Industry Analysis, Regional Outlook, Competitive Strategies And Forecasts, 2023-2032