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AI in E Commerce Market Size, Industry Share & Trends | 2032
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AI in E Commerce Market Size, Industry Share & Trends | 2032

Segments - AI in E Commerce Market by Technology (Deep Learning, Augmented Reality, Machine Learning, Computer Vision, Speech Recognition, and Natural Language Processing), Application (Warehouse Automation, Customer Relationship Management, Customer Service, Fake Review Analysis, Merchandizing, and Supply Chain Analysis), Deployment (On-Premise, Hybrid, and Cloud-based), and Region (Asia Pacific, North America, Latin America, Europe, and Middle East & Africa) - Global Industry Analysis, Growth, Size, Share, Trends, and Forecast 2024 – 2032

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Author : Raksha Sharma
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Editor : Shruti Bhat

Upcoming | Report ID :ICT-SE-6560 | 4.7 Rating | 89 Reviews | 278 Pages | Format : PDF Excel PPT

Report Description


The global AI in E commerce market size was USD 6.1 Billion in 2023 and is expected to reach USD 59.8 Billion by 2032, expanding at a CAGR of 17% during 2024–2032. The market growth is attributed to the rising digital transformation in the retail industry and the increasing demand for personalized shopping experiences.

Rising technological advances in artificial intelligence technology are enhancing the e-commerce industry. The AI integration with e commerce platforms facilitates specialized shopping experiences for customers. It enables e commerce websites to suggest products to users uniquely and analyzes customer engagement across POS channels.

AI in E Commerce Market Outlook

AI has transformed customer engagement by offering personalized product and service recommendations based on consumer/user behavior and historical data. The personalization trend with AI has exponentially driven the online shopping industry by accessing data from websites, email campaigns, and mobile apps. For instance,

  • In March 2024, EcomTech demonstrated AI's impact by refining customer engagement through personalized recommendations and dynamic pricing, leading to a 25% sales conversion rate increase and a 20% boost in average order value.

AI in e commerce is expected to witness all dimensions of online industries including demand to predict shopping patterns. It has extensively impacted predictive analysis by analyzing AI algorithms and customer data that indicate the purchase number of products, reduce waste, and allow retailers to optimize inventory management. For example,
Regulations such as the GDPR in the EU and similar laws globally shape how AI is used in e-commerce platforms to ensure compliance with data handling standards and promote ethical AI practices. These regulations are crucial in fostering a secure and trustworthy e commerce environment for consumers globally.

AI in E Commerce Market Dynamics

AI in E Commerce Market Dynamics

Major Drivers

Increasing use of AI-powered chatbots is driving the market. Chatbot offers personalized responses to customers to enhance their experience. These chatbots are equipped with machine learning (ML) and natural language processing (NLP) technologies and provide real-time insights per customer's choice. They understand customer behavior patterns & sentiments and assist them by responding to their queries and building relations.

Existing Restraints

Data protection concerns and privacy are anticipated to hamper the market. The E-commerce platform collects client data to personalize the experience and improve sales. It is crucial to handle customer data carefully and adhere to privacy regulations while using AI. To safeguard sensitive information, companies provide transparent information about user consent, and data usage, and implement strong security measures.

Emerging Opportunities

AI-driven voice search and visuals are anticipated to create lucrative opportunities in the market. By mining the metadata and processing inquiries, AI in visual search optimizes its functionalities. It enhances consumer engagement & experience with a visual search engine by using AI features to track, analyze, and predict growing shopping trends.

Scope of the AI in E Commerce Market Report

The market report includes an assessment of the market trends, segments, and regional markets. Overview and dynamics are included in the report.

Attributes

Details

Report Title

AI in E Commerce Market - Global Industry Analysis, Growth, Share, Size, Trends, and Forecast

Base Year

2023

Historic Data

2016–2021

Forecast Period

2024–2032

Segmentation

Technology (Deep Learning, Augmented Reality, Machine Learning, Computer Vision, Speech Recognition, and Natural Language Processing), Application (Warehouse Automation, Customer Relationship Management, Customer Service, Fake Review Analysis, Merchandizing, and Supply Chain Analysis), and Deployment (On-Premise, Hybrid, and Cloud-based)

Regional Scope

Asia Pacific, North America, Latin America, Europe, and Middle East & Africa

Report Coverage

Company Share, Market Analysis and Size, Competitive Landscape, Growth Factors, Market Trends, and Revenue Forecast

Key Players Covered in the Report

Amazon Web Services, Inc.; Otto Group; Myntra; eBay; Siam Makro Public Co.Ltd.; IBM Corporation; Zoovu; Fractal Analytics Inc.; Kroger Co.; Google LLC; SAP SE; and Salesforce.com, Inc.


Regional Outlook

In terms of region, the global AI in e commerce market is classified as Asia Pacific, North America, Latin America, Europe, and Middle East & Africa. North America holds the major share of the market, due to customer behavior. The availability of multiple e-commerce industries is considered to be the main factor in the change in customer behavior, as they demand individual experiences, control, and high standards for convenience.

Asia Pacific is anticipated to witness significant growth during the forecast period, owing to technical and economic improvements in the region. The explosion of e commerce has boosted digital marketing platforms, payment systems, online marketplaces, and logistical networks.

AI in E Commerce Market Region

Market Segment Insights

Technology Segment Analysis

On the basis of technology, the global market is segregated into deep learning, augmented reality, machine learning, computer vision, speech recognition, and natural language processing. The machine learning segment registers a considerable share of the market in 2023, as it offers deep insights from collected information and provides personalized user experiences to customers. It helps retailers to optimize their demand forecasts and supply chain plans, to augment inventory productivity, driving the segment. For instance,

  • In April 2023, Flipkart announced that to manage its business performance, it is using machine learning. They are using AI solutions to propel the consumer experience and provide pricing recommendations.

Natural language processing (NLP) is expected to hold a steady share of the market during the forecast period, as it helps users to customize their searches. E commerce retailers seek NLP by recommending the right service or product, to engage potential customers and categorize the products. NLP has gained traction and is trendier in e-commerce as voice-activated payments, thus boosting the demand of the segment.

AI in E Commerce Market Technology

Application Segment Analysis

Based on application, the market is divided into warehouse automation, customer relationship management, customer service, fake review analysis, merchandising, and supply chain analysis. The warehouse automation segment holds the major market share of the market in 2023, due to identifying inventory and the rising adoption of IoT sensors for automated alerts. Intelligent robots help e commerce companies to boost efficiency and productivity through seamless warehouse management.

The customer relationship management segment is expected to expand at a significant growth rate during the projection period, attributed to the emerging demand for better customer engagement. The segment is expected to flourish in the market, as AI-driven tools help retailers maintain robust customer relationships and loyalty.

AI in E Commerce Market Application

Deployment Segment Analysis

On the basis of deployment, the market is trifurcated into hybrid, on-premise, and cloud-based. The cloud-based segment generated the largest revenue share in 2023, owing to scalability and seamless inventory management. Cloud services provide a personalized experience to its customers with increased agility, as the cloud offers real-time data. For example, Amazon utilizes a dynamic pricing strategy. They periodically adjust their prices by around 20%, whenever their competitors offer promotions.

Segments

The AI in E Commerce market has been segmented based on

Technology

  • Deep Learning
  • Augmented Reality
  • Machine Learning
  • Computer Vision
  • Speech Recognition
  • Natural Language Processing

Application

  • Warehouse Automation
  • Customer Relationship Management
  • Customer Service
  • Fake Review Analysis
  • Merchandizing
  • Supply Chain Analysis

Deployment

  • On-Premise
  • Hybrid
  • Cloud-based

Region

  • Asia Pacific
  • North America
  • Latin America
  • Europe
  • Middle East & Africa

Key Players

  • Amazon Web Services, Inc.
  • Otto Group
  • Myntra
  • eBay
  • Siam Makro Public Co.Ltd.
  • IBM Corporation
  • Zoovu
  • Fractal Analytics Inc.
  • Kroger Co.
  • Google LLC
  • SAP SE
  • Salesforce.com, Inc.

Competitive Landscape

Key players competing in the global AI in e-commerce market are Amazon Web Services, Inc.; Otto Group; Myntra; eBay; Siam Makro Public Co. Ltd.; IBM Corporation; Zoovu; Fractal Analytics Inc.; Kroger Co.; Google LLC; SAP SE; Salesforce.com, Inc. 

These companies adopted development strategies including mergers, acquisitions, collaboration, partnerships, product launches, and production expansion to expand their consumer base worldwide. For instance,

  • In April 2023, Siam Makro Public Company Limited collaborated with Oracle to accelerate its digital transformation by implementing Oracle Cloud Infrastructure to drive its retail management.

  • In January 2023, Microsoft collaborated with AiFi, to launch smart store analytics, which provides a cloud-tracking service for smart and cashier-less outlets that aids with operational analytics and shoppers.

  • In November 2022, Fractal Analytics Inc. launched Asper.ai, for manufacturing consumer goods and retail sectors. It brings end-to-end AI products, strategic pricing, inventory optimization, demand planning, and positioning.

  • In June 2022, Zoovu raised around 169 million dollars in a series C funding to boost the AI-powered platform and expand its penetration used by Amazon, 3M, and Microsoft.

  • In July 2021, LivePerson, Inc. acquired e-bot7 to help brands roll out AI-powered messaging experiences.

    AI in E Commerce Market Key Players

Table Of Content

1. Executive Summary
2. Assumptions and Acronyms Used
3. Research Methodology
4. AI in E Commerce Market Overview
  4.1. Introduction
     4.1.1. Market Taxonomy
     4.1.2. Market Definition
  4.2. Macro-Economic Factors
     4.2.1. Industry Outlook
  4.3. AI in E Commerce Market Dynamics
     4.3.1. Market Drivers
     4.3.2. Market Restraints
     4.3.3. Opportunity
     4.3.4. Market Trends
  4.4. AI in E Commerce Market - Supply Chain
  4.5. Global AI in E Commerce Market Forecast
     4.5.1. AI in E Commerce Market Size (US$ Mn) and Y-o-Y Growth
     4.5.2. AI in E Commerce Market Size (000’ Units) and Y-o-Y Growth
     4.5.3. AI in E Commerce Market Absolute $ Opportunity
5. Global AI in E Commerce Market Analysis and Forecast by Applications
  5.1. Market Trends
  5.2. Introduction
     5.2.1. Basis Point Share (BPS) Analysis by Applications
     5.2.2. Y-o-Y Growth Projections by Applications
  5.3. AI in E Commerce Market Size and Volume Forecast by Applications
     5.3.1. Warehouse Automation
     5.3.2. Customer Relationship Management
     5.3.3. Customer Service
     5.3.4. Fake Review Analysis
     5.3.5. Merchandizing
     5.3.6. Supply Chain Analysis
  5.4. Absolute $ Opportunity Assessment by Applications
  5.5. Market Attractiveness/Growth Potential Analysis by Applications
6. Global AI in E Commerce Market Analysis and Forecast by Region
  6.1. Market Trends
  6.2. Introduction
     6.2.1. Basis Point Share (BPS) Analysis by Region
     6.2.2. Y-o-Y Growth Projections by Region
  6.3. AI in E Commerce Market Size and Volume Forecast by Region
     6.3.1. North America
     6.3.2. Latin America
     6.3.3. Europe
     6.3.4. Asia Pacific
     6.3.5. Middle East and Africa (MEA)
  6.4. Absolute $ Opportunity Assessment by Region
  6.5. Market Attractiveness/Growth Potential Analysis by Region
  6.6. Global AI in E Commerce Demand Share Forecast, 2019-2026
7. North America AI in E Commerce Market Analysis and Forecast
  7.1. Introduction
     7.1.1. Basis Point Share (BPS) Analysis by Country
     7.1.2. Y-o-Y Growth Projections by Country
  7.2. North America AI in E Commerce Market Size and Volume Forecast by Country
     7.2.1. U.S.
     7.2.2. Canada
  7.3. Absolute $ Opportunity Assessment by Country
  7.4. North America AI in E Commerce Market Size and Volume Forecast by Applications
     7.4.1. Warehouse Automation
     7.4.2. Customer Relationship Management
     7.4.3. Customer Service
     7.4.4. Fake Review Analysis
     7.4.5. Merchandizing
     7.4.6. Supply Chain Analysis
  7.5. Basis Point Share (BPS) Analysis by Applications
  7.6. Y-o-Y Growth Projections by Applications
  7.7. Market Attractiveness/Growth Potential Analysis
     7.7.1. By Country
     7.7.2. By Product Type
     7.7.3. By Application
  7.8. North America AI in E Commerce Demand Share Forecast, 2019-2026
8. Latin America AI in E Commerce Market Analysis and Forecast
  8.1. Introduction
     8.1.1. Basis Point Share (BPS) Analysis by Country
     8.1.2. Y-o-Y Growth Projections by Country
     8.1.3. Latin America Average Pricing Analysis
  8.2. Latin America AI in E Commerce Market Size and Volume Forecast by Country
      8.2.1. Brazil
      8.2.2. Mexico
      8.2.3. Rest of Latin America
   8.3. Absolute $ Opportunity Assessment by Country
  8.4. Latin America AI in E Commerce Market Size and Volume Forecast by Applications
     8.4.1. Warehouse Automation
     8.4.2. Customer Relationship Management
     8.4.3. Customer Service
     8.4.4. Fake Review Analysis
     8.4.5. Merchandizing
     8.4.6. Supply Chain Analysis
  8.5. Basis Point Share (BPS) Analysis by Applications
  8.6. Y-o-Y Growth Projections by Applications
  8.7. Market Attractiveness/Growth Potential Analysis
     8.7.1. By Country
     8.7.2. By Product Type
     8.7.3. By Application
  8.8. Latin America AI in E Commerce Demand Share Forecast, 2019-2026
9. Europe AI in E Commerce Market Analysis and Forecast
  9.1. Introduction
     9.1.1. Basis Point Share (BPS) Analysis by Country
     9.1.2. Y-o-Y Growth Projections by Country
     9.1.3. Europe Average Pricing Analysis
  9.2. Europe AI in E Commerce Market Size and Volume Forecast by Country
     9.2.1. Germany
     9.2.2. France
     9.2.3. Italy
     9.2.4. U.K.
     9.2.5. Spain
     9.2.6. Russia
     9.2.7. Rest of Europe
  9.3. Absolute $ Opportunity Assessment by Country
  9.4. Europe AI in E Commerce Market Size and Volume Forecast by Applications
     9.4.1. Warehouse Automation
     9.4.2. Customer Relationship Management
     9.4.3. Customer Service
     9.4.4. Fake Review Analysis
     9.4.5. Merchandizing
     9.4.6. Supply Chain Analysis
  9.5. Basis Point Share (BPS) Analysis by Applications
  9.6. Y-o-Y Growth Projections by Applications
  9.7. Market Attractiveness/Growth Potential Analysis
     9.7.1. By Country
     9.7.2. By Product Type
     9.7.3. By Application
  9.8. Europe AI in E Commerce Demand Share Forecast, 2019-2026
10. Asia Pacific AI in E Commerce Market Analysis and Forecast
  10.1. Introduction
     10.1.1. Basis Point Share (BPS) Analysis by Country
     10.1.2. Y-o-Y Growth Projections by Country
     10.1.3. Asia Pacific Average Pricing Analysis
  10.2. Asia Pacific AI in E Commerce Market Size and Volume Forecast by Country
     10.2.1. China
     10.2.2. Japan
     10.2.3. South Korea
     10.2.4. India
     10.2.5. Australia
     10.2.6. Rest of Asia Pacific (APAC)
  10.3. Absolute $ Opportunity Assessment by Country
  10.4. Asia Pacific AI in E Commerce Market Size and Volume Forecast by Applications
     10.4.1. Warehouse Automation
     10.4.2. Customer Relationship Management
     10.4.3. Customer Service
     10.4.4. Fake Review Analysis
     10.4.5. Merchandizing
     10.4.6. Supply Chain Analysis
  10.5. Basis Point Share (BPS) Analysis by Applications
  10.6. Y-o-Y Growth Projections by Applications
  10.7. Market Attractiveness/Growth Potential Analysis
     10.7.1. By Country
     10.7.2. By Product Type
     10.7.3. By Application
  10.8. Asia Pacific AI in E Commerce Demand Share Forecast, 2019-2026
11. Middle East & Africa AI in E Commerce Market Analysis and Forecast
  11.1. Introduction
     11.1.1. Basis Point Share (BPS) Analysis by Country
     11.1.2. Y-o-Y Growth Projections by Country
     11.1.3. Middle East & Africa Average Pricing Analysis
  11.2. Middle East & Africa AI in E Commerce Market Size and Volume Forecast by Country
     11.2.1. Saudi Arabia
     11.2.2. South Africa
     11.2.3. UAE
     11.2.4. Rest of Middle East & Africa (MEA)
  11.3. Absolute $ Opportunity Assessment by Country
  11.4. Middle East & Africa AI in E Commerce Market Size and Volume Forecast by Applications
     11.4.1. Warehouse Automation
     11.4.2. Customer Relationship Management
     11.4.3. Customer Service
     11.4.4. Fake Review Analysis
     11.4.5. Merchandizing
     11.4.6. Supply Chain Analysis
  11.5. Basis Point Share (BPS) Analysis by Applications
  11.6. Y-o-Y Growth Projections by Applications
  11.7. Market Attractiveness/Growth Potential Analysis
     11.7.1. By Country
     11.7.2. By Product Type
     11.7.3. By Application
  11.8. Middle East & Africa AI in E Commerce Demand Share Forecast, 2019-2026
12. Competition Landscape
  12.1. Global AI in E Commerce Market: Market Share Analysis
  12.2. AI in E Commerce Distributors and Customers
  12.3. AI in E Commerce Market: Competitive Dashboard
  12.4. Company Profiles (Details: Overview, Financials, Developments, Strategy)
     12.4.1. Amazon Web Services, Inc.
     12.4.2. Otto Group
     12.4.3. Myntra
     12.4.4. eBay
     12.4.5. Siam Makro Public Co.Ltd.
     12.4.6. IBM Corporation
     12.4.7. Zoovu
     12.4.8. Fractal Analytics Inc.
     12.4.9. Kroger Co.
     12.4.10. Google LLC
     12.4.11. SAP SE
     12.4.12. Salesforce.com, Inc.

Methodology

Our Clients

Deloitte
Dassault Aviation
FedEx Logistics
The John Holland Group
Pfizer
Honda Motor Co. Ltd.
Nestle SA
General Electric