Artificial Intelligence (AI) in E-Commerce Market Size 2031

Artificial Intelligence (AI) in E-Commerce Market Size 2031

Segments - Artificial Intelligence (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 2023 – 2031

https://growthmarketreports.com/Raksha
Author : Raksha Sharma
https://growthmarketreports.com/Vineet
Fact-checked by : Vineet Pandey
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Editor : Shruti Bhat

Upcoming | Report ID :ICT-SE-5537 | 4.9 Rating | 49 Reviews | 244 Pages | Format : PDF Excel PPT

Report Description


The global AI in e-commerce market size was USD 6.1 Bn in 2022 and is likely to reach USD 59.8 Bn by 2031, expanding at a CAGR of 17% during 2023–2031. The market growth is attributed to the rising digital transformation in the retail industry and the increasing demand for personalized shopping experiences.

Advances in Artificial Intelligence technology are playing a crucial role in the rapidly expanding e-commerce industry. The AI integration with e-commerce platforms is facilitating better and more specialized shopping experiences for customers. With this technology, digital commerce platforms are able to bring evolutionary changes to product suggestions to users as well as analyze customer engagement across POS channels to provide a hassle-free product browsing experience. All of these factors are boosting the AI in e-commerce market.

AI in E-Commerce Market Outlook

In addition to this, customer engagement is also being transformed with AI, as it offers personalized product and service recommendations based on consumer/user behavior and historical data. The personalization trend with AI has exponentially driven online shopping industry growth, by processing on data from websites, email campaigns, and mobile apps. For instance,

  • The survey by Ubisend, UK-based leading chatbot platform, held in 2019 states that, around 40% of consumers are seeking shopping deals and discounts from AI-powered chatbots, and among every five customers one is willing to buy service or products from the same platform.

The research report finds that the COVID-19 pandemic has boosted AI in the e-commerce market. The rapidly evolving consumer purchasing patterns & behavior, in-shop operations, and rising demand for various services & products have elevated AI adoption in online retail space across the world.  Since 2020, to enhance customer experience and augment online sales, many industries adopted AI technology. The demand for machine learning and robotics solutions rapidly grew during the pandemic from e-commerce industry players, to speed up warehouse operations and make up for the labor shortage caused by the pandemic and lockdowns. This, as a result, further boosted the market growth during pandemic.

AI in E-Commerce Market Dynamics

AI in E-Commerce Market Dynamics

Major Drivers

Increasing use of AI-powered chatbots is one of the key driving factors of the global AI in the e-commerce 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 offer real-time insights as per customer's choice.

Chatbot understands customer behavior patterns & sentiments and assists them by responding to their queries and building relations. Such AI-powered chatbots are enabling e-commerce apps and websites to enhance the platform's reliability and customer servicing, which is driving their adoption across the industry. For instance,

  • As per the report published in April 2023 by TIDIO, an AI-powered customer service platform,  around 88% of customers had one conversation with a chatbot in the past year. And out of 10 customers at least one conversion is seen with a chatbot in 2022.

 Growing need to optimize product suggestions and inventory management is propelling the market. AI in e-commerce is expected to witness all dimensions of online industries, including the demand to predict shopping patterns. It has made an extensive impact on predictive analysis by analyzing customer data that can predict how the customer interacts with the platform features and recognize their shopping inclinations. Inventory optimization with AI, enables streamlining supply and demand cycles and supports in prevention of waste of resources.

Existing Restraints

Higher implementation cost is likely to be a restraining factor for the market. For enhancing customer engagement, well-established retail brands keep investing in innovative technologies, as their budget concerns are significantly lesser compared to small scale brands. Small & medium-sized enterprises and start-up companies face challenges in adopting new technologies, owing to a lack of technical expertise, infrastructure, and budgetary limits, which can restrict the market.

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. While using AI, it is crucial to handle customer data carefully and adhere to privacy regulations. There are significant concerns about the way customer data is being stored and handled by e-commerce corporations. Governments around the world are framing various bills and regulations to address the privacy issues raised by various watchdog organizations. These policies can act as restraints for the market as they are likely to vary in each nation.

Emerging Opportunities

Expansion of AI-driven voice search and visuals is anticipated to create lucrative opportunities in the market. By mining the metadata and processing inquiries, AI in visual search optimizes its functionalities. The audio and visual featuresenhance consumer engagement & experience with search engines by using AI features to track, analyze, and predict growing shopping trends. For instance,

  • In September 2022, Google Search introduced new tools to foster voice and visual shopping. When customers search the word shop followed by the product name, they can see the visual feed of the product and nearby inventory related to it.

 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 have also been included in the report.

Attributes

Details

Report Title

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

Base Year

2022

Historic Data

2016–2021

Forecast Period

2023–2031

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), 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; Salesforce.com, Inc.

AI in E-Commerce Market Segment Insights

Technology Segment Analysis

On the basis of technology, the global AI in E-Commerce Market is segregated into deep learning, augmented reality, machine learning, computer vision, speech recognition, and natural language processing. The machine learning segment is projected to register a considerable CAGR during the forecast period, 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.

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. To keep potential customers interested and categorize products, e-commerce retailers are using NLP to recommend the right service or product. NLP provides smart product recommendations based on previous search context and data. In recent years, NLP has gained traction in e-commerce for making voice-activated payments.

AI in E-Commerce Market Technology Segmentation

Application Segment Analysis

Based on application, the AI in e-commerce market is divided into warehouse automation, customer relationship management, customer service, fake review analysis, merchandising, and supply chain analysis. The warehouse automation segment is expected to expand at a significant growth rate during the projection period, owing to automation in identifying inventory and the rising adoption of internet of things (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 grow at a rapid pace. The growth of the segment is attributed to the emerging demand for better customer engagement, as customer interaction is not limited to offline stores. AI-driven CRM tools help retailers to maintain robust customer relationships and loyalty, by quickly and efficiently communicating with customers, recommending products, and addressing customers queries. For instance,

  • According to minderest study in 2018, Amazon utilizes a dynamic pricing strategy. The platform periodically adjusts the prices by around 20%, whenever competitors are running promotion campaigns with discount offers. Based on sales forecast, Amazon does it gradually to achieve maximum profitability.

AI in E-Commerce Market Application

Deployment Segment Analysis

On the basis of deployment, the AI in e-commerce market is divided into hybrid, on-premise, and cloud-based. The cloud-based segment is anticipated to hold the key share of the market during the forecast period, owing to scalability and seamless inventory management. Cloud computing offers real-time data, cloud architecture, and analytics for predictive & prescriptive inventory forecasting services to the e-commerce. Cloud services provide a personalized experience to its customers with increased agility. For instance,

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

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 is expected to dominate the market during the projection period, due to increasing focus to provide personalized shopping experience based on customer interaction and behavior analysis on the platform.

The availability of multiple e-commerce businesses in the region is the key factor fueling the demand for individual experiences, more control, and high standards for convenience. Moreover, the increasing preference to online shopping to suit the changing lifestyle has fueled the e-commerce growth in this region.

  • In July 2021, LivePerson, Inc. acquired e-bot7 to help brands roll out AI-powered messaging experiences. This is likely to accelerate the speed at which brands can deploy and train AI-powered conversations. The company’s self-service AI tool has automated 60% of conversations in just 6 weeks.

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 in the region has expanded digital marketing platforms, payment systems, online marketplaces, and logistical networks. E-commerce players are able to serve the users efficiently with the integration of AI feature, as they allow seamless shopping experience and logistic support. Further, the vast customer base also requisites companies to adopt AI chatbots to address customer concerns without any delays. Such factors are crucially driving market in the region.

For instance,

  • In April 2023, Flipkart announced that to manage its business performance, it is using machine learning and data science. They are using AI solutions to enhance the consumer experience, predicting ratings and returns, assessing product quality, potential listing, and provide pricing recommendations.

    AI in E-Commerce Market Regions

Segments

The AI in E-Commerce market has been segmented on the basis of

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 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 USD in a series C funding to boost the AI-powered platform and expand its penetration used by Amazon, 3M, and Microsoft.

    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

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