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Global AI in E-Commerce Market 2025-2035

Published Nov 20, 2025
Length 204 Pages
SKU # ORMR20648975

Description

Global AI in E-Commerce Market Size, Share & Trends Analysis Report by Component (Software and Services), by Deployment Mode (On-Premises, and Cloud), and by Application (Warehouse Automation, Supply Chain Analysis, Customer Relationship Management, Product Recommendation, Merchandising, Fake Review Analysis, and Customer Service), Forecast Period (2026-2035)

Industry Overview

AI in e-commerce market was valued at $8,375 million in 2025 and is projected to reach $36,230 million by 2035, growing at a CAGR of 15.8% from 2026 to 2035. The global AI in e-commerce market is driven primarily by rapid advancements in machine learning, natural language processing, and computer vision. The advancement in these technologies enables hyper-personalization, intelligent automation, and data-driven decision-making across the shopping journey. The rising use of hyper-personalization to enhance the shopping experience via recommendation engines is expected to provide substantial market growth during the forecast period. For instance, in August 2025, Saks Global’s CCO announced that the company is integrating AI-enabled personalization -starting with Saks’s homepage. The goal of leveraging AI is to rebuild luxury shopping and to push its retail brands into a new phase.

Market Dynamics

Conversational Commerce: Chatbots, Virtual Assistants, & Voice Interfaces for Customer Interaction

The rising demand for conversational AI is expected to be the key driver in the global AI in e-commerce market. The rising adoption of AI-powered chatbots and virtual assistants across retailers enables natural language communication among customers and e-commerce platforms. These chatbots can guide customers through product selections, provide checkout assistance, and offer post-purchase support. For instance, in June 2024, Target announced that the company leveraged AI AI-powered chatbot “Store Companion.” The company leveraged a chatbot to enhance the shopping experience and to provide information on tasks. The information on tasks refers to rebooting a cash register or enrolling a shopper in Target's loyalty program.

Rising Popularity of Visual & Image‐Based Product Search

The rising popularity of visual & image‐based product search, as it allows customers to search for products using images. The visual & image‐based product search assists customers in directly searching for their needed product with an image instead of following the traditional method of text. This new AI technology of Amazon leverages deep learning algorithms to identify shapes, colors, patterns, and textures. The deep learning algorithms make it easier for users to find exact or similar products. For instance, in September 2025, Amazon launched “Lens Live,” an AI-powered visual search for real-time shopping. The Lens Live is integrated into the company’s Amazon shopping app. It is a new AI feature tool that assists customers in instantly identifying and shopping for the products they see in the real world.

Market Segmentation
  • Based on the component, the market is segmented into software and services.
  • Based on the deployment mode, the market is segmented into cloud and on-premises.
  • Based on the Application, the market is segmented into warehouse automation, supply chain analysis, customer relationship management, product recommendation, merchandising, fake review analysis, and customer service.
Product Recommendation Segment to Lead the Market with the Largest Share

Among the applications, the product recommendation is expected to hold the largest market share in the market, owing to benefits such as a personalized shopping experience, increasing customer engagement, and rising conversion rates. The e-commerce platforms across the globe, such as Amazon, Alibaba, Flipkart, and others, are leveraging AI for product recommendation, which helps to generate higher revenue. The AI for product recommendation drives sales growth by influencing purchase decisions, increasing average order value, and improving cross-selling and upselling opportunities. For instance, in September 2024, Amazon announced that the company is using generative AI to improve product recommendations and descriptions, which can be more relevant to its customers. Based on a customer’s shopping activity, Amazon reviews each customer’s preferences to create personalized recommendations on their homepage. It also provides personalized product descriptions that are more relevant to customers.

Component: A Key Segment in Market Growth

Among all segments, the component segment is expected to be a key segment driving the growth of the market during the forecast period. The software solutions, such as recommendation engines, CRM platforms, and fraud detection systems, are the backbone of AI adoption. The rising adoption of software solutions among retailers to enhance customer experience and boost operational efficiency is further driving the growth during the forecast period. For instance, in May 2025, Glance AI launched an AI commerce platform that is built to revolutionize how people shop and to reshape how intelligence drives decisions and economies.

Regional Outlook

The global AI in e-commerce market is further divided by geography, including North America (the US and Canada), Asia-Pacific (India, China, Japan, South Korea, Australia and New Zealand, ASEAN Countries, and the Rest of Asia-Pacific), Europe (the UK, Germany, France, Italy, Spain, Russia, and the Rest of Europe), and the Rest of the World (the Middle East & Africa, and Latin America).

North America is driving the Market Growth

North America is expected to hold the largest market share in the AI in e-commerce market during the forecast period. The factors contributing to the market growth, such as high investment in AI solutions, an advanced ecosystem, and the presence of key market players, are contributing to the growth of the market. The rising investment in AI technologies by market players in the region will further propel the growth of the market. For instance, in August 2025, Doola announced the launch of AI Co-Founder. AI Co-Founder is the first intelligent business partner that cuts founders' back-office work from hours per week to minutes. With the launch of AI Co-Founder by Doola, e-commerce entrepreneurs can now get from idea to first sale faster and automate the complex operations of scaling a US business.

Asia-Pacific Region Shares Significant Market Share

The Asia-Pacific region is experiencing substantial growth in AI in the e-commerce market. The growing technological advancements, expanding digital infrastructure, and rising consumer expectations are expected to contribute to the growth of the market during the forecast period. For instance, in March 2025, SBL launched a project finance unit for AI, fintech, and e-commerce industries. The project will help broaden the activities of the bank’s project finance and structuring unit. This unit is responsible for appraising, structuring, and funding large-scale infrastructure projects.

Market Players Outlook

The global AI in E-Commerce market is driven by leading companies such Amazon Web Services, Inc., Google LLC, IBM Corp., Microsoft Corp., Salesforce, Inc., Kore.ai, Inc., SAP SE, and Oracle Corp., TCS, Yellow.ai, among others, with players strengthening their presence through strategic partnerships, mergers and acquisitions, innovative product launches, advanced technology integration, and expansion across emerging markets.

Recent Development
  • In August 2025, Amazon announced the launch of Rufus in India. Rufus is a generative AI-powered conversational shopping assistant. The virtual assistant can answer customer questions on shopping needs, products, and comparisons. The chatbot can make recommendations based on this context and facilitate product discovery.
  • In July 2025, Mango launched a new Stylist assistant with AI in E-Commerce. The AI in the E-Commerce assistant is to help shoppers and provide a fashion guide across the US and parts of Europe. The company launched a chatbot on its website to offer answers based on the context provided by users interested in personalized recommendations.
The Report Covers
  • Market value data analysis for 2025 and forecast to 2035.
  • Annualized market revenues ($ million) for each market segment.
  • Country-wise analysis of major geographical regions.
  • Key companies operating in the global AI in e-commerce market. Based on the availability of data, information related to new products and relevant news is also available in the report.
  • Analysis of business strategies by identifying the key market segments positioned for strong growth in the future.
  • Analysis of market-entry and market expansion strategies.
  • Competitive strategies by identifying ‘who-stands-where’ in the market.

Table of Contents

204 Pages
1. Report Summary
Current Industry Analysis and Growth Potential Outlook
Global AI in E-Commerce Market Sales Analysis - Component | Deployment Mode | Application ($ Million)
AI in E-Commerce Market Sales Performance of Top Countries
1.1. Research Methodology
Primary Research Approach
Secondary Research Approach
1.2. Market Snapshot
2. Market Overview and Insights
2.1. Scope of the Study
2.2. Analyst Insight & Current Market Trends
2.2.1. Key AI in E-Commerce Industry Trends
2.2.2. Market Recommendations
2.3. Porter's Five Forces Analysis for the AI in E-Commerce Market
2.3.1. Competitive Rivalry
2.3.2. Threat of New Entrants
2.3.3. Bargaining Power of Suppliers
2.3.4. Bargaining Power of Buyers
2.3.5. Threat of Substitutes
3. Market Determinants
3.1. Market Drivers
3.1.1. Drivers For Global AI in E-Commerce Market: Impact Analysis
3.2. Market Pain Points and Challenges
3.2.1. Restraints For Global AI in E-Commerce Market: Impact Analysis
3.3. Market Opportunities
3.3.1. Opportunities For Global AI in E-Commerce Market: Impact Analysis
4. Competitive Landscape
4.1. Competitive Dashboard - AI in E-Commerce Market Revenue and Share by Manufacturers
AI in E-Commerce Product Comparison Analysis
Top Market Player Ranking Matrix
4.2. Key Company Analysis
4.2.1. Amazon Web Services, Inc.
4.2.1.1. Overview
4.2.1.2. Product Portfolio
4.2.1.3. Financial Analysis
4.2.1.4. SWOT Analysis
4.2.1.5. Business Strategy
4.2.2. Google LLC
4.2.2.1. Overview
4.2.2.2. Product Portfolio
4.2.2.3. Financial Analysis
4.2.2.4. SWOT Analysis
4.2.2.5. Business Strategy
4.2.3. IBM Corp.
4.2.3.1. Overview
4.2.3.2. Product Portfolio
4.2.3.3. Financial Analysis
4.2.3.4. SWOT Analysis
4.2.3.5. Business Strategy
4.2.4. Microsoft Corp.
4.2.4.1. Overview
4.2.4.2. Product Portfolio
4.2.4.3. Financial Analysis
4.2.4.4. SWOT Analysis
4.2.4.5. Business Strategy
4.2.5. Salesforce, Inc.
4.2.5.1. Overview
4.2.5.2. Product Portfolio
4.2.5.3. Financial Analysis
4.2.5.4. SWOT Analysis
4.2.5.5. Business Strategy
4.3. Top Winning Strategies by Market Players
4.3.1. Merger and Acquisition
4.3.2. Product Launch
4.3.3. Partnership And Collaboration
5. Global AI in E-Commerce Market Sales Analysis By Component ($ Million)
5.1. Software
5.2. Services
6. Global AI in E-Commerce Market Sales Analysis By Deployment Mode ($ Million)
6.1. Cloud
6.2. On-Premises
7. Global AI in E-Commerce Market Sales Analysis By Application ($ Million)
7.1. Warehouse Automation
7.2. Supply Chain Analysis
7.3. Customer Relationship Management
7.4. Product Recommendation
7.5. Merchandizing
7.6. Fake Review Analysis
7.7. Customer Service
8. Regional Analysis
8.1. North American AI in E-Commerce Market Sales Analysis - Component | Deployment Mode | Application | Country ($ Million)
Macroeconomic Factors for North America
8.1.1. United States
8.1.2. Canada
8.2. European AI in E-Commerce Market Sales Analysis - Component | Deployment Mode | Application | Country ($ Million)
Macroeconomic Factors for Europe
8.2.1. UK
8.2.2. Germany
8.2.3. Italy
8.2.4. Spain
8.2.5. France
8.2.6. Russia
8.2.7. Rest of Europe
8.3. Asia-Pacific AI in E-Commerce Market Sales Analysis - Component | Deployment Mode | Application | Country ($ Million)
Macroeconomic Factors for Asia-Pacific
8.3.1. China
8.3.2. Japan
8.3.3. South Korea
8.3.4. India
8.3.5. Australia & New Zealand
8.3.6. ASEAN Countries (Thailand, Indonesia, Vietnam, Singapore, And Others)
8.3.7. Rest of Asia-Pacific
8.4. Rest of the World AI in E-Commerce Market Sales Analysis - Component | Deployment Mode | Application | Country ($ Million)
Macroeconomic Factors for the Rest of the World
8.4.1. Latin America
8.4.2. Middle East and Africa
9. Company Profiles
9.1. Accenture Plc
9.1.1. Quick Facts
9.1.2. Company Overview
9.1.3. Product Portfolio
9.1.4. Business Strategies
9.2. Adobe Systems Inc.
9.2.1. Quick Facts
9.2.2. Company Overview
9.2.3. Product Portfolio
9.2.4. Business Strategies
9.3. Algolia, Inc.
9.3.1. Quick Facts
9.3.2. Company Overview
9.3.3. Product Portfolio
9.3.4. Business Strategies
9.4. Amazon Web Services, Inc.
9.4.1. Quick Facts
9.4.2. Company Overview
9.4.3. Product Portfolio
9.4.4. Business Strategies
9.5. Bloomreach, Inc.
9.5.1. Quick Facts
9.5.2. Company Overview
9.5.3. Product Portfolio
9.5.4. Business Strategies
9.6. Capgemini Services SAS
9.6.1. Quick Facts
9.6.2. Company Overview
9.6.3. Product Portfolio
9.6.4. Business Strategies
9.7. Clerk.io ApS
9.7.1. Quick Facts
9.7.2. Company Overview
9.7.3. Product Portfolio
9.7.4. Business Strategies
9.8. Coveo Solutions, Inc.
9.8.1. Quick Facts
9.8.2. Company Overview
9.8.3. Product Portfolio
9.8.4. Business Strategies
9.9. Dynamic Yield Ltd.
9.9.1. Quick Facts
9.9.2. Company Overview
9.9.3. Product Portfolio
9.9.4. Business Strategies
9.10. Genesys Cloud Services, Inc.
9.10.1. Quick Facts
9.10.2. Company Overview
9.10.3. Product Portfolio
9.10.4. Business Strategies
9.11. Google LLC
9.11.1. Quick Facts
9.11.2. Company Overview
9.11.3. Product Portfolio
9.11.4. Business Strategies
9.12. IBM Corp.
9.12.1. Quick Facts
9.12.2. Company Overview
9.12.3. Product Portfolio
9.12.4. Business Strategies
9.13. Infosys Ltd.
9.13.1. Quick Facts
9.13.2. Company Overview
9.13.3. Product Portfolio
9.13.4. Business Strategies
9.14. Intercom, Inc.
9.14.1. Quick Facts
9.14.2. Company Overview
9.14.3. Product Portfolio
9.14.4. Business Strategies
9.15. Klaviyo
9.15.1. Quick Facts
9.15.2. Company Overview
9.15.3. Product Portfolio
9.15.4. Business Strategies
9.16. Kore.ai Inc.
9.16.1. Quick Facts
9.16.2. Company Overview
9.16.3. Product Portfolio
9.16.4. Business Strategies
9.17. Microsoft Corp.
9.17.1. Quick Facts
9.17.2. Company Overview
9.17.3. Product Portfolio
9.17.4. Business Strategies
9.18. Optimizely
9.18.1. Quick Facts
9.18.2. Company Overview
9.18.3. Product Portfolio
9.18.4. Business Strategies
9.19. Oracle Corp.
9.19.1. Quick Facts
9.19.2. Company Overview
9.19.3. Product Portfolio
9.19.4. Business Strategies
9.20. Salesforce, Inc.
9.20.1. Quick Facts
9.20.2. Company Overview
9.20.3. Product Portfolio
9.20.4. Business Strategies
9.21. SAP SE
9.21.1. Quick Facts
9.21.2. Company Overview
9.21.3. Product Portfolio
9.21.4. Business Strategies
9.22. Tata Consultancy Services Ltd.
9.22.1. Quick Facts
9.22.2. Company Overview
9.22.3. Product Portfolio
9.22.4. Business Strategies
9.23. Yellow.ai
9.23.1. Quick Facts
9.23.2. Company Overview
9.23.3. Product Portfolio
9.23.4. Business Strategies
9.24. Yotpo Ltd.
9.24.1. Quick Facts
9.24.2. Company Overview
9.24.3. Product Portfolio
9.24.4. Business Strategies
9.25. Zendesk, Inc.
9.25.1. Quick Facts
9.25.2. Company Overview
9.25.3. Product Portfolio
9.25.4. Business Strategies
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