Asia-Pacific AI in E-Commerce Market 2025-2035

Description

List of Tables

Asia-Pacific 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 (2025-2035)

Industry Overview

Asia-Pacific AI in e-commerce market was valued at $2.2 billion in 2024 and is projected to reach $12.0 billion by 2035, growing at a CAGR of 16.8% during the forecast period (2025-2035). The growing digital payments, along with fintech integration, are expected to propel the growth of AI adoption in e-commerce. The consumers' shift from traditional payment methods towards digital wallets, UPI, QR-code payments, and buy-now-pay-later options further contributes growth of the market during the forecast period. The e-commerce market players are adopting AI technologies to secure these payment methods and to detect fraud in real time. These organizations are analyzing payment patterns to integrate a seamless checkout experience. For instance, according to the Economic Times, Unified Payment Interface (UPI), in December 2024, UPI transactions marked a new record and grew by 16.73 billion. This was the rise from 15.48 billion in November 2024. This continuous month-on-month growth is highlighting India's shift from traditional payment methods to digital payments.

Market Dynamics

AI-Driven Recommendations Personalize Shopping, Boosting Customer Engagement

The growing demand for personalized shopping experiences through AI-driven recommendations is expected to drive AI in the e-commerce market in the region. The adoption of personalized shopping experiences is to enhancing customer engagement, along with increasing conversion rates, average order values, and long-term customer loyalty. For instance, in June 2024, Taobao and Tmall announced that they are upgrading consumer shopping support through AI. The integration of AI is to better engage and serve shoppers. Through this AI support, the company will boost operating efficiency for merchants. TTG platforms have unveiled a suite of AI-powered tools from personalized consumer-facing chatbots to visual generation applications for merchants.

Adoption of Chatbots and Virtual Assistants is Enhancing Customer Support in Online Shopping

The growing adoption of chatbots and virtual assistants to enhance customer support is driving the growth of AI in the e-commerce market in the region. These AI-powered tools provide 24/7 assistance, handle large volumes of queries simultaneously, and offer instant solutions to common issues such as order tracking, returns, or product inquiries. For instance, in December 2024, Lazada implemented an AI-powered virtual assistant called AI Lazzie. The company's virtual assistant acts as a virtual shopping assistant and provides tailored recommendations and seamless support.

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 all the applications, product recommendations are expected to hold the largest share in the Asia-Pacific AI in e-commerce market. AI-powered product recommendation enhances personalization, increasing customer engagement, boosting conversion rates, and supporting higher sales revenue. For instance, in August 2025, Amazon launched Rufus, a new generative AI-powered conversational shopping assistant, in India. The conversational AI assistant can answer customer questions on shopping needs, products, and comparisons. The AI assistant can make product recommendations based on the context, and can facilitate product discovery in the same Amazon shopping experience customers use regularly.

Software: A Key Segment in Market Growth

In the Asia-Pacific AI in e-commerce market, the software segment is expected to play a key role as it powers the core engines, models, and applications that drive AI capabilities across the sector, with its scalability through licensing, subscription, and SaaS models making it a strong recurring revenue driver and fuelling market growth during the forecast period.

Regional Outlook

The Asia-Pacific AI in e-commerce market is further divided by countries, including India, China, South Korea, ASEAN, Australia and New Zealand, Japan, and the Rest of Asia-Pacific.

China Dominates the Market with a Major Share

Among all regions, China is expected to dominate the Asia-Pacific AI in the e-commerce market during the forecast period. The growth is majorly driven by its advanced digital infrastructure, presence of key e-commerce platforms, and extensive adoption of AI technologies in the country. For instance, in August 2025, Glance AI launched an AI commerce platform in partnership with Sharp's Flagship AQUOS R10 smartphones. Sharp, the company, debuted an AI-powered shopping experience on the new AQUOS R10 SH-M31 smartphone.

Market Players Outlook

Key companies in the Asia-Pacific AI in e-commerce market, including Amazon Web Services, Adobe, Appier, Google, IBM, Jio Haptik, Salesforce, ViSenze, Oracle, Infosys, Yellow.ai, Microsoft, SenseTime, and Tata Consultancy Services, are advancing the market by pursuing collaborations, partnerships, and acquisitions to enhance AI capabilities, broaden product offerings, promote sustainability, and meet rising demand for personalized, efficient, and high-performing e-commerce solutions across retail and customer experience channels.

Recent Developments

In April 2025, Glu, an AI-powered platform, launched in APAC to streamline e-commerce content production. The platform aims to address creative challenges within e-commerce businesses by leveraging generative AI to automate repetitive tasks, provide intelligent recommendations, and simplify the content production process from creation to publication. Glu also integrates with other shopping platforms such as Shopify, Facebook, Instagram, TikTok, Pinterest, Google Ads, and Mailchimp. This integration is designed to streamline workflows for e-commerce businesses, enabling them to manage their creative content across multiple channels more efficiently.

The Report Covers:

Market value data analysis of 2024 and forecast to 2035.
Annualized market revenues ($ million) for each market segment.
Country-wise analysis of major geographical regions.
Key companies operating in the Asia-Pacific 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.

Product Code: OMR2023176

1. Report Summary

Current Industry Analysis and Growth Potential Outlook
Asia-Pacific AI in E-Commerce Market Sales Analysis - Component | Mode | Application ($ Million)
Asia-Pacific 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 Asia-Pacific AI in E-Commerce Industry Trends
- 2.2.2. Market Recommendations

3. Market Determinants

3.1. Market Drivers
- 3.1.1. Drivers For Asia-Pacific AI in E-Commerce Market: Impact Analysis
3.2. Market Pain Points and Challenges
- 3.2.1. Restraints For Asia-Pacific AI in E-Commerce Market: Impact Analysis
3.3. Market Opportunities
- 3.3.1. Opportunities For Asia-Pacific AI in E-Commerce Market: Impact Analysis

4. Competitive Landscape

4.1. Competitive Dashboard - Asia-Pacific 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. Asia-Pacific AI in E-Commerce Market Sales Analysis by Component ($ Million)

5.1. Software
5.2. Services

6. Asia-Pacific AI in E-Commerce Market Sales Analysis by Deployment Mode ($ Million)

6.1. Cloud
6.2. On-Premises

7. Asia-Pacific 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. Asia-Pacific AI in E-Commerce Market Sales Analysis - Component | Mode | Application | Country ($ Million)
Macroeconomic Factors for Asia-Pacific
- 8.1.1. China
- 8.1.2. Japan
- 8.1.3. India
- 8.1.4. South Korea
- 8.1.5. ASEAN Economies
- 8.1.6. Australia and New Zealand
- 8.1.7. Rest of Asia-Pacific

9. Company Profiles

9.1. ABEJA, Inc.
- 9.1.1. Quick Facts
- 9.1.2. Company Overview
- 9.1.3. Product Portfolio
- 9.1.4. Business Strategies
9.2. Adobe Inc.
- 9.2.1. Quick Facts
- 9.2.2. Company Overview
- 9.2.3. Product Portfolio
- 9.2.4. Business Strategies
9.3. Advance Intelligence Pte. Ltd.
- 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. Appier, Inc.
- 9.5.1. Quick Facts
- 9.5.2. Company Overview
- 9.5.3. Product Portfolio
- 9.5.4. Business Strategies
9.6. Bitonic Technology Labs Inc. (Yellow.ai)
- 9.6.1. Quick Facts
- 9.6.2. Company Overview
- 9.6.3. Product Portfolio
- 9.6.4. Business Strategies
9.7. Google LLC
- 9.7.1. Quick Facts
- 9.7.2. Company Overview
- 9.7.3. Product Portfolio
- 9.7.4. Business Strategies
9.8. Gupshup, Inc.
- 9.8.1. Quick Facts
- 9.8.2. Company Overview
- 9.8.3. Product Portfolio
- 9.8.4. Business Strategies
9.9. Jio Haptik Technologies Ltd.
- 9.9.1. Quick Facts
- 9.9.2. Company Overview
- 9.9.3. Product Portfolio
- 9.9.4. Business Strategies
9.10. HashMicro Pte Ltd.
- 9.10.1. Quick Facts
- 9.10.2. Company Overview
- 9.10.3. Product Portfolio
- 9.10.4. Business Strategies
9.11. IBM Corp.
- 9.11.1. Quick Facts
- 9.11.2. Company Overview
- 9.11.3. Product Portfolio
- 9.11.4. Business Strategies
9.12. Infosys Ltd.
- 9.12.1. Quick Facts
- 9.12.2. Company Overview
- 9.12.3. Product Portfolio
- 9.12.4. Business Strategies
9.13. Kata.ai
- 9.13.1. Quick Facts
- 9.13.2. Company Overview
- 9.13.3. Product Portfolio
- 9.13.4. Business Strategies
9.14. Mad Street Den, Inc.
- 9.14.1. Quick Facts
- 9.14.2. Company Overview
- 9.14.3. Product Portfolio
- 9.14.4. Business Strategies
9.15. Beijing Kuangshi Technology Co., Ltd.
- 9.15.1. Quick Facts
- 9.15.2. Company Overview
- 9.15.3. Product Portfolio
- 9.15.4. Business Strategies
9.16. Microsoft Corp.
- 9.16.1. Quick Facts
- 9.16.2. Company Overview
- 9.16.3. Product Portfolio
- 9.16.4. Business Strategies
9.17. NexMind AI Pte Ltd.
- 9.17.1. Quick Facts
- 9.17.2. Company Overview
- 9.17.3. Product Portfolio
- 9.17.4. Business Strategies
9.18. Nodeflux Teknologi Indonesia
- 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. SenseTime Technology Development Co., Ltd.
- 9.22.1. Quick Facts
- 9.22.2. Company Overview
- 9.22.3. Product Portfolio
- 9.22.4. Business Strategies
9.23. SleekFlow Technologies Ltd.
- 9.23.1. Quick Facts
- 9.23.2. Company Overview
- 9.23.3. Product Portfolio
- 9.23.4. Business Strategies
9.24. Tata Consultancy Services Ltd.
- 9.24.1. Quick Facts
- 9.24.2. Company Overview
- 9.24.3. Product Portfolio
- 9.24.4. Business Strategies
9.25. Trax Technology Solutions Pte. Ltd.
- 9.25.1. Quick Facts
- 9.25.2. Company Overview
- 9.25.3. Product Portfolio
- 9.25.4. Business Strategies
9.26. Netcore Unbxd
- 9.26.1. Quick Facts
- 9.26.2. Company Overview
- 9.26.3. Product Portfolio
- 9.26.4. Business Strategies
9.27. ViSenze Pte Ltd.
- 9.27.1. Quick Facts
- 9.27.2. Company Overview
- 9.27.3. Product Portfolio
- 9.27.4. Business Strategies
9.28. Wipro Ltd.
- 9.28.1. Quick Facts
- 9.28.2. Company Overview
- 9.28.3. Product Portfolio
- 9.28.4. Business Strategies