AI In E-commerce Market Size, Share, Opportunities, And Trends By Application (Personalization, Customer Service, Supply Chain Optimization, Fraud Prevention), By Offering (B2B, B2C, C2C, Omnichannel), By End-Users (Food And Beverages, Fashion & Apparel, Retail, Healthcare, Others), And By Geography - Forecasts From 2024 To 2029

  • Published : Mar 2024
  • Report Code : KSI061616790
  • Pages : 140

The AI in e-commerce market is anticipated to grow significantly over the forecast period.

AI in the e-commerce market refers to the use of artificial intelligence (AI) technology and techniques in the e-commerce industry to improve different elements of online shopping experiences, operations, and performance.

Some of the key aspects of AI e-commerce are personalization, chatbots and virtual assistants, predictive analytics, and dynamic pricing. AI algorithms analyze user data, browsing history, and purchasing habits to give personalized product suggestions, tailored promotions, and tailored shopping experiences. This enables e-commerce organizations to improve consumer engagement, raise conversion rates, and boost revenues.

AI-powered chatbots and virtual assistants automate customer service, answer questions, help with product searches, and provide seamless communication across the customer experience. This improves the customer experience, decreases response times, and cuts operating expenses for e-commerce firms.

AI-powered predictive analytics forecasts customer demand, optimizes inventory management, and detects e-commerce data trends and patterns. E-commerce organizations may use historical data and market patterns to make data-driven choices, reduce stockouts, and increase supply chain efficiency.

AI algorithms use market dynamics, competitive pricing, and consumer demand to optimize product prices in real-time. Dynamic pricing solutions enable e-commerce organizations to increase revenue, improve competitiveness, and adapt swiftly to market changes.

AI e-commerce solutions optimize operations, improve consumer experiences, and drive development in a competitive online marketplace, therefore changing the future of e-commerce and fostering innovation.

Market Drivers

  • Rising personalized shopping experiences is contributing to the AI in e-commerce market growth

AI-powered recommendation engines use user data and behavior to provide personalized product suggestions. This increases user engagement and conversion rates. Personalized shopping experiences contribute significantly to the AI e-commerce industry expansion by boosting customer engagement, conversion rates, and brand loyalty.

Among various services available in the market, ZBrain is a full-stack, generative AI platform for creating bespoke apps powered by LLMs trained on corporate data. ZBrain's practical solutions can help you simplify your operations by automating tasks, improving customer interactions, and making better decisions.

Overall, personalized shopping experiences enabled by AI improve consumer happiness, sales, and the overall e-commerce sector growth. As technology advances, the role of personalization in e-commerce is expected to grow more complex, providing increasingly individualized and relevant experiences for online buyers.

  • Inventory management and demand forecasting are contributing to the AI in e-commerce market growth

AI analytics optimize inventory management and demand forecasting, minimizing stockouts and reducing excess inventory costs.

One of the products, Commerce AI, gives merchandisers simple access to AI capabilities and intuitive tools, which improves their efficiency and sales. Commerce concierge integrates with messaging applications, allowing for natural language, image-based, and data-driven interactions that improve product searches, deliver personalized replies, and speed transactions.

Inventory management and demand forecasting enabled by AI are critical drivers of development in the e-commerce business. AI technologies help e-commerce firms succeed and grow by optimizing inventory levels, boosting supply chain efficiency, increasing customer happiness, and allowing for data-driven decision-making.

Market Restraints

  • Integration challenges hamper the market growth

Integrating AI technology into current e-commerce platforms and processes may be complicated and time-consuming. Legacy systems may be incompatible with contemporary AI solutions, necessitating costly and disruptive system updates or customizations. Integration issues might cause delays in the execution of AI projects and raise project costs, impeding the AI e-commerce market growth.

AI in the e-commerce market is segmented based on different types of offerings

AI in the e-commerce market is segmented based on different types of offerings. B2B e-commerce involves commercial transactions, and AI technologies help to improve supply chain management, procurement procedures, and relationships. Predictive analytics, personalized suggestions, and automated inventory management systems are among the solutions available to improve the customer experience.

B2C e-commerce refers to online transactions between businesses and customers, with AI technology used to improve customer experience, personalize product suggestions, and optimize marketing tactics via chatbots, recommendation engines, and predictive analytics.

Consumer-to-consumer e-commerce refers to online transactions between consumers selling items or services. AI technologies enable peer-to-peer transactions, build trust, and improve user experiences. Fraud detection algorithms, reputation systems, and virtual customer care agents are all possible solutions.

Omnichannel e-commerce blends numerous channels and touchpoints to provide a seamless purchasing experience. AI technology provides for data integration, real-time inventory management, and personalized consumer experiences. CRM systems, inventory optimization algorithms, and analytics platforms are examples of omnichannel e-commerce solutions.

North America is anticipated to hold a significant share of AI in the e-commerce market.

The North American region is expected to have a significant proportion of the AI e-commerce market. North America is noted for its strong emphasis on technology innovation, with several top tech businesses and startups headquartered in the area, including IBM, Salesforce, Meta, and Google. This environment encourages the development and application of AI technology across a variety of businesses, including e-commerce.

North America has a sophisticated digital infrastructure, which includes high-speed internet access, widespread smartphone use, and advanced payment methods. These aspects facilitate the adoption of AI-powered e-commerce solutions by both enterprises and consumers.

The North American market accounts for a sizable percentage of worldwide e-commerce activity, to a huge online shopping population and a booming digital economy. This opens up several chances for AI e-commerce solution providers to target and grab market share in the region.

Key Developments

  • June 2022 - Zoovu, an AI-powered e-commerce platform, secured $169 million, backed by FTV Capital. The funds would have been utilized to expand Zoovu's US go-to-market strategy and data-driven product platform, which would improve the e-commerce experience and enable companies to assist shoppers in making purchasing decisions.
  • July 2021- LivePerson, a worldwide pioneer in conversational AI, acquired German business e-bot7, boosting its self-service capabilities and expanding across Europe. The purchase allowed LivePerson to collaborate with creative businesses to develop personalized interactions for sales, marketing, and customer service.

Company Products

  • Virto Start – Virto Start™ offers Enterprise-grade B2B technology on a mid-sized budget, with extensibility and functionality to establish a digital solution. It contains a pre-built storefront and themes for easy commerce experiences. A specialized digital professional offers a road map and plan.
  • Toloka e-commerce AI – Toloka's ML models and data labeling platform enable organizations to use AI systems to improve consumer interactions and shopping experiences, providing a competitive advantage and increasing customer retention.

Market Segmentation

  • By Application
    • Personalization
    • Customer Service
    • Supply Chain Optimization
    • Fraud Prevention
  • By Offering
    • B2B
    • B2C
    • C2C
    • Omnichannel
  • By End-Users
    • Food and Beverages
    • Fashion & Apparel
    • Retail
    • Healthcare
    • Others
  • By Geography
    • North America
      • USA
      • Canada
      • Mexico
    • South America
      • Brazil
      • Argentina
      • Others
    • Europe
      • Germany
      • France
      • UK
      • Spain
      • Others
    • Middle East and Africa
      • Saudi Arabia
      • UAE
      • Israel
      • Others
    • Asia Pacific
      • China
      • Japan
      • India
      • South Korea
      • Indonesia
      • Taiwan
      • Others


1.1. Market Overview

1.2. Market Definition

1.3. Scope of the Study

1.4. Market Segmentation

1.5. Currency

1.6. Assumptions

1.7. Base, and Forecast Years Timeline

1.8. Key benefits to the stakeholder


2.1. Research Design

2.2. Research Process


3.1. Key Findings

3.2. Analyst View


4.1. Market Drivers

4.2. Market Restraints

4.3. Porter’s Five Forces Analysis

4.3.1. Bargaining Power of Suppliers

4.3.2. Bargaining Power of Buyers

4.3.3. Threat of New Entrants

4.3.4. Threat of Substitutes

4.3.5. Competitive Rivalry in the Industry

4.4. Industry Value Chain Analysis

4.5. Analyst View


5.1. Introduction

5.2. Personalization

5.2.1. Market opportunities and trends

5.2.2. Growth prospects

5.2.3. Geographic lucrativeness 

5.3. Customer Service

5.3.1. Market opportunities and trends

5.3.2. Growth prospects

5.3.3.  Geographic lucrativeness 

5.4. Supply Chain Optimization

5.4.1. Market opportunities and trends

5.4.2. Growth prospects

5.4.3. Geographic lucrativeness 

5.5. Fraud Prevention

5.5.1. Market opportunities and trends

5.5.2. Growth prospects

5.5.3. Geographic lucrativeness 


6.1. Introduction

6.2. B2B

6.2.1. Market opportunities and trends

6.2.2. Growth prospects

6.2.3. Geographic lucrativeness 

6.3. B2C

6.3.1. Market opportunities and trends

6.3.2. Growth prospects

6.4. C2C

6.4.1. Market opportunities and trends

6.4.2. Growth prospects

6.4.3. Geographic lucrativeness 

6.5. Omnichannel

6.5.1. Market opportunities and trends

6.5.2. Growth prospects

6.5.3. Geographic lucrativeness 


7.1. Introduction

7.2. Food and Beverages

7.2.1. Market opportunities and trends

7.2.2. Growth prospects

7.2.3. Geographic lucrativeness 

7.3.  Fashion & Apparel

7.3.1. Market opportunities and trends

7.3.2. Growth prospects

7.3.3. Geographic lucrativeness 

7.4. Retail

7.4.1. Market opportunities and trends

7.4.2. Growth prospects

7.4.3. Geographic lucrativeness 

7.5. Healthcare

7.5.1. Market opportunities and trends

7.5.2. Growth prospects

7.5.3. Geographic lucrativeness 

7.6. Others

7.6.1. Market opportunities and trends

7.6.2. Growth prospects

7.6.3. Geographic lucrativeness 


8.1. Introduction

8.2. North America

8.2.1. By Application

8.2.2. By Offering

8.2.3. By End-user

8.2.4. By Country United States Market Trends and Opportunities Growth Prospects Canada Market Trends and Opportunities Growth Prospects Mexico Market Trends and Opportunities Growth Prospects

8.3. South America

8.3.1. By Application

8.3.2. By Offering

8.3.3. By End-user

8.3.4. By Country Brazil Market Trends and Opportunities Growth Prospects Argentina Market Trends and Opportunities Growth Prospects Others Market Trends and Opportunities Growth Prospects

8.4. Europe

8.4.1. By Application

8.4.2. By Offering

8.4.3. By End-user

8.4.4. By Country Germany Market Trends and Opportunities Growth Prospects France Market Trends and Opportunities Growth Prospects United Kingdom Market Trends and Opportunities Growth Prospects Spain Market Trends and Opportunities Growth Prospects Others Market Trends and Opportunities Growth Prospects

8.5. Middle East and Africa

8.5.1. By Application

8.5.2. By Offering

8.5.3. By End-user

8.5.4. By Country Saudi Arabia Market Trends and Opportunities Growth Prospects UAE Market Trends and Opportunities Growth Prospects Israel Market Trends and Opportunities Growth Prospects Others Market Trends and Opportunities Growth Prospects

8.6. Asia Pacific

8.6.1. By Application

8.6.2. By Offering

8.6.3. By End-user

8.6.4. By Country China Market Trends and Opportunities Growth Prospects Japan Market Trends and Opportunities Growth Prospects India Market Trends and Opportunities Growth Prospects South Korea Market Trends and Opportunities Growth Prospects Indonesia Market Trends and Opportunities Growth Prospects Taiwan Market Trends and Opportunities Growth Prospects Others Market Trends and Opportunities Growth Prospects


9.1. Major Players and Strategy Analysis

9.2. Market Share Analysis

9.3. Mergers, Acquisition, Agreements, and Collaborations

9.4. Competitive Dashboard


10.1. BigCommerce Pty. Ltd

10.2. Salesforce

10.3. Appinventiv

10.4. Kyndru

10.5. LeewayHertz.

10.6. Kyndryl

10.7. AltexSoft

10.8. Toloka

10.9. Virto Commerce

10.10. JR E-commerce

BigCommerce Pty. Ltd








Virto Commerce

JR E-commerce