The global AI-Based Recommendation System market size is predicted to grow from US$ 2133 million in 2025 to US$ 3363 million in 2031; it is expected to grow at a CAGR of 7.9% from 2025 to 2031.
An AI-based recommendation system is a type of software that uses artificial intelligence algorithms to analyze data on user behavior and preferences in order to suggest products, services, or content that the user is likely to be interested in. These systems are commonly used in e-commerce, entertainment, and social media platforms to enhance the user experience and increase engagement.
AI-based recommendation systems can be based on various types of algorithms, including collaborative filtering, content-based filtering, and hybrid models. Collaborative filtering analyzes user behavior and preferences to identify patterns and similarities in order to make recommendations. Content-based filtering, on the other hand, analyzes the features of products or content to recommend similar items to users based on their preferences.
Overall, AI-based recommendation systems have proved to be effective in improving user engagement, increasing sales, and reducing churn rates in various industries.
The global AI-based recommendation system market refers to the use of artificial intelligence (AI) technologies to provide personalized recommendations to individuals based on their preferences, behaviors, and historical data. AI-based recommendation systems utilize algorithms and machine learning techniques to analyze large datasets and offer suggestions for products, services, content, or actions.
The market for AI-based recommendation systems is driven by several factors:
Growing demand for personalized experiences: With the increasing volume of digital content, products, and services available, consumers are seeking personalized experiences that cater to their specific needs and preferences. AI-based recommendation systems help businesses deliver tailored recommendations, enhancing customer engagement, satisfaction, and loyalty.
Rising e-commerce and online streaming activities: The proliferation of e-commerce platforms and online streaming services has generated vast amounts of data regarding consumer preferences and behavior. AI-based recommendation systems analyze this data to provide relevant product recommendations, improve cross-selling and upselling, and enhance the overall customer shopping or content consumption experience.
Advancements in AI and machine learning technologies: The advancements in AI and machine learning algorithms have significantly improved the capabilities of recommendation systems. Deep learning techniques, natural language processing, and collaborative filtering algorithms enable more accurate and effective personalized recommendations, driving the adoption of AI-based recommendation systems across various industries.
Focus on enhancing customer engagement and retention: Businesses are increasingly recognizing the importance of customer engagement and retention for long-term success. AI-based recommendation systems help in creating personalized customer experiences, increasing customer satisfaction, and encouraging repeat purchases or usage, thereby improving customer retention rates and revenue generation.
Integration of recommendation systems in various industries: AI-based recommendation systems are employed in diverse industries, including e-commerce, media and entertainment, healthcare, banking and finance, and travel and hospitality. These systems help in suggesting relevant products, content, treatments, financial services, or travel options, catering to the specific preferences and needs of individuals in each industry.
In conclusion, the global AI-based recommendation system market is witnessing significant growth due to the increased demand for personalized experiences, the rise in e-commerce and online streaming activities, advancements in AI and machine learning technologies, and the focus on customer engagement and retention. By leveraging AI algorithms and techniques, recommendation systems improve customer experiences, drive customer loyalty, and boost business revenue. With the continuous expansion of digital content and services, the AI-based recommendation system market is expected to grow further in the coming years.The global AI-based recommendation system market refers to the use of artificial intelligence (AI) technologies to provide personalized recommendations to individuals based on their preferences, behaviors, and historical data. AI-based recommendation systems utilize algorithms and machine learning techniques to analyze large datasets and offer suggestions for products, services, content, or actions.
The market for AI-based recommendation systems is driven by several factors:
Growing demand for personalized experiences: With the increasing volume of digital content, products, and services available, consumers are seeking personalized experiences that cater to their specific needs and preferences. AI-based recommendation systems help businesses deliver tailored recommendations, enhancing customer engagement, satisfaction, and loyalty.
Rising e-commerce and online streaming activities: The proliferation of e-commerce platforms and online streaming services has generated vast amounts of data regarding consumer preferences and behavior. AI-based recommendation systems analyze this data to provide relevant product recommendations, improve cross-selling and upselling, and enhance the overall customer shopping or content consumption experience.
Advancements in AI and machine learning technologies: The advancements in AI and machine learning algorithms have significantly improved the capabilities of recommendation systems. Deep learning techniques, natural language processing, and collaborative filtering algorithms enable more accurate and effective personalized recommendations, driving the adoption of AI-based recommendation systems across various industries.
Focus on enhancing customer engagement and retention: Businesses are increasingly recognizing the importance of customer engagement and retention for long-term success. AI-based recommendation systems help in creating personalized customer experiences, increasing customer satisfaction, and encouraging repeat purchases or usage, thereby improving customer retention rates and revenue generation.
Integration of recommendation systems in various industries: AI-based recommendation systems are employed in diverse industries, including e-commerce, media and entertainment, healthcare, banking and finance, and travel and hospitality. These systems help in suggesting relevant products, content, treatments, financial services, or travel options, catering to the specific preferences and needs of individuals in each industry.
In conclusion, the global AI-based recommendation system market is witnessing significant growth due to the increased demand for personalized experiences, the rise in e-commerce and online streaming activities, advancements in AI and machine learning technologies, and the focus on customer engagement and retention. By leveraging AI algorithms and techniques, recommendation systems improve customer experiences, drive customer loyalty, and boost business revenue. With the continuous expansion of digital content and services, the AI-based recommendation system market is expected to grow further in the coming years.
The 鈥淎I-Based Recommendation System Industry Forecast鈥� looks at past sales and reviews total world AI-Based Recommendation System sales in 2024, providing a comprehensive analysis by region and market sector of projected AI-Based Recommendation System sales for 2025 through 2031. With AI-Based Recommendation System sales broken down by region, market sector and sub-sector, this report provides a detailed analysis in US$ millions of the world AI-Based Recommendation System industry.
This Insight Report provides a comprehensive analysis of the global AI-Based Recommendation System landscape and highlights key trends related to product segmentation, company formation, revenue, and market share, latest development, and M&A activity. This report also analyses the strategies of leading global companies with a focus on AI-Based Recommendation System portfolios and capabilities, market entry strategies, market positions, and geographic footprints, to better understand these firms鈥� unique position in an accelerating global AI-Based Recommendation System market.
This Insight Report evaluates the key market trends, drivers, and affecting factors shaping the global outlook for AI-Based Recommendation System and breaks down the forecast by Type, by Application, geography, and market size to highlight emerging pockets of opportunity. With a transparent methodology based on hundreds of bottom-up qualitative and quantitative market inputs, this study forecast offers a highly nuanced view of the current state and future trajectory in the global AI-Based Recommendation System.
This report presents a comprehensive overview, market shares, and growth opportunities of AI-Based Recommendation System market by product type, application, key players and key regions and countries.
Segmentation by Type:
Collaborative Filtering
Content Based Filtering
Hybrid Recommendation
Segmentation by Application:
E-commerce Platform
Online Education
Social Networking
Finance
News and Media
Health Care
Travel
Other
This report also splits the market by region:
Americas
United States
Canada
Mexico
Brazil
APAC
China
Japan
Korea
Southeast Asia
India
Australia
Europe
Germany
France
UK
Italy
Russia
Middle East & Africa
Egypt
South Africa
Israel
Turkey
GCC Countries
The below companies that are profiled have been selected based on inputs gathered from primary experts and analyzing the company's coverage, product portfolio, its market penetration.
AWS
IBM
Google
SAP
Microsoft
Salesforce
Intel
HPE
Oracle
Sentient Technologies
Netflix
Facebook
Alibaba
Huawei
Tencent
Please Note - This is an on demand report and will be delivered in 2 business days (48 hours) post payment.
1 Scope of the Report
1.1 Market Introduction
1.2 Years Considered
1.3 Research Objectives
1.4 Market Research Methodology
1.5 Research Process and Data Source
1.6 Economic Indicators
1.7 Currency Considered
1.8 Market Estimation Caveats
2 Executive Summary
2.1 World Market Overview
2.1.1 Global AI-Based Recommendation System Market Size (2020-2031)
2.1.2 AI-Based Recommendation System Market Size CAGR by Region (2020 VS 2024 VS 2031)
2.1.3 World Current & Future Analysis for AI-Based Recommendation System by Country/Region (2020, 2024 & 2031)
2.2 AI-Based Recommendation System Segment by Type
2.2.1 Collaborative Filtering
2.2.2 Content Based Filtering
2.2.3 Hybrid Recommendation
2.3 AI-Based Recommendation System Market Size by Type
2.3.1 AI-Based Recommendation System Market Size CAGR by Type (2020 VS 2024 VS 2031)
2.3.2 Global AI-Based Recommendation System Market Size Market Share by Type (2020-2025)
2.4 AI-Based Recommendation System Segment by Application
2.4.1 E-commerce Platform
2.4.2 Online Education
2.4.3 Social Networking
2.4.4 Finance
2.4.5 News and Media
2.4.6 Health Care
2.4.7 Travel
2.4.8 Other
2.5 AI-Based Recommendation System Market Size by Application
2.5.1 AI-Based Recommendation System Market Size CAGR by Application (2020 VS 2024 VS 2031)
2.5.2 Global AI-Based Recommendation System Market Size Market Share by Application (2020-2025)
3 AI-Based Recommendation System Market Size by Player
3.1 AI-Based Recommendation System Market Size Market Share by Player
3.1.1 Global AI-Based Recommendation System Revenue by Player (2020-2025)
3.1.2 Global AI-Based Recommendation System Revenue Market Share by Player (2020-2025)
3.2 Global AI-Based Recommendation System Key Players Head office and Products Offered
3.3 Market Concentration Rate Analysis
3.3.1 Competition Landscape Analysis
3.3.2 Concentration Ratio (CR3, CR5 and CR10) & (2023-2025)
3.4 New Products and Potential Entrants
3.5 Mergers & Acquisitions, Expansion
4 AI-Based Recommendation System by Region
4.1 AI-Based Recommendation System Market Size by Region (2020-2025)
4.2 Global AI-Based Recommendation System Annual Revenue by Country/Region (2020-2025)
4.3 Americas AI-Based Recommendation System Market Size Growth (2020-2025)
4.4 APAC AI-Based Recommendation System Market Size Growth (2020-2025)
4.5 Europe AI-Based Recommendation System Market Size Growth (2020-2025)
4.6 Middle East & Africa AI-Based Recommendation System Market Size Growth (2020-2025)
5 Americas
5.1 Americas AI-Based Recommendation System Market Size by Country (2020-2025)
5.2 Americas AI-Based Recommendation System Market Size by Type (2020-2025)
5.3 Americas AI-Based Recommendation System Market Size by Application (2020-2025)
5.4 United States
5.5 Canada
5.6 Mexico
5.7 Brazil
6 APAC
6.1 APAC AI-Based Recommendation System Market Size by Region (2020-2025)
6.2 APAC AI-Based Recommendation System Market Size by Type (2020-2025)
6.3 APAC AI-Based Recommendation System Market Size by Application (2020-2025)
6.4 China
6.5 Japan
6.6 South Korea
6.7 Southeast Asia
6.8 India
6.9 Australia
7 Europe
7.1 Europe AI-Based Recommendation System Market Size by Country (2020-2025)
7.2 Europe AI-Based Recommendation System Market Size by Type (2020-2025)
7.3 Europe AI-Based Recommendation System Market Size by Application (2020-2025)
7.4 Germany
7.5 France
7.6 UK
7.7 Italy
7.8 Russia
8 Middle East & Africa
8.1 Middle East & Africa AI-Based Recommendation System by Region (2020-2025)
8.2 Middle East & Africa AI-Based Recommendation System Market Size by Type (2020-2025)
8.3 Middle East & Africa AI-Based Recommendation System Market Size by Application (2020-2025)
8.4 Egypt
8.5 South Africa
8.6 Israel
8.7 Turkey
8.8 GCC Countries
9 Market Drivers, Challenges and Trends
9.1 Market Drivers & Growth Opportunities
9.2 Market Challenges & Risks
9.3 Industry Trends
10 Global AI-Based Recommendation System Market Forecast
10.1 Global AI-Based Recommendation System Forecast by Region (2026-2031)
10.1.1 Global AI-Based Recommendation System Forecast by Region (2026-2031)
10.1.2 Americas AI-Based Recommendation System Forecast
10.1.3 APAC AI-Based Recommendation System Forecast
10.1.4 Europe AI-Based Recommendation System Forecast
10.1.5 Middle East & Africa AI-Based Recommendation System Forecast
10.2 Americas AI-Based Recommendation System Forecast by Country (2026-2031)
10.2.1 United States Market AI-Based Recommendation System Forecast
10.2.2 Canada Market AI-Based Recommendation System Forecast
10.2.3 Mexico Market AI-Based Recommendation System Forecast
10.2.4 Brazil Market AI-Based Recommendation System Forecast
10.3 APAC AI-Based Recommendation System Forecast by Region (2026-2031)
10.3.1 China AI-Based Recommendation System Market Forecast
10.3.2 Japan Market AI-Based Recommendation System Forecast
10.3.3 Korea Market AI-Based Recommendation System Forecast
10.3.4 Southeast Asia Market AI-Based Recommendation System Forecast
10.3.5 India Market AI-Based Recommendation System Forecast
10.3.6 Australia Market AI-Based Recommendation System Forecast
10.4 Europe AI-Based Recommendation System Forecast by Country (2026-2031)
10.4.1 Germany Market AI-Based Recommendation System Forecast
10.4.2 France Market AI-Based Recommendation System Forecast
10.4.3 UK Market AI-Based Recommendation System Forecast
10.4.4 Italy Market AI-Based Recommendation System Forecast
10.4.5 Russia Market AI-Based Recommendation System Forecast
10.5 Middle East & Africa AI-Based Recommendation System Forecast by Region (2026-2031)
10.5.1 Egypt Market AI-Based Recommendation System Forecast
10.5.2 South Africa Market AI-Based Recommendation System Forecast
10.5.3 Israel Market AI-Based Recommendation System Forecast
10.5.4 Turkey Market AI-Based Recommendation System Forecast
10.6 Global AI-Based Recommendation System Forecast by Type (2026-2031)
10.7 Global AI-Based Recommendation System Forecast by Application (2026-2031)
10.7.1 GCC Countries Market AI-Based Recommendation System Forecast
11 Key Players Analysis
11.1 AWS
11.1.1 AWS Company Information
11.1.2 AWS AI-Based Recommendation System Product Offered
11.1.3 AWS AI-Based Recommendation System Revenue, Gross Margin and Market Share (2020-2025)
11.1.4 AWS Main Business Overview
11.1.5 AWS Latest Developments
11.2 IBM
11.2.1 IBM Company Information
11.2.2 IBM AI-Based Recommendation System Product Offered
11.2.3 IBM AI-Based Recommendation System Revenue, Gross Margin and Market Share (2020-2025)
11.2.4 IBM Main Business Overview
11.2.5 IBM Latest Developments
11.3 Google
11.3.1 Google Company Information
11.3.2 Google AI-Based Recommendation System Product Offered
11.3.3 Google AI-Based Recommendation System Revenue, Gross Margin and Market Share (2020-2025)
11.3.4 Google Main Business Overview
11.3.5 Google Latest Developments
11.4 SAP
11.4.1 SAP Company Information
11.4.2 SAP AI-Based Recommendation System Product Offered
11.4.3 SAP AI-Based Recommendation System Revenue, Gross Margin and Market Share (2020-2025)
11.4.4 SAP Main Business Overview
11.4.5 SAP Latest Developments
11.5 Microsoft
11.5.1 Microsoft Company Information
11.5.2 Microsoft AI-Based Recommendation System Product Offered
11.5.3 Microsoft AI-Based Recommendation System Revenue, Gross Margin and Market Share (2020-2025)
11.5.4 Microsoft Main Business Overview
11.5.5 Microsoft Latest Developments
11.6 Salesforce
11.6.1 Salesforce Company Information
11.6.2 Salesforce AI-Based Recommendation System Product Offered
11.6.3 Salesforce AI-Based Recommendation System Revenue, Gross Margin and Market Share (2020-2025)
11.6.4 Salesforce Main Business Overview
11.6.5 Salesforce Latest Developments
11.7 Intel
11.7.1 Intel Company Information
11.7.2 Intel AI-Based Recommendation System Product Offered
11.7.3 Intel AI-Based Recommendation System Revenue, Gross Margin and Market Share (2020-2025)
11.7.4 Intel Main Business Overview
11.7.5 Intel Latest Developments
11.8 HPE
11.8.1 HPE Company Information
11.8.2 HPE AI-Based Recommendation System Product Offered
11.8.3 HPE AI-Based Recommendation System Revenue, Gross Margin and Market Share (2020-2025)
11.8.4 HPE Main Business Overview
11.8.5 HPE Latest Developments
11.9 Oracle
11.9.1 Oracle Company Information
11.9.2 Oracle AI-Based Recommendation System Product Offered
11.9.3 Oracle AI-Based Recommendation System Revenue, Gross Margin and Market Share (2020-2025)
11.9.4 Oracle Main Business Overview
11.9.5 Oracle Latest Developments
11.10 Sentient Technologies
11.10.1 Sentient Technologies Company Information
11.10.2 Sentient Technologies AI-Based Recommendation System Product Offered
11.10.3 Sentient Technologies AI-Based Recommendation System Revenue, Gross Margin and Market Share (2020-2025)
11.10.4 Sentient Technologies Main Business Overview
11.10.5 Sentient Technologies Latest Developments
11.11 Netflix
11.11.1 Netflix Company Information
11.11.2 Netflix AI-Based Recommendation System Product Offered
11.11.3 Netflix AI-Based Recommendation System Revenue, Gross Margin and Market Share (2020-2025)
11.11.4 Netflix Main Business Overview
11.11.5 Netflix Latest Developments
11.12 Facebook
11.12.1 Facebook Company Information
11.12.2 Facebook AI-Based Recommendation System Product Offered
11.12.3 Facebook AI-Based Recommendation System Revenue, Gross Margin and Market Share (2020-2025)
11.12.4 Facebook Main Business Overview
11.12.5 Facebook Latest Developments
11.13 Alibaba
11.13.1 Alibaba Company Information
11.13.2 Alibaba AI-Based Recommendation System Product Offered
11.13.3 Alibaba AI-Based Recommendation System Revenue, Gross Margin and Market Share (2020-2025)
11.13.4 Alibaba Main Business Overview
11.13.5 Alibaba Latest Developments
11.14 Huawei
11.14.1 Huawei Company Information
11.14.2 Huawei AI-Based Recommendation System Product Offered
11.14.3 Huawei AI-Based Recommendation System Revenue, Gross Margin and Market Share (2020-2025)
11.14.4 Huawei Main Business Overview
11.14.5 Huawei Latest Developments
11.15 Tencent
11.15.1 Tencent Company Information
11.15.2 Tencent AI-Based Recommendation System Product Offered
11.15.3 Tencent AI-Based Recommendation System Revenue, Gross Margin and Market Share (2020-2025)
11.15.4 Tencent Main Business Overview
11.15.5 Tencent Latest Developments
12 Research Findings and Conclusion
听
听
*If Applicable.