AI 기반 콘텐츠 맞춤화 : 시장 점유율 분석, 업계 동향 및 통계, 성장 예측(2026-2031년)

According to Mordor Intelligence, the AI content personalization market size is projected to expand from USD 1.49 billion in 2025 and USD 1.83 billion in 2026 to USD 4.75 billion by 2031, registering a CAGR of 20.98% between 2026 and 2031.

This report is Segmented by Application (Content Recommendation, Marketing and Advertising Personalization, Customer Experience Personalization, Audience Analytics, and Other Applications), End User (Streaming Platforms, Broadcaster and Cable Networks, Telecom Operators, Digital Platforms, and Other End Users), and Geography. The Market Forecasts Provided in Terms of Value (USD).

Global AI Content Personalization Market Trends and Insights

Rising Demand for Hyper-Personalized Viewer Journeys

Catalog growth is making generic content carousels less useful for many viewers, especially when several services compete for the same attention. Deloitte's 2026 survey found that 22% of fans would use streaming video services more if they offered generative AI-based recommendations. Nearly 30% of respondents also wanted a personalized digest that combined streaming, social, and intellectual-property news. The underlying business case is strongest when recommendations help viewers complete more of the content they begin. Localized models can also give regional services a stronger basis for competing when language, viewing habits, and catalog preferences differ from those in Western training data. This makes the AI content personalization market important to services seeking to protect engagement as their libraries become broader and more varied.

GenAI-Assisted Creative and Row Generation

Generative AI is moving from an experimental feature toward a practical way to build streaming homepages. Netflix's GenPage uses viewing history and request context to generate rows, entities, and page layouts into a single, structured output. Netflix reported a 20% reduction in end-to-end serving latency and a statistically significant improvement in its core engagement metric during online A/B testing. Its offline work also found that prompt enrichment reduced the weighted binary classification loss by 6.9%, outperforming simply scaling model capacity. These approaches allow services to tailor row names, artwork, and page structure without depending on a separate human editorial process for every variation. The artificial intelligence (AI) content personalization market therefore benefits as operators seek more detailed personalization without slower page load times.

Data Residency and Consent Complexity

Data residency and consent requirements can limit the behavioral information available to personalization systems. The European Data Protection Board's 2025 guidance on the Digital Services Act and GDPR states that tracking-based profiling requires explicit consent and that recommender systems must provide non-profiling options. Operators that rely only on consented first-party signals can have less data for training than systems built on broader behavioral graphs. A study of GDPR-compliant recommender systems found that, on average, more than 30 user interactions were needed before compelling predictions could be generated. The AI content personalization market can face a longer cold-start period for new users and create a greater burden for operators entering additional jurisdictions. The AI content personalization market must therefore support useful experiences while allowing customers to make meaningful privacy choices.

Other drivers and restraints analyzed in the detailed report include:

1. Expansion of Real-Time Behavioral Decisioning
2. Rapid Adoption of Hybrid Recommendation Architectures
3. High Integration Effort Across CMS, CRM, CDP, and Ad Tech Stacks

For complete list of drivers and restraints, kindly check the Table Of Contents.

Segment Analysis

Content recommendation accounted for 34.04% of the AI content personalization market size in 2025. Its position reflects the value of accumulated interaction data, because each additional session can strengthen collaborative filtering signals. That data advantage can make it more difficult for later entrants to match established recommendation quality. Customer experience personalization is projected to grow at a CAGR of 21.08% from 2026 to 2031. This shift reflects a move from standalone content rows to session-wide adjustments across homepages, navigation, and search. Netflix's GenPage illustrates page-level generation, while Adobe's CX Enterprise represents a broader approach to customer experience orchestration. The AI content personalization market is moving toward a broader definition of personalization that encompasses the surrounding experience rather than just the title selected for a viewer.

Marketing and advertising personalization also benefits from the growing use of consent-based first-party signals as third-party cookie pools become less central. Taboola's Realize+ uses a decision engine for cross-campaign budget decisions and an element generator for creative and targeting optimization. Audience analytics supports these applications by gathering signals and feeding them back into the optimization process. It is consequently an enabling layer rather than a separate experience for many buyers. Other applications include voice assistant personalization and interactive content adaptation, which remain less developed at a commercial scale. Connected television settings may provide rich behavioral signals beyond traditional screen sessions. The AI content personalization industry can also serve enterprise learning, healthcare content portals, and financial services, where streaming-derived methods may support higher-value engagements. These adjacent uses broaden the commercial role of core personalization capabilities.

Complete Report Scope:

• By Application
  • Content Recommendation
  • Marketing and Advertising Personalization
  • Customer Experience Personalization
  • Audience Analytics
  • Other Applications
• By End User
  • Streaming Platforms
  • Broadcaster and Cable Networks
  • Telecom Operators
  • Digital Platforms
  • Other End Users
• By Geography
  • North America
    • United States
    • Canada
    • Mexico
  • South America
    • Brazil
    • Argentina
    • Chile
    • Rest of South America
  • Europe
    • Germany
    • United Kingdom
    • France
    • Italy
    • Spain
    • Rest of Europe
  • Asia-Pacific
    • China
    • Japan
    • India
    • South Korea
    • Australia
    • Rest of Asia-Pacific
  • Middle East
    • Saudi Arabia
    • United Arab Emirates
    • Qatar
    • Rest of Middle East
  • Africa
    • South Africa
    • Egypt
    • Nigeria
    • Rest of Africa

Geography Analysis

North America held 42.76% share of the regional total in 2025. The region benefits from concentrated technology research and development spending and large subscription video revenue pools. Deloitte reported that nearly 90% of US households subscribed to an average of 4 subscription video services. In this mature AI content personalization market, engagement quality and retention are central competitive issues. Programmatic advertising systems also support closer links between personalized discovery and advertising yield.

Asia-Pacific is projected to be the fastest-growing region, with a CAGR of 21.73% from 2026 to 2031. Growth is supported by expanding OTT services in India, South Korea, Japan, and Australia, as well as by stronger AI engineering capabilities across the region. Media Partners Asia projected that India will surpass China as the largest subscription video market by 2030, with 358 million individual subscriptions. India presents a demanding localization setting because regional-language viewing accounts for a major share of OTT consumption. AI systems are being used for subtitles, electronic program guide descriptions, and caption translation across Indian languages. China's domestic video platforms are also developing generative recommendation and live-streaming personalization systems that could compete in South and Southeast Asia.

Europe and South America were the third- and fourth-largest regional markets, respectively. European adoption is moderated by privacy and transparency requirements, although Germany and the United Kingdom remain important centers for privacy-compliant personalization. A 2025 BVDW study found that 41% of German internet users were willing to share their usage data to improve content recommendations. South America, led by Brazil, is building personalization capacity alongside OTT expansion and local-language programming. The Middle East and Africa remain early-stage markets, though media digitalization in Saudi Arabia and broader OTT adoption in South Africa support longer-term demand. These regional differences require the artificial intelligence (AI) content personalization market to combine localization, data governance, and operational simplicity.

1. Netflix, Inc.
2. Amazon.com, Inc.
3. Alphabet Inc.
4. Adobe Inc.
5. International Business Machines Corporation
6. Salesforce, Inc.
7. Oracle Corporation
8. Sitecore A/S
9. Bloomreach, Inc.
10. Taboola.com Ltd.
11. Outbrain Inc.
12. Revcontent, Inc.
13. ThinkAnalytics Ltd.
14. Kaltura, Inc.
15. Brightcove Inc.
16. Viaccess-Orca
17. Dynamic Yield (Mastercard)
18. Wurl, LLC
19. ContentWise S.r.l.
20. Personyze Ltd.

Additional Benefits:

• The market estimate (ME) sheet in Excel format
• 3 months of analyst support

TABLE OF CONTENTS

1 INTRODUCTION

• 1.1 Study Assumptions and Market Definition
• 1.2 Scope of the Study

2 RESEARCH METHODOLOGY

3 EXECUTIVE SUMMARY

4 MARKET LANDSCAPE

• 4.1 Market Overview
• 4.2 Market Drivers
  • 4.2.1 Rising Demand for Hyper-Personalized Viewer Journeys
  • 4.2.2 Expansion of Real-Time Behavioral Decisioning
  • 4.2.3 Rapid Adoption of Hybrid Recommendation Architectures
  • 4.2.4 Growing Need to Monetize Long-Tail Content Catalogs
  • 4.2.5 Demand for Privacy-First Personalization Architectures
  • 4.2.6 GenAI-Assisted Creative and Row Generation
• 4.3 Market Restraints
  • 4.3.1 Cold-Start Accuracy Gaps for New Users and New Titles
  • 4.3.2 Data Residency and Consent Complexity
  • 4.3.3 High Integration Effort Across CMS, CRM, CDP and Ad Tech Stacks
  • 4.3.4 Personalization Fatigue and Perceived Manipulation Risk
• 4.4 Industry Value Chain Analysis
• 4.5 Regulatory Landscape
• 4.6 Technological Outlook
• 4.7 Porter's Five Forces Analysis
  • 4.7.1 Bargaining Power of Buyers
  • 4.7.2 Bargaining Power of Suppliers
  • 4.7.3 Threat of New Entrants
  • 4.7.4 Threat of Substitutes
  • 4.7.5 Intensity of Competitive Rivalry

5 MARKET SIZE AND GROWTH FORECASTS (VALUE)

• 5.1 By Application
  • 5.1.1 Content Recommendation
  • 5.1.2 Marketing and Advertising Personalization
  • 5.1.3 Customer Experience Personalization
  • 5.1.4 Audience Analytics
  • 5.1.5 Other Applications
• 5.2 By End User
  • 5.2.1 Streaming Platforms
  • 5.2.2 Broadcaster and Cable Networks
  • 5.2.3 Telecom Operators
  • 5.2.4 Digital Platforms
  • 5.2.5 Other End Users
• 5.3 By Geography
  • 5.3.1 North America
    • 5.3.1.1 United States
    • 5.3.1.2 Canada
    • 5.3.1.3 Mexico
  • 5.3.2 South America
    • 5.3.2.1 Brazil
    • 5.3.2.2 Argentina
    • 5.3.2.3 Chile
    • 5.3.2.4 Rest of South America
  • 5.3.3 Europe
    • 5.3.3.1 Germany
    • 5.3.3.2 United Kingdom
    • 5.3.3.3 France
    • 5.3.3.4 Italy
    • 5.3.3.5 Spain
    • 5.3.3.6 Rest of Europe
  • 5.3.4 Asia-Pacific
    • 5.3.4.1 China
    • 5.3.4.2 Japan
    • 5.3.4.3 India
    • 5.3.4.4 South Korea
    • 5.3.4.5 Australia
    • 5.3.4.6 Rest of Asia-Pacific
  • 5.3.5 Middle East
    • 5.3.5.1 Saudi Arabia
    • 5.3.5.2 United Arab Emirates
    • 5.3.5.3 Qatar
    • 5.3.5.4 Rest of Middle East
  • 5.3.6 Africa
    • 5.3.6.1 South Africa
    • 5.3.6.2 Egypt
    • 5.3.6.3 Nigeria
    • 5.3.6.4 Rest of Africa

6 COMPETITIVE LANDSCAPE

• 6.1 Market Concentration
• 6.2 Strategic Moves
• 6.3 Vendor Positioning Analysis
• 6.4 Company Profiles (includes Global Level Overview, Market Level Overview, Core Segments, Financials as available, Strategic Information, Products and Services, Recent Developments)
  • 6.4.1 Netflix, Inc.
  • 6.4.2 Amazon.com, Inc.
  • 6.4.3 Alphabet Inc.
  • 6.4.4 Adobe Inc.
  • 6.4.5 International Business Machines Corporation
  • 6.4.6 Salesforce, Inc.
  • 6.4.7 Oracle Corporation
  • 6.4.8 Sitecore A/S
  • 6.4.9 Bloomreach, Inc.
  • 6.4.10 Taboola.com Ltd.
  • 6.4.11 Outbrain Inc.
  • 6.4.12 Revcontent, Inc.
  • 6.4.13 ThinkAnalytics Ltd.
  • 6.4.14 Kaltura, Inc.
  • 6.4.15 Brightcove Inc.
  • 6.4.16 Viaccess-Orca
  • 6.4.17 Dynamic Yield (Mastercard)
  • 6.4.18 Wurl, LLC
  • 6.4.19 ContentWise S.r.l.
  • 6.4.20 Personyze Ltd.

7 MARKET OPPORTUNITIES AND FUTURE OUTLOOK

• 7.1 White-Space and Unmet-Need Assessment