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市场调查报告书
商品编码
1613924

媒体和娱乐市场中的 AI/ML - 全球行业规模、份额、趋势、机会和预测，按解决方案、按应用、按最终用户、按地区和竞争细分，2019-2029F

AI/ML in Media and Entertainment Market - Global Industry Size, Share, Trends, Opportunity, and Forecast, Segmented, By Solutions, By Application, By End User, By Region & Competition, 2019-2029F
出版日期: | 出版商: TechSci Research | 英文 185 Pages | 商品交期: 2-3个工作天内

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简介目录

2023年，全球媒体和娱乐市场的AI/ML价值为153.8亿美元，预计到2029年将达到694.1亿美元，预测期内复合年增长率为28.36%。媒体和娱乐市场中的人工智慧/机器学习涵盖了先进的人工智慧和机器学习技术在媒体和娱乐产业各个方面的应用。该市场包括将人工智慧和机器学习整合到内容创建、分发和消费流程中，旨在提高营运效率、个人化和用户参与度。人工智慧和机器学习技术用于分析大量资料、自动化内容製作并提供可操作的见解，使媒体公司能够根据个人喜好自订其产品并优化其内容策略。在内容创作中，人工智慧驱动的工具可协助产生脚本、创造视觉效果，甚至创作音乐，从而显着减少製作时间和成本。在内容分发中，人工智慧演算法用于有针对性的广告、推荐系统和受众细分，确保内容到达最相关的观众并最大化收入机会。此外，人工智慧和机器学习透过个人化增强用户体验，根据观看历史记录和偏好提供客製化推荐。该市场还包括数位版权管理的应用，其中人工智慧有助于监控和保护智慧财产权，以及受众分析的应用，其中机器学习模型可以预测趋势和行为，指导策略决策。随着产业不断发展，人工智慧和机器学习在动态媒体和娱乐领域推动创新、提高效率和提供个人化体验方面发挥关键作用。

市场概况
预测期 2025-2029
2023 年市场规模 153.8亿美元
2029 年市场规模 694.1亿美元
2024-2029 年复合年增长率 28.36%
成长最快的细分市场 生产计划与管理
最大的市场 北美洲

主要市场驱动因素

增强的内容个人化

自动内容建立和编辑

改进受众洞察和定位

主要市场挑战

资料隐私和安全问题

演算法偏差和公平性

主要市场趋势

高内容推荐

人工智慧驱动的内容创建和自动化

透过人工智慧驱动的互动体验增强观众参与度

细分市场洞察

应用洞察

区域洞察

目录

第 1 章：产品概述

第 2 章：研究方法

第 3 章：执行摘要

第 4 章：客户之声

第 5 章：媒体与娱乐领域的全球 AI/ML 市场展望

  • 市场规模及预测
    • 按价值
  • 市占率及预测
    • 按解决方案（硬体、服务）
    • 按应用程式（游戏、虚假故事检测、抄袭检测个人化、生产规划与管理、销售与行销、人才辨识、内容撷取等）
    • 按最终用户（电影和电视、音乐、体育、媒体机构等）
    • 按地区
  • 按公司划分 (2023)
  • 市场地图

第 6 章：北美人工智慧/机器学习在媒体和娱乐市场的前景

  • 市场规模及预测
  • 市占率及预测
  • 北美：国家分析
    • 加拿大
    • 墨西哥

第 7 章：欧洲媒体与娱乐市场中的 AI/ML 前景

  • 市场规模及预测
  • 市占率及预测
  • 欧洲：国家分析
    • 英国
    • 义大利
    • 法国
    • 西班牙

第 8 章：亚太地区媒体与娱乐领域人工智慧/机器学习市场展望

  • 市场规模及预测
  • 市占率及预测
  • 亚太地区：国家分析
    • 印度
    • 日本
    • 韩国
    • 澳洲

第 9 章：南美洲媒体与娱乐市场中的 AI/ML 前景

  • 市场规模及预测
  • 市占率及预测
  • 南美洲：国家分析
    • 阿根廷
    • 哥伦比亚

第 10 章：中东和非洲媒体和娱乐市场中的 AI/ML 前景

  • 市场规模及预测
  • 市占率及预测
  • 中东和非洲：国家分析
    • 沙乌地阿拉伯
    • 阿联酋
    • 科威特
    • 土耳其

第 11 章：市场动态

  • 司机
  • 挑战

第 12 章：市场趋势与发展

第 13 章：公司简介

  • Alphabet Inc.
  • Apple Inc.
  • Sony Pictures Entertainment Inc.
  • NBCUniversal Media, LLC
  • Alibaba Cloud International
  • IBM Corporation
  • Microsoft Corporation
  • Nvidia Corporation

第 14 章：策略建议

第15章调查会社について・免责事项

简介目录
Product Code: 24751

Global AI/ML in Media and Entertainment Market was valued at USD 15.38 billion in 2023 and is expected to reach USD 69.41 billion by 2029 with a CAGR of 28.36% during the forecast period. The AI/ML in Media and Entertainment market encompasses the application of advanced artificial intelligence and machine learning technologies to various facets of the media and entertainment industry. This market includes the integration of AI and ML into content creation, distribution, and consumption processes, aimed at enhancing operational efficiency, personalization, and user engagement. AI and ML technologies are employed to analyze vast amounts of data, automate content production, and provide actionable insights, enabling media companies to tailor their offerings to individual preferences and optimize their content strategies. In content creation, AI-driven tools assist in generating scripts, creating visuals, and even composing music, significantly reducing production time and costs. In content distribution, AI algorithms are utilized for targeted advertising, recommendation systems, and audience segmentation, ensuring that content reaches the most relevant viewers and maximizing revenue opportunities. Additionally, AI and ML enhance the user experience through personalization, providing customized recommendations based on viewing history and preferences. The market also includes applications in digital rights management, where AI helps in monitoring and protecting intellectual property, and in audience analytics, where machine learning models predict trends and behaviors, guiding strategic decisions. As the industry continues to evolve, AI and ML are pivotal in driving innovation, improving efficiency, and delivering personalized experiences in the dynamic media and entertainment landscape.

Market Overview
Forecast Period2025-2029
Market Size 2023USD 15.38 Billion
Market Size 2029USD 69.41 Billion
CAGR 2024-202928.36%
Fastest Growing SegmentProduction Planning & Management
Largest MarketNorth America

Key Market Drivers

Enhanced Content Personalization

The AI and machine learning (ML) technologies are revolutionizing the media and entertainment industry by enabling unprecedented levels of content personalization. With vast amounts of data generated by viewers, AI algorithms analyze user behavior, preferences, and interactions to deliver highly tailored content recommendations. This personalization is driven by advanced machine learning models that can predict what content viewers are most likely to enjoy based on their historical data, viewing patterns, and demographic information. By integrating AI, media companies can offer customized experiences, which significantly boosts user engagement and satisfaction. For example, streaming services like Netflix and Spotify use sophisticated recommendation engines to suggest movies, TV shows, and music based on individual user profiles, enhancing the overall viewing experience and driving higher retention rates. This targeted approach not only improves user experience but also increases the effectiveness of content monetization strategies. As consumer expectations for personalized experiences continue to rise, the demand for AI-driven solutions in content recommendation and personalization is expected to grow, making it a crucial driver of market expansion in the media and entertainment sector.

Automated Content Creation and Editing

AI and ML are transforming content creation and editing processes, making them more efficient and cost-effective. Automated content generation tools powered by AI can produce high-quality written articles, scripts, and even creative content such as music and visual art, reducing the time and labor required by human creators. For instance, AI algorithms can generate news articles from raw data, create video summaries, and assist in scriptwriting by analyzing successful storytelling patterns. Machine learning models can also automate editing tasks, such as video trimming, color correction, and audio enhancement, with a level of precision and speed that surpasses traditional methods. This automation not only accelerates the production cycle but also enables creators to focus on more strategic and creative aspects of content development. Additionally, AI-powered tools can analyze audience reactions and feedback to refine content strategies, ensuring that the final product aligns with audience expectations and market trends. As media companies strive to meet the growing demand for fresh and engaging content, the adoption of AI-driven automation tools will continue to drive innovation and efficiency in content creation and editing processes.

Improved Audience Insights and Targeting

AI and ML technologies provide media and entertainment companies with advanced capabilities for analyzing audience data and deriving actionable insights. By leveraging big data analytics and machine learning algorithms, companies can gain a deeper understanding of viewer behaviors, preferences, and trends. This enhanced data analysis allows for more precise audience segmentation and targeting, enabling media firms to develop and deliver content that resonates with specific demographic groups. For example, AI can analyze social media interactions, viewing patterns, and consumer feedback to identify emerging trends and predict future content demands. This data-driven approach helps media companies optimize marketing strategies, tailor advertising campaigns, and allocate resources more effectively. Additionally, AI-powered sentiment analysis tools can gauge audience reactions to content, providing valuable feedback that informs future content development and promotional efforts. As the media and entertainment landscape becomes increasingly competitive, the ability to leverage AI for audience insights and targeted marketing will be a key driver of growth and success in the industry.

Key Market Challenges

Data Privacy and Security Concerns

In the media and entertainment sector, the deployment of AI and machine learning technologies faces significant hurdles related to data privacy and security. These technologies rely heavily on vast amounts of personal data, including user behavior, viewing habits, and interaction patterns, to generate insights and deliver personalized experiences. However, the collection, storage, and processing of such sensitive information raise substantial privacy concerns. Regulatory frameworks like the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) impose strict guidelines on data usage and user consent, demanding that companies implement robust data protection measures. The complexity of ensuring compliance with these regulations while leveraging AI-driven analytics can be daunting. Additionally, data breaches or misuse can lead to severe reputational damage and financial penalties. Media and entertainment companies must invest significantly in advanced security protocols and data governance strategies to mitigate these risks, balancing the need for innovative AI solutions with stringent privacy requirements. The ongoing evolution of privacy regulations and the increasing sophistication of cyber threats further exacerbate the challenge, necessitating continuous adaptation and vigilance.

Algorithmic Bias and Fairness

Another critical challenge facing the integration of AI and machine learning in the media and entertainment industry is addressing algorithmic bias and ensuring fairness. AI systems are often trained on historical data, which can inadvertently encode and perpetuate existing biases, leading to skewed or unfair outcomes. For instance, recommendation algorithms might favor content that reinforces stereotypes or excludes minority voices, impacting diversity and representation in media. This bias can manifest in various forms, including gender, racial, and cultural biases, potentially alienating audiences and undermining the credibility of media platforms. To combat this, companies must develop and implement strategies to detect and mitigate biases within their algorithms. This involves diversifying training data, employing fairness-aware algorithms, and conducting regular audits to ensure equitable outcomes. Additionally, fostering transparency and accountability in AI decision-making processes is crucial for building trust with users. Addressing algorithmic bias requires a concerted effort to balance technological innovation with ethical considerations, ensuring that AI applications in media and entertainment promote inclusivity and fairness while avoiding the reinforcement of harmful biases.

Key Market Trends

High Content Recommendations

The media and entertainment industry is witnessing a profound shift towards highly personalized content recommendations driven by advancements in AI and machine learning (ML). AI algorithms analyze vast amounts of viewer data, including viewing history, preferences, and engagement patterns, to deliver tailored content suggestions. This hyper-personalization enhances user experience by presenting relevant media, increasing viewer satisfaction and retention. Streaming platforms, such as Netflix and Spotify, leverage sophisticated recommendation engines to suggest shows, movies, and music that align with individual tastes. As AI technology evolves, these algorithms are becoming more adept at understanding nuanced preferences, such as mood and context, further refining content curation. Additionally, the integration of natural language processing (NLP) allows platforms to interpret user queries and feedback more accurately, improving the relevance of recommendations. This trend is not only transforming user engagement but also driving content discovery and consumption patterns, creating new opportunities for media companies to engage audiences and generate revenue.

AI-Driven Content Creation and Automation

AI and ML are revolutionizing content creation and production processes, making them more efficient and cost-effective. From automated video editing to scriptwriting assistance and AI-generated music, media companies are increasingly turning to machine learning algorithms to streamline production workflows. AI tools can analyze vast amounts of existing content to create new, high-quality media assets, such as video trailers, summaries, or promotional material, often without requiring human intervention. Additionally, AI-based automation is reducing production timelines and labor costs by taking over repetitive tasks, allowing human creators to focus on more strategic and creative aspects. This trend is not only making media production faster but also democratizing content creation, enabling smaller studios and independent creators to produce high-quality content at scale.

Enhanced Viewer Engagement Through AI-Powered Interactive Experiences

The use of AI in media and entertainment is extending beyond content personalization and production to include interactive experiences that actively engage audiences. AI technologies are powering immersive experiences through augmented reality (AR), virtual reality (VR), and interactive storytelling, enhancing viewer engagement. For example, AI-driven VR and AR applications enable users to interact with media content in real-time, creating more personalized and immersive experiences. Interactive storytelling powered by AI allows users to influence plotlines or outcomes, offering a unique and dynamic form of entertainment. This trend is transforming how audiences consume content, providing deeper engagement and a more participatory experience, which can significantly drive user loyalty and retention in an increasingly competitive media landscape.

Segmental Insights

Application Insights

The Gaming segment held the largest Market share in 2023. The integration of AI and machine learning (ML) in the gaming segment of the media and entertainment market is driven by several compelling factors that are transforming the industry. One primary driver is the demand for enhanced gaming experiences through personalized content and adaptive gameplay. AI and ML technologies enable developers to create more immersive and engaging games by analyzing player behaviors and preferences to deliver tailored experiences. This personalization extends to dynamic content generation, where AI algorithms can generate unique in-game environments, characters, and narratives based on individual player interactions, significantly enriching gameplay and increasing player retention. Additionally, AI-driven analytics provide game developers with valuable insights into player behavior, which helps in refining game design, optimizing monetization strategies, and predicting trends. The rise of cloud gaming services further amplifies the role of AI and ML, as these technologies support seamless, low-latency streaming and enhance user experience through real-time adjustments and predictive maintenance.

AI and ML also play a crucial role in the development of non-player characters (NPCs) and game AI, where advanced algorithms enable NPCs to exhibit more realistic behaviors and adapt to player actions, contributing to a more lifelike and responsive gaming environment. Furthermore, the application of AI in game testing and quality assurance streamlines the development process by automating repetitive tasks, identifying bugs, and ensuring a higher level of game quality and stability. The growing popularity of esports and competitive gaming also fuels the demand for AI and ML, as these technologies are used to analyze player performance, strategize in real-time, and enhance training methods. As AI and ML continue to advance, their capabilities in natural language processing and computer vision offer new opportunities for interactive storytelling and enhanced player interactions. Overall, the continuous evolution of AI and ML technologies is driving innovation and growth in the gaming segment by providing developers with powerful tools to create more engaging, personalized, and immersive gaming experiences, thus meeting the evolving demands of gamers and propelling the industry forward.

Regional Insights

North America region held the largest market share in 2023. The AI and machine learning (ML) market in the media and entertainment sector in North America is experiencing robust growth driven by several key factors. The increasing demand for personalized content and tailored user experiences is a significant market driver. AI and ML technologies enable media companies to analyze vast amounts of data to understand consumer preferences and behaviors, allowing for the creation of customized recommendations and targeted content that enhances viewer engagement and satisfaction. Additionally, the rise of streaming services and digital platforms has intensified competition, prompting companies to leverage AI and ML to optimize content delivery, improve user interfaces, and enhance overall service quality. Machine learning algorithms are also instrumental in content creation and production, offering tools for automated video editing, scriptwriting, and even generating realistic visual effects, which streamline workflows and reduce production costs.

AI-driven analytics provide valuable insights into viewer trends and content performance, empowering media companies to make data-informed decisions and strategically allocate resources. Another significant driver is the growing need for advanced security measures to protect intellectual property and prevent piracy; AI technologies offer sophisticated solutions for detecting and mitigating unauthorized content distribution. The expansion of virtual and augmented reality experiences also contributes to market growth, as AI and ML play crucial roles in developing immersive and interactive media experiences. Additionally, the increasing integration of AI in advertising and marketing within the media sector allows for more precise targeting and optimization of ad campaigns, enhancing revenue generation opportunities. As technology continues to advance, North American media and entertainment companies are increasingly investing in AI and ML to stay competitive, innovate their offerings, and meet evolving consumer expectations, further driving the market's expansion.

Key Market Players

  • Alphabet Inc.
  • Apple Inc.
  • Sony Pictures Entertainment Inc.
  • NBCUniversal Media, LLC
  • Alibaba Cloud International
  • IBM Corporation
  • Microsoft Corporation
  • Nvidia Corporation

Report Scope:

In this report, the Global AI/ML in Media and Entertainment Market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:

AI/ML in Media and Entertainment Market, By Solutions:

  • Hardware
  • Services

AI/ML in Media and Entertainment Market, By Application:

  • Gaming
  • Fake Story Detection
  • Plagiarism Detection Personalization
  • Production Planning & Management
  • Sales & Marketing
  • Talent Identification
  • Content Capture
  • Others

AI/ML in Media and Entertainment Market, By End User:

  • Film and Television
  • Music
  • Sports
  • Media Agencies
  • Others

AI/ML in Media and Entertainment Market, By Region:

  • North America
    • United States
    • Canada
    • Mexico
  • Europe
    • France
    • United Kingdom
    • Italy
    • Germany
    • Spain
  • Asia-Pacific
    • China
    • India
    • Japan
    • Australia
    • South Korea
  • South America
    • Brazil
    • Argentina
    • Colombia
  • Middle East & Africa
    • South Africa
    • Saudi Arabia
    • UAE
    • Kuwait
    • Turkey

Competitive Landscape

Company Profiles: Detailed analysis of the major companies presents in the Global AI/ML in Media and Entertainment Market.

Available Customizations:

Global AI/ML in Media and Entertainment Market report with the given Market data, TechSci Research offers customizations according to a company's specific needs. The following customization options are available for the report:

Company Information

  • Detailed analysis and profiling of additional Market players (up to five).

Table of Contents

1. Product Overview

  • 1.1. Market Definition
  • 1.2. Scope of the Market
    • 1.2.1. Markets Covered
    • 1.2.2. Years Considered for Study
  • 1.3. Key Market Segmentations

2. Research Methodology

  • 2.1. Objective of the Study
  • 2.2. Baseline Methodology
  • 2.3. Formulation of the Scope
  • 2.4. Assumptions and Limitations
  • 2.5. Sources of Research
    • 2.5.1. Secondary Research
    • 2.5.2. Primary Research
  • 2.6. Approach for the Market Study
    • 2.6.1. The Bottom-Up Approach
    • 2.6.2. The Top-Down Approach
  • 2.7. Methodology Followed for Calculation of Market Size & Market Shares
  • 2.8. Forecasting Methodology
    • 2.8.1. Data Triangulation & Validation

3. Executive Summary

4. Voice of Customer

5. Global AI/ML in Media and Entertainment Market Outlook

  • 5.1. Market Size & Forecast
    • 5.1.1. By Value
  • 5.2. Market Share & Forecast
    • 5.2.1. By Solutions (Hardware, Services)
    • 5.2.2. By Application (Gaming, Fake Story Detection, Plagiarism Detection Personalization, Production Planning & Management, Sales & Marketing, Talent Identification, Content Capture, and Others)
    • 5.2.3. By End User (Film and Television, Music, Sports, Media Agencies, and Others)
    • 5.2.4. By Region
  • 5.3. By Company (2023)
  • 5.4. Market Map

6. North America AI/ML in Media and Entertainment Market Outlook

  • 6.1. Market Size & Forecast
    • 6.1.1. By Value
  • 6.2. Market Share & Forecast
    • 6.2.1. By Solutions
    • 6.2.2. By Application
    • 6.2.3. By End User
    • 6.2.4. By Country
  • 6.3. North America: Country Analysis
    • 6.3.1. United States AI/ML in Media and Entertainment Market Outlook
      • 6.3.1.1. Market Size & Forecast
        • 6.3.1.1.1. By Value
      • 6.3.1.2. Market Share & Forecast
        • 6.3.1.2.1. By Solutions
        • 6.3.1.2.2. By Application
        • 6.3.1.2.3. By End User
    • 6.3.2. Canada AI/ML in Media and Entertainment Market Outlook
      • 6.3.2.1. Market Size & Forecast
        • 6.3.2.1.1. By Value
      • 6.3.2.2. Market Share & Forecast
        • 6.3.2.2.1. By Solutions
        • 6.3.2.2.2. By Application
        • 6.3.2.2.3. By End User
    • 6.3.3. Mexico AI/ML in Media and Entertainment Market Outlook
      • 6.3.3.1. Market Size & Forecast
        • 6.3.3.1.1. By Value
      • 6.3.3.2. Market Share & Forecast
        • 6.3.3.2.1. By Solutions
        • 6.3.3.2.2. By Application
        • 6.3.3.2.3. By End User

7. Europe AI/ML in Media and Entertainment Market Outlook

  • 7.1. Market Size & Forecast
    • 7.1.1. By Value
  • 7.2. Market Share & Forecast
    • 7.2.1. By Solutions
    • 7.2.2. By Application
    • 7.2.3. By End User
    • 7.2.4. By Country
  • 7.3. Europe: Country Analysis
    • 7.3.1. Germany AI/ML in Media and Entertainment Market Outlook
      • 7.3.1.1. Market Size & Forecast
        • 7.3.1.1.1. By Value
      • 7.3.1.2. Market Share & Forecast
        • 7.3.1.2.1. By Solutions
        • 7.3.1.2.2. By Application
        • 7.3.1.2.3. By End User
    • 7.3.2. United Kingdom AI/ML in Media and Entertainment Market Outlook
      • 7.3.2.1. Market Size & Forecast
        • 7.3.2.1.1. By Value
      • 7.3.2.2. Market Share & Forecast
        • 7.3.2.2.1. By Solutions
        • 7.3.2.2.2. By Application
        • 7.3.2.2.3. By End User
    • 7.3.3. Italy AI/ML in Media and Entertainment Market Outlook
      • 7.3.3.1. Market Size & Forecast
        • 7.3.3.1.1. By Value
      • 7.3.3.2. Market Share & Forecast
        • 7.3.3.2.1. By Solutions
        • 7.3.3.2.2. By Application
        • 7.3.3.2.3. By End User
    • 7.3.4. France AI/ML in Media and Entertainment Market Outlook
      • 7.3.4.1. Market Size & Forecast
        • 7.3.4.1.1. By Value
      • 7.3.4.2. Market Share & Forecast
        • 7.3.4.2.1. By Solutions
        • 7.3.4.2.2. By Application
        • 7.3.4.2.3. By End User
    • 7.3.5. Spain AI/ML in Media and Entertainment Market Outlook
      • 7.3.5.1. Market Size & Forecast
        • 7.3.5.1.1. By Value
      • 7.3.5.2. Market Share & Forecast
        • 7.3.5.2.1. By Solutions
        • 7.3.5.2.2. By Application
        • 7.3.5.2.3. By End User

8. Asia-Pacific AI/ML in Media and Entertainment Market Outlook

  • 8.1. Market Size & Forecast
    • 8.1.1. By Value
  • 8.2. Market Share & Forecast
    • 8.2.1. By Solutions
    • 8.2.2. By Application
    • 8.2.3. By End User
    • 8.2.4. By Country
  • 8.3. Asia-Pacific: Country Analysis
    • 8.3.1. China AI/ML in Media and Entertainment Market Outlook
      • 8.3.1.1. Market Size & Forecast
        • 8.3.1.1.1. By Value
      • 8.3.1.2. Market Share & Forecast
        • 8.3.1.2.1. By Solutions
        • 8.3.1.2.2. By Application
        • 8.3.1.2.3. By End User
    • 8.3.2. India AI/ML in Media and Entertainment Market Outlook
      • 8.3.2.1. Market Size & Forecast
        • 8.3.2.1.1. By Value
      • 8.3.2.2. Market Share & Forecast
        • 8.3.2.2.1. By Solutions
        • 8.3.2.2.2. By Application
        • 8.3.2.2.3. By End User
    • 8.3.3. Japan AI/ML in Media and Entertainment Market Outlook
      • 8.3.3.1. Market Size & Forecast
        • 8.3.3.1.1. By Value
      • 8.3.3.2. Market Share & Forecast
        • 8.3.3.2.1. By Solutions
        • 8.3.3.2.2. By Application
        • 8.3.3.2.3. By End User
    • 8.3.4. South Korea AI/ML in Media and Entertainment Market Outlook
      • 8.3.4.1. Market Size & Forecast
        • 8.3.4.1.1. By Value
      • 8.3.4.2. Market Share & Forecast
        • 8.3.4.2.1. By Solutions
        • 8.3.4.2.2. By Application
        • 8.3.4.2.3. By End User
    • 8.3.5. Australia AI/ML in Media and Entertainment Market Outlook
      • 8.3.5.1. Market Size & Forecast
        • 8.3.5.1.1. By Value
      • 8.3.5.2. Market Share & Forecast
        • 8.3.5.2.1. By Solutions
        • 8.3.5.2.2. By Application
        • 8.3.5.2.3. By End User

9. South America AI/ML in Media and Entertainment Market Outlook

  • 9.1. Market Size & Forecast
    • 9.1.1. By Value
  • 9.2. Market Share & Forecast
    • 9.2.1. By Solutions
    • 9.2.2. By Application
    • 9.2.3. By End User
    • 9.2.4. By Country
  • 9.3. South America: Country Analysis
    • 9.3.1. Brazil AI/ML in Media and Entertainment Market Outlook
      • 9.3.1.1. Market Size & Forecast
        • 9.3.1.1.1. By Value
      • 9.3.1.2. Market Share & Forecast
        • 9.3.1.2.1. By Solutions
        • 9.3.1.2.2. By Application
        • 9.3.1.2.3. By End User
    • 9.3.2. Argentina AI/ML in Media and Entertainment Market Outlook
      • 9.3.2.1. Market Size & Forecast
        • 9.3.2.1.1. By Value
      • 9.3.2.2. Market Share & Forecast
        • 9.3.2.2.1. By Solutions
        • 9.3.2.2.2. By Application
        • 9.3.2.2.3. By End User
    • 9.3.3. Colombia AI/ML in Media and Entertainment Market Outlook
      • 9.3.3.1. Market Size & Forecast
        • 9.3.3.1.1. By Value
      • 9.3.3.2. Market Share & Forecast
        • 9.3.3.2.1. By Solutions
        • 9.3.3.2.2. By Application
        • 9.3.3.2.3. By End User

10. Middle East and Africa AI/ML in Media and Entertainment Market Outlook

  • 10.1. Market Size & Forecast
    • 10.1.1. By Value
  • 10.2. Market Share & Forecast
    • 10.2.1. By Solutions
    • 10.2.2. By Application
    • 10.2.3. By End User
    • 10.2.4. By Country
  • 10.3. Middle East and Africa: Country Analysis
    • 10.3.1. South Africa AI/ML in Media and Entertainment Market Outlook
      • 10.3.1.1. Market Size & Forecast
        • 10.3.1.1.1. By Value
      • 10.3.1.2. Market Share & Forecast
        • 10.3.1.2.1. By Solutions
        • 10.3.1.2.2. By Application
        • 10.3.1.2.3. By End User
    • 10.3.2. Saudi Arabia AI/ML in Media and Entertainment Market Outlook
      • 10.3.2.1. Market Size & Forecast
        • 10.3.2.1.1. By Value
      • 10.3.2.2. Market Share & Forecast
        • 10.3.2.2.1. By Solutions
        • 10.3.2.2.2. By Application
        • 10.3.2.2.3. By End User
    • 10.3.3. UAE AI/ML in Media and Entertainment Market Outlook
      • 10.3.3.1. Market Size & Forecast
        • 10.3.3.1.1. By Value
      • 10.3.3.2. Market Share & Forecast
        • 10.3.3.2.1. By Solutions
        • 10.3.3.2.2. By Application
        • 10.3.3.2.3. By End User
    • 10.3.4. Kuwait AI/ML in Media and Entertainment Market Outlook
      • 10.3.4.1. Market Size & Forecast
        • 10.3.4.1.1. By Value
      • 10.3.4.2. Market Share & Forecast
        • 10.3.4.2.1. By Solutions
        • 10.3.4.2.2. By Application
        • 10.3.4.2.3. By End User
    • 10.3.5. Turkey AI/ML in Media and Entertainment Market Outlook
      • 10.3.5.1. Market Size & Forecast
        • 10.3.5.1.1. By Value
      • 10.3.5.2. Market Share & Forecast
        • 10.3.5.2.1. By Solutions
        • 10.3.5.2.2. By Application
        • 10.3.5.2.3. By End User

11. Market Dynamics

  • 11.1. Drivers
  • 11.2. Challenges

12. Market Trends & Developments

13. Company Profiles

  • 13.1. Alphabet Inc.
    • 13.1.1. Business Overview
    • 13.1.2. Key Revenue and Financials
    • 13.1.3. Recent Developments
    • 13.1.4. Key Personnel/Key Contact Person
    • 13.1.5. Key Product/Services Offered
  • 13.2. Apple Inc.
    • 13.2.1. Business Overview
    • 13.2.2. Key Revenue and Financials
    • 13.2.3. Recent Developments
    • 13.2.4. Key Personnel/Key Contact Person
    • 13.2.5. Key Product/Services Offered
  • 13.3. Sony Pictures Entertainment Inc.
    • 13.3.1. Business Overview
    • 13.3.2. Key Revenue and Financials
    • 13.3.3. Recent Developments
    • 13.3.4. Key Personnel/Key Contact Person
    • 13.3.5. Key Product/Services Offered
  • 13.4. NBCUniversal Media, LLC
    • 13.4.1. Business Overview
    • 13.4.2. Key Revenue and Financials
    • 13.4.3. Recent Developments
    • 13.4.4. Key Personnel/Key Contact Person
    • 13.4.5. Key Product/Services Offered
  • 13.5. Alibaba Cloud International
    • 13.5.1. Business Overview
    • 13.5.2. Key Revenue and Financials
    • 13.5.3. Recent Developments
    • 13.5.4. Key Personnel/Key Contact Person
    • 13.5.5. Key Product/Services Offered
  • 13.6. IBM Corporation
    • 13.6.1. Business Overview
    • 13.6.2. Key Revenue and Financials
    • 13.6.3. Recent Developments
    • 13.6.4. Key Personnel/Key Contact Person
    • 13.6.5. Key Product/Services Offered
  • 13.7. Microsoft Corporation
    • 13.7.1. Business Overview
    • 13.7.2. Key Revenue and Financials
    • 13.7.3. Recent Developments
    • 13.7.4. Key Personnel/Key Contact Person
    • 13.7.5. Key Product/Services Offered
  • 13.8. Nvidia Corporation
    • 13.8.1. Business Overview
    • 13.8.2. Key Revenue and Financials
    • 13.8.3. Recent Developments
    • 13.8.4. Key Personnel/Key Contact Person
    • 13.8.5. Key Product/Services Offered

14. Strategic Recommendations

15. About Us & Disclaimer