メディアおよびエンターテインメントにおけるAI/ML市場- 世界の産業規模、シェア、動向、機会、予測、セグメント、ソリューション別、用途別、エンドユーザー別、地域別、競合、2019年～2029年

メディアおよびエンターテインメントにおけるAI/MLの世界市場規模は2023年に153億8,000万米ドルで、予測期間中のCAGRは28.36%で2029年には694億1,000万米ドルに達すると予測されています。

メディアおよびエンターテインメントにおけるAI/ML市場は、高度な人工知能と機械学習技術をメディアおよびエンターテインメント産業の様々な側面に適用することを包含しています。この市場には、業務効率、パーソナライゼーション、ユーザーエンゲージメントの強化を目的とした、コンテンツの作成、配信、消費のプロセスへのAIおよびMLの統合が含まれます。AIとML技術は、膨大な量のデータを分析し、コンテンツ制作を自動化し、実用的な洞察を提供するために採用され、メディア企業が個々の嗜好に合わせて提供物を調整し、コンテンツ戦略を最適化することを可能にします。コンテンツ制作では、AI主導のツールがスクリプトの生成、ビジュアルの作成、作曲までを支援し、制作時間とコストを大幅に削減します。コンテンツ配信では、AIアルゴリズムがターゲット広告、推薦システム、視聴者セグメンテーションに活用され、コンテンツが最も関連性の高い視聴者に確実に届き、収益機会を最大化します。さらに、AIとMLはパーソナライゼーションを通じてユーザー体験を向上させ、視聴履歴や嗜好に基づいてカスタマイズされた推薦を提供します。この市場には、AIが知的財産の監視と保護に役立つデジタル著作権管理や、機械学習モデルが動向や行動を予測し、戦略的決定を導く視聴者分析への応用も含まれます。業界が進化を続ける中、AIとMLは、ダイナミックなメディアおよびエンターテインメントの状況において、イノベーションを推進し、効率を改善し、パーソナライズされた体験を提供する上で極めて重要です。

市場促進要因

コンテンツ・パーソナライゼーションの強化

コンテンツの自動作成と編集

オーディエンスのインサイトとターゲティングの改善

市場の課題

データのプライバシーとセキュリティに関する懸念

アルゴリズムの偏りと公平性

主な市場動向

高いコンテンツ推薦

AIによるコンテンツ作成と自動化

AIを活用したインタラクティブ体験による視聴者エンゲージメントの強化

目次

第1章 概要

第2章 調査手法

第3章 エグゼクティブサマリー

第4章 顧客の声

第5章 世界のメディアおよびエンターテインメントにおけるAI/ML市場展望

• 市場規模・予測
  • 金額別
• 市場シェア・予測
  • ソリューション別（ハードウェア、サービス）
  • 用途別（ゲーム、フェイクストーリー検出、盗作検出パーソナライゼーション、制作計画と管理、セールスとマーケティング、人材発掘、コンテンツキャプチャなど）
  • エンドユーザー別（映画・テレビ、音楽、スポーツ、メディア代理店など）
  • 地域別
• 企業別（2023）
• 市場マップ

第6章 北米のメディアおよびエンターテインメントにおけるAI/ML市場展望

• 市場規模・予測
• 市場シェア・予測
• 北米：国別分析
  • カナダ
  • メキシコ

第7章 欧州のメディアおよびエンターテインメントにおけるAI/ML市場展望

• 市場規模・予測
• 市場シェア・予測
• 欧州：国別分析
  • 英国
  • イタリア
  • フランス
  • スペイン

第8章 アジア太平洋地域のメディアおよびエンターテインメントにおけるAI/ML市場展望

• 市場規模・予測
• 市場シェア・予測
• アジア太平洋地域：国別分析
  • インド
  • 日本
  • 韓国
  • オーストラリア

第9章 南米のメディアおよびエンターテインメントにおけるAI/ML市場展望

• 市場規模・予測
• 市場シェア・予測
• 南米：国別分析
  • アルゼンチン
  • コロンビア

第10章 中東・アフリカのメディアおよびエンターテインメントにおけるAI/ML市場展望

• 市場規模・予測
• 市場シェア・予測
• 中東・アフリカ：国別分析
  • サウジアラビア
  • アラブ首長国連邦
  • クウェート
  • トルコ

第11章 市場力学

• 促進要因
• 課題

第12章 市場動向と発展

第13章 企業プロファイル

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

第14章 戦略的提言

第15章 調査会社について・免責事項

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.

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