1. 方法論と範囲
1.1. 調査方法
1.2. 調査目的と調査範囲
2. 定義と概要
3. エグゼクティブ・サマリー
3.1. タイプ別スニペット
3.2. コンポーネント別スニペット
3.3. ビジネス機能別スニペット
3.4. 統合モード別スニペット
3.5. エンドユーザー別スニペット
3.6. 地域別スニペット
4. ダイナミクス
4.1. 影響要因
4.1.1. 推進要因
4.1.1.1. コンテンツ作成とキュレーションの自動化に対する需要の高まり
4.1.1.2. 加速するバーチャルリアリティ
4.1.2. 制約事項
4.1.2.1. 高いトレーニングコスト
4.1.3. 機会
4.1.4. 影響分析
5. 産業分析
5.1. ポーターのファイブフォース分析
5.2. サプライチェーン分析
5.3. 価格分析
5.4. 規制分析
5.5. ロシア・ウクライナ戦争の影響分析
5.6. DMI意見
6. COVID-19分析
6.1. COVID-19の分析
6.1.1. COVID-19以前のシナリオ
6.1.2. COVID-19開催中のシナリオ
6.1.3. COVID-19後のシナリオ
6.2. COVID-19中の価格ダイナミクス
6.3. 需給スペクトラム
6.4. パンデミック時の市場に関連する政府の取り組み
6.5. メーカーの戦略的取り組み
6.6. 結論
7. タイプ別
7.1. はじめに
7.1.1. 市場規模分析および前年比成長率分析（%）, タイプ別
7.1.2. 市場魅力度指数（タイプ別
7.2. AIチャットボット
7.2.1. はじめに
7.2.2. 市場規模分析と前年比成長率分析(%)
7.3. 音声ボット
7.4. 対話型音声アシスタント（IVA）
7.5. 生成AIエージェント
8. コンポーネント別
8.1. はじめに
8.1.1. 市場規模分析および前年比成長率分析(%), コンポーネント別
8.1.2. 市場魅力度指数（コンポーネント別
8.2. ソリューション*市場
8.2.1. 導入
8.2.2. 市場規模分析と前年比成長率分析(%)
8.3. マネージドサービス
8.4. プロフェッショナルサービス
8.5. トレーニング＆コンサルティング
8.6. システムインテグレーション＆インプリメンテーション
8.7. サポート＆メンテナンス
9. ビジネス機能別
9.1. 導入
9.1.1. 事業機能別市場規模分析および前年比成長率分析（%） 9.1.2.
9.1.2. 市場魅力度指数（ビジネス機能別
9.2. セールス＆マーケティング
9.2.1. はじめに
9.2.2. 市場規模分析と前年比成長率分析(%)
9.3. オペレーション＆サプライチェーン
9.4. 財務・会計
9.5. 人事（HR）
9.6. ITサービスマネジメント（ITSM）
9.7. その他
10. 統合モード別
10.1. 導入
10.1.1. 統合モード別市場規模分析と前年比成長率分析（%）。
10.1.2. 市場魅力度指数（統合モード別
10.2. 企業内システム
10.2.1. はじめに
10.2.2. 市場規模分析と前年比成長率分析(%)
10.3. 外部通信チャネル
11. エンドユーザー別
11.1. はじめに
11.1.1. 市場規模分析および前年比成長率分析（%）, エンドユーザー別
11.1.2. 市場魅力度指数、エンドユーザー別
11.2. BFSI*市場
11.2.1. 序論
11.2.2. 市場規模分析と前年比成長率分析(%)
11.3. 小売・eコマース
11.4. 教育
11.5. メディア・娯楽
11.6. ヘルスケア＆ライフサイエンス
11.7. 旅行・ホスピタリティ
11.8. 自動車
11.9. IT・ITeS
11.10. 政府・防衛
11.11. その他
12. 地域別
12.1. はじめに
12.1.1. 地域別市場規模分析および前年比成長率分析(%)
12.1.2. 市場魅力度指数、地域別
12.2. 北米
12.2.1. 序論
12.2.2. 主な地域別ダイナミクス
12.2.3. 市場規模分析および前年比成長率分析（%）, タイプ別
12.2.4. 市場規模分析とYoY成長率分析(%)、コンポーネント別
12.2.5. 市場規模分析およびYoY成長率分析(%)、ビジネス機能別
12.2.6. 市場規模分析およびYoY成長率分析(%)、統合モード別
12.2.7. 市場規模分析およびYoY成長率分析(%)、エンドユーザー別
12.2.8. 市場規模分析およびYoY成長率分析(%)、国別
12.2.8.1. 米国
12.2.8.2. カナダ
12.2.8.3. メキシコ
12.3. ヨーロッパ
12.3.1. はじめに
12.3.2. 主な地域別ダイナミクス
12.3.3. 市場規模分析および前年比成長率分析(%), タイプ別
12.3.4. 市場規模分析とYoY成長率分析(%)、コンポーネント別
12.3.5. 市場規模分析およびYoY成長率分析(%)、ビジネス機能別
12.3.6. 市場規模分析およびYoY成長率分析(%)、統合モード別
12.3.7. 市場規模分析およびYoY成長率分析(%)、エンドユーザー別
12.3.8. 市場規模分析およびYoY成長率分析(%)、国別
12.3.8.1. ドイツ
12.3.8.2. イギリス
12.3.8.3. フランス
12.3.8.4. イタリア
12.3.8.5. スペイン
12.3.8.6. その他のヨーロッパ
12.4. 南米
12.4.1. はじめに
12.4.2. 主な地域別ダイナミクス
12.4.3. 市場規模分析および前年比成長率分析（%）, タイプ別
12.4.4. 市場規模分析とYoY成長率分析(%)、コンポーネント別
12.4.5. 市場規模分析およびYoY成長率分析(%)、ビジネス機能別
12.4.6. 市場規模分析およびYoY成長率分析(%)、統合モード別
12.4.7. 市場規模分析およびYoY成長率分析(%)、エンドユーザー別
12.4.8. 市場規模分析およびYoY成長率分析(%)、国別
12.4.8.1. ブラジル
12.4.8.2. アルゼンチン
12.4.8.3. その他の南米諸国
12.5. アジア太平洋
12.5.1. はじめに
12.5.2. 主な地域別ダイナミクス
12.5.3. 市場規模分析および前年比成長率分析（%）, タイプ別
12.5.4. 市場規模分析とYoY成長率分析(%)、コンポーネント別
12.5.5. 市場規模分析およびYoY成長率分析(%)、ビジネス機能別
12.5.6. 市場規模分析およびYoY成長率分析(%)、統合モード別
12.5.7. 市場規模分析およびYoY成長率分析(%)、エンドユーザー別
12.5.8. 市場規模分析およびYoY成長率分析(%)、国別
12.5.8.1. 中国
12.5.8.2. インド
12.5.8.3. 日本
12.5.8.4. オーストラリア
12.5.8.5. その他のアジア太平洋地域
12.6. 中東・アフリカ
12.6.1. 序論
12.6.2. 主な地域別ダイナミクス
12.6.3. 市場規模分析とYoY成長率分析(%), タイプ別
12.6.4. 市場規模分析とYoY成長率分析(%)、コンポーネント別
12.6.5. 市場規模分析およびYoY成長率分析(%)、ビジネス機能別
12.6.6. 市場規模分析およびYoY成長率分析(%)、統合モード別
12.6.7. 市場規模分析および前年比成長率分析（%）, エンドユーザー別
13. 競合情勢
13.1. 競争シナリオ
13.2. 市場ポジショニング／シェア分析
13.3. M&A分析
14. 企業プロフィール
14.1. Google*
14.1.1. Company Overview
14.1.2. Product Portfolio and Description
14.1.3. Financial Overview
14.1.4. Key Developments
14.2. Microsoft
14.3. Amazon Web Services, Inc.
14.4. IBM
14.5. Oracle
14.6. Nuance Communications, Inc.
14.7. FIS
14.8. SAP SE
14.9. Artificial Solutions
14.10. Kore.ai, Inc.
リストは網羅的ではありません
15. 付録
15.1. コレド.AIについて
15.2. お問い合わせ

Overview
Global Generational AI Market reached US$ 44.56 billion in 2023 and is expected to reach US$ 998.23 billion by 2031, growing with a CAGR of 47.50% during the forecast period 2024-2031.
Ongoing breakthroughs in AI technology, especially in natural language processing (NLP), computer vision and generative adversarial networks (GANs), are creating new opportunities for producing high-quality, human-like material across multiple domains. Furthermore, the increased digitization of businesses has resulted in a heightened demand for AI-driven solutions to automate processes and enhance user creativity and personalization.
The rising adoption of generative AI across various sectors such as entertainment, healthcare, marketing and design is driving market expansion as enterprises acknowledge its capacity to transform content production, product development and consumer interaction. It is also driven by the proliferation of consumer generative AI applications such as Google’s Bard and OpenAI’s ChatGPT.
Furthermore, the increasing demand for generative AI products may provide approximately US$ 280 billion in additional software income, propelled by specialized assistants, novel infrastructure products and coding copilots. Corporations like as Amazon Web Services, Microsoft, Google and Nvidia may emerge as the primary beneficiaries as corporations increasingly transition workloads to the public cloud.

Dynamics
Rising Demand For Automated Content Creation And Curation
As digital platforms and the Internet advance rapidly, sectors such as media, advertising, gaming and design exhibit an unquenchable demand for varied and captivating content. Deep learning models and generative adversarial networks (GANs) are generative AI technologies that facilitate automated content creation with exceptional realism and creativity, allowing creators to generate substantial quantities of diverse, high-quality multimedia content efficiently and cost-effectively.
Generative AI enables models to be multimodal, allowing simultaneous processing of several modalities, such as images and text, hence expanding their application domains and enhancing their versatility. Generative AI improves the interaction between humans and computers by enabling communication in natural language instead of programming languages.
Generative AI possesses the capacity to revolutionize enterprises by creating novel avenues for automation, innovation and customization, simultaneously reducing expenses and enhancing customer experience. In March 2023, Grammarly, Inc., a US-based AI writing helper, introduced GrammarlyGo, a generative AI function that allows users to create, edit and customize text.

Accelerating Virtual Realities
AI developers often utilize generative AI to construct game landscapes and novel virtual realms. It allows virtual reality (VR) developers to construct an unlimited repository of unique and engaging gaming experiences. Consequently, the implementation of use cases like VR games and VR training simulations yields considerable efficiencies. Consequently, initial implementations of AI in business will probably concentrate on enhancing human capabilities through a workforce including human employees collaborating with intelligent virtual assistants or collaborative robots (cobots). This will substantially propel global market expansion.
In January 2023, Nvidia unveiled new enterprise Metaverse technologies, including Virtual Reality (VR) and Augmented Reality (AR), for various generative AI tools, such as the Omniverse site. The business launched its Omniverse portal with RTX and 3D enhancements, along with an early access program for developers aiming to create avatars and virtual assistants.
Strategic breakthroughs and enhancements initiated by leading competitors are anticipated to drive market expansion. Furthermore, the development and scripting capabilities in numerous virtual world apps are advantageous for designers and programmers. Nonetheless, generative AI is employed to produce 3D models from textual descriptions or 2D animations. It enables people to engage in a profound experience within an unfamiliar 3D environment.

High Training Costs
Acquiring and preparing extensive, diverse datasets can be costly and time-intensive; nonetheless, training data is crucial for instructing AI models to provide precise and realistic outputs. Manual annotation curation and validation processes are often necessary to produce high-quality training data, demanding significant time and expertise from human resources.
Moreover, locating suitable data that precisely represents the intended outcomes across several domains can be challenging and costly, particularly for niche or specialized applications. For startups and smaller enterprises, the costly data preparation demands may act as entry obstacles, hindering their full use of generative AI technology.

Segment Analysis
The global generational AI market is segmented based on type, component, business function, integration mode, end-user and region.

Transforming Content Creation Is Revolutionizing Media And Entertainment
In the media and entertainment industry, generative AI technologies enable content creators to easily generate substantial volumes of high-quality multimedia material at minimal expense, in a context where creativity and differentiation are essential. Generative AI can be employed to generate lifelike characters, compose music, create visual effects and provide tailored recommendations for audiences, resulting in engaging and immersive experiences in gaming, animation and other media.
As media consumption patterns change and the need for diverse and engaging content increases, the media and entertainment industry persistently invests in generative AI technologies to foster innovation and influence the future of content creation and consumption. In January 2023, BuzzFeed, Inc., a US-based internet media, news and entertainment company, revealed a strategy to utilize AI capabilities from OpenAI, an American AI firm, to improve and customize certain content offerings.

Geographical Penetration
Rising Investment, Data Diversity and Cultural Adaptation in Asia-Pacific
Asia-Pacific is projected to experience the most rapid growth, with China, Japan, South Korea and India emerging as frontrunners in AI innovation, propelled by dynamic startup ecosystems and supportive government efforts. City governments in China, including Shanghai, have provided computer vouchers to AI firms to offset the training expenses of large language models (LLMs).
The South Korean Ministry of Science and ICT has allocated US$ 642.5 million for investment in companies developing sophisticated AI processors until 2030. The investment will involve the building of additional data centers and partnerships with cloud service providers and makers of generative AI hardware, alongside other projects.
The population size and diverse language and cultural landscapes of the region, along with the abundance of data, enable the development of generative AI systems that are attuned to the distinct preferences and subtleties of the local populace. For instance, SB Intuitions, a subsidiary of the large Japanese corporation SoftBank, is developing local LLMs specifically designed for the Japanese language. By the conclusion of 2024, SoftBank aims to have these proprietary LLMs completely created, featuring 350 billion parameters.

Competitive Landscape
The major global players in the market include Google, Microsoft, Amazon Web Services, Inc., IBM oracle, Nuance Communications, Inc., FIS, SAP SE, Artificial Solutions and Kore.ai, Inc.

Russia-Ukraine War Impact Analysis
The Russia-Ukraine conflict has highlighted the essential function of AI in contemporary combat, especially generative AI systems that facilitate real-time data analysis, target identification and strategic decision-making. Ukraine, aided by Western allies and private sector collaborations, has utilized AI to analyze extensive battlefield data, improving accuracy in reaction to Russian offensives.
Generative AI facilitates the analysis of information from various sources, including systems, armaments and field communications, enabling Ukrainian forces to uphold a human-centric strategy while leveraging new technology to enhance battlefield intelligence and tactical flexibility. The widespread implementation of AI technology in conflict zones may accelerate significant progress in the generative AI business, particularly within the defense sector.
As Ukraine demonstrates the impact of AI-assisted operations, more nations may invest in developing AI for military use, particularly for analyzing high-stakes, dynamic data environments. The lessons and knowledge acquired from the Ukraine conflict may expedite the enhancement of generative AI technologies and motivate international defense sectors to emphasize AI in strategic operations, influencing the future of military-oriented AI advancements.

Type
• AI Chatbots
• Voice Bots
• Interactive Voice Assistants (IVA)
• Generative AI Agents
Component
• Solutions
• Managed Services
• Professional Services
• Training & Consulting
• System Integration & Implementation
• Support & Maintenance
Business Function
• Sales & Marketing
• Operations & Supply Chain
• Finance & Accounting
• Human Resources (HR)
• IT Service Management (ITSM)
• Others
Integration Mode
• Internal Enterprise Systems
• External Communication Channels
End-User
• BFSI
• Retail & eCommerce
• Education
• Media & Entertainment
• Healthcare & Life Sciences
• Travel & Hospitality
• Automotive
• IT/ITeS
• Government & Defense
• Other
By Region
• North America
o US
o Canada
o Mexico
• Europe
o Germany
o UK
o France
o Italy
o Spain
o Rest of Europe
• South America
o Brazil
o Argentina
o Rest of South America
• Asia-Pacific
o China
o India
o Japan
o Australia
o Rest of Asia-Pacific
• Middle East and Africa

Key Developments
• In March 2024, Microsoft and Adobe declared intentions to integrate Adobe Experience Cloud workflows and insights into Microsoft Copilot. The partnership seeks to utilize Microsoft 365 to assist marketers in overcoming application and data silos while enhancing the management of daily workflows.
• In March 2024, Adobe and NVIDIA, established collaborators in research and development, announced a new collaboration to harness the capabilities of generative AI to enhance creative workflows. Adobe and NVIDIA will together develop a new generation of sophisticated generative AI models, emphasizing deep integration with applications utilized by the foremost artists and marketers globally.
• In February 2024, the GSMA and IBM announced a collaboration to enhance the adoption and proficiency of generative artificial intelligence (AI) in the telecommunications sector by launching the GSMA Advance's AI Training program and the GSMA Foundry Generative AI initiative.
• In February 2024, OpenAI announced the launch of Sora, a generative AI model for text-to-video conversion. Sora is capable of producing films lasting up to one minute while preserving visual quality and conforming to the user's specifications. This model is currently not publically accessible, with restricted access allowed to a select group of red teamers, visual artists, designers and filmmakers.
• In February 2024, Google introduced Gemini 1.5, an enhanced generative AI model featuring extensive context comprehension across various modalities. In the same month, Google announced the introduction of Gemma, a new series of lightweight open-weight devices. The latest models, Gemma 2B and Gemma 7B, were "inspired by Gemini" and are accessible for commercial and research purposes.
• In January 2024, Capgemini and AWS enhanced their strategic partnership to facilitate widespread enterprise use of generative AI. Capgemini and AWS are collaborating to assist clients in understanding the economic value of generative AI while addressing constraints such as cost, scale and trust.

Why Purchase the Report?
• To visualize the global generational AI market segmentation based on type, component, business function, integration mode, end-user and region, as well as understand key commercial assets and players.
• Identify commercial opportunities by analyzing trends and co-development.
• Excel data sheet with numerous data points of the generational AI market level with all segments.
• PDF report consists of a comprehensive analysis after exhaustive qualitative interviews and an in-depth study.
• Product mapping available as excel consisting of key products of all the major players.

The global generational AI market report would provide approximately 78 tables, 85 figures and 212 pages
Target Audience 2024
• Manufacturers/ Buyers
• Industry Investors/Investment Bankers
• Research Professionals
• Emerging Companies

1. Methodology and Scope
1.1. Research Methodology
1.2. Research Objective and Scope of the Report
2. Definition and Overview
3. Executive Summary
3.1. Snippet by Type
3.2. Snippet by Component
3.3. Snippet by Business Function
3.4. Snippet by Integration Mode
3.5. Snippet by End-User
3.6. Snippet by Region
4. Dynamics
4.1. Impacting Factors
4.1.1. Drivers
4.1.1.1. Rising Demand For Automated Content Creation And Curation
4.1.1.2. Accelerating Virtual Realities
4.1.2. Restraints
4.1.2.1. High Training Costs
4.1.3. Opportunity
4.1.4. Impact Analysis
5. Industry Analysis
5.1. Porter's Five Force Analysis
5.2. Supply Chain Analysis
5.3. Pricing Analysis
5.4. Regulatory Analysis
5.5. Russia-Ukraine War Impact Analysis
5.6. DMI Opinion
6. COVID-19 Analysis
6.1. Analysis of COVID-19
6.1.1. Scenario Before COVID-19
6.1.2. Scenario During COVID-19
6.1.3. Scenario Post COVID-19
6.2. Pricing Dynamics Amid COVID-19
6.3. Demand-Supply Spectrum
6.4. Government Initiatives Related to the Market During Pandemic
6.5. Manufacturers Strategic Initiatives
6.6. Conclusion
7. By Type
7.1. Introduction
7.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Type
7.1.2. Market Attractiveness Index, By Type
7.2. AI Chatbots*
7.2.1. Introduction
7.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
7.3. Voice Bots
7.4. Interactive Voice Assistants (IVA)
7.5. Generative AI Agents
8. By Component
8.1. Introduction
8.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
8.1.2. Market Attractiveness Index, By Component
8.2. Solutions*
8.2.1. Introduction
8.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
8.3. Managed Services
8.4. Professional Services
8.5. Training & Consulting
8.6. System Integration & Implementation
8.7. Support & Maintenance
9. By Business Function
9.1. Introduction
9.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Business Function
9.1.2. Market Attractiveness Index, By Business Function
9.2. Sales & Marketing*
9.2.1. Introduction
9.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
9.3. Operations & Supply Chain
9.4. Finance & Accounting
9.5. Human Resources (HR)
9.6. IT Service Management (ITSM)
9.7. Others
10. By Integration Mode
10.1. Introduction
10.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Integration Mode
10.1.2. Market Attractiveness Index, By Integration Mode
10.2. Internal Enterprise Systems*
10.2.1. Introduction
10.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
10.3. External Communication Channels
11. By End-User
11.1. Introduction
11.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
11.1.2. Market Attractiveness Index, By End-User
11.2. BFSI*
11.2.1. Introduction
11.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
11.3. Retail & eCommerce
11.4. Education
11.5. Media & Entertainment
11.6. Healthcare & Life Sciences
11.7. Travel & Hospitality
11.8. Automotive
11.9. IT/ITeS
11.10. Government & Defense
11.11. Other
12. By Region
12.1. Introduction
12.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Region
12.1.2. Market Attractiveness Index, By Region
12.2. North America
12.2.1. Introduction
12.2.2. Key Region-Specific Dynamics
12.2.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Type
12.2.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
12.2.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Business Function
12.2.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Integration Mode
12.2.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
12.2.8. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
12.2.8.1. US
12.2.8.2. Canada
12.2.8.3. Mexico
12.3. Europe
12.3.1. Introduction
12.3.2. Key Region-Specific Dynamics
12.3.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Type
12.3.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
12.3.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Business Function
12.3.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Integration Mode
12.3.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
12.3.8. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
12.3.8.1. Germany
12.3.8.2. UK
12.3.8.3. France
12.3.8.4. Italy
12.3.8.5. Spain
12.3.8.6. Rest of Europe
12.4. South America
12.4.1. Introduction
12.4.2. Key Region-Specific Dynamics
12.4.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Type
12.4.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
12.4.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Business Function
12.4.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Integration Mode
12.4.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
12.4.8. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
12.4.8.1. Brazil
12.4.8.2. Argentina
12.4.8.3. Rest of South America
12.5. Asia-Pacific
12.5.1. Introduction
12.5.2. Key Region-Specific Dynamics
12.5.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Type
12.5.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
12.5.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Business Function
12.5.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Integration Mode
12.5.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
12.5.8. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
12.5.8.1. China
12.5.8.2. India
12.5.8.3. Japan
12.5.8.4. Australia
12.5.8.5. Rest of Asia-Pacific
12.6. Middle East and Africa
12.6.1. Introduction
12.6.2. Key Region-Specific Dynamics
12.6.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Type
12.6.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
12.6.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Business Function
12.6.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Integration Mode
12.6.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
13. Competitive Landscape
13.1. Competitive Scenario
13.2. Market Positioning/Share Analysis
13.3. Mergers and Acquisitions Analysis
14. Company Profiles
14.1. Google*
14.1.1. Company Overview
14.1.2. Product Portfolio and Description
14.1.3. Financial Overview
14.1.4. Key Developments
14.2. Microsoft
14.3. Amazon Web Services, Inc.
14.4. IBM
14.5. Oracle
14.6. Nuance Communications, Inc.
14.7. FIS
14.8. SAP SE
14.9. Artificial Solutions
14.10. Kore.ai, Inc.
LIST NOT EXHAUSTIVE
15. Appendix
15.1. About Us and Services
15.2. Contact Us

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