マーケティング向け人工知能（AI）の世界市場-2023年～2030年

概要

世界のマーケティング向け人工知能（AI）市場は、2022年に127億米ドルに達し、2023-2030年の予測期間中にCAGR 25.1％で成長し、2030年には773億米ドルに達すると予測されています。

業界のデジタル化に伴いデータは増加しています。データはAIの核となる基盤であるため、データが多ければ多いほどAIはマーケティングに役立ちます。AIシステムが容易に取り組める高度なマーケティング活動には、消費者のセグメンテーション、カスタマイズ、予測分析などがあります。高性能なコンピューティング資源に簡単にアクセスできるため、AIは膨大なデータセットを迅速かつ効果的に処理し、リアルタイムの意思決定を可能にします。

例えば、2023年5月25日、著名な人工知能（AI）SaaS企業であるAppier社は、東南アジアの大手小売・eコマースブランドと提携し、マーケティング戦略を変革し、デジタルプラットフォーム全体で高度にパーソナライズされたショッピング体験を提供しています。ジェネレーティブAIの台頭は小売業界に大きな影響を与えており、小売業者はタスクの自動化、パーソナライズされたマーケティング活動の拡大、チャットボットによる顧客サービスサポートの強化、実用的なインサイトの生成を可能にしています。

アジア太平洋は、世界のマーケティング向け人工知能（AI）市場で最大の地域であり、世界市場の1/3以上を占めています。インターネットへのアクセスを有する巨大な人口や、域内の大幅なデジタル化を受けて、膨大なデータの収集が可能で、AI駆動型マーケティングにより有益な考察を提供しています。また、中国、インド、東南アジア諸国などのeコマースプラットフォームの拡大により、AIを活用した提言エンジン、パーソナライゼーション、カスタマーサポートに対する需要が高まっています。

ダイナミクス：

予測分析に対する需要の高まり

定型業務やプロセスの自動化により、法律専門家は法的分析や戦略策定など、より価値の高い業務に集中できるようになり、法律事務所や法務部門における効率性と生産性の向上につながります。自動化により、文書レビュー、契約分析、法務調査などの作業における手作業の必要性を最小限に抑えることができるため、運用コストの削減につながり、予算の最適化を目指す法務組織にとって魅力的です。

Squarkai.comによると、AIと予測分析により、マーケティング担当者は個々の顧客データを分析することで、高度にパーソナライズされたキャンペーンを作成することができます。予測分析はデータ分析を自動化し、時間とリソースを節約します。マーケティング担当者は、より戦略的なタスクに労力を割くことができ、全体的な効率が向上します。Spiralticsによると、2021年には専門家の80％がデータ保護に大きな影響を与えるAIベースのソリューションを導入しています。

企業間のコラボレーションが市場を活性化

企業はコラボレーションを通じて、AIアルゴリズム、データ分析、マーケティングプラットフォーム、特定業界に対する認識など、それぞれの能力を組み合わせることで、より効率的なAIマーケティングソリューションを提供することができます。アイデアの交換や斬新なテクノロジーの研究を促進することで、コラボレーションはイノベーションを促進します。企業は、マーケティングの可能性を広げる最先端のAIツールや方法論を共同で生み出すことができます。

例えば、2023年8月16日、市場情勢デジタルとキルトAIは、高度な人工知能（AI）技術を使用してマーケティングの展望を変革することを目的とした戦略的パートナーシップを締結しました。Langoorの革新的なマーケティング戦略とQuilt AIの診断、予測、生成AIの専門知識を融合させることで、このパートナーシップは、マーケティング担当者がその努力においてAIの可能性を活用する方法に革命をもたらそうとしています。

AIアルゴリズムによるマーケティング能力の強化

より洗練された機械学習モデルとアルゴリズムの構築により、AIのマーケティング能力は大幅に向上しました。これらのモデルやアルゴリズムは、膨大なデータセットを分析し、動向を把握し、驚くほど正確な予測を行うことができるため、マーケティング活動をより成功に導くことができます。ビッグデータ・ソースがより利用しやすくなり、マーケターは豊富なデータを活用・評価する機会を得るようになると、これらの巨大なデータベースはAIによって処理できるようになり、マーケターがデータに基づいて意思決定を下すのに役立つようになります。

例えば、2023年9月12日、コカ・コーラは「コカ・コーラY3000」と呼ばれる新しい飲料を発売しました。これは、人間と人工知能（AI）の両方と共同開発した初のフレーバーとして宣伝されており、この製品はコカ・コーラのクリエーションズ・プラットフォームの一部で、同社の特徴であるソーダを強調しながら若い消費者にアピールすることを目的としています。コカ・コーラY3000は、クリエーション・プラットフォームの他の飲料と同様、特定のフレーバーを強調するのではなく、ユニークなムードや体験を提供することに重点を置いています。コカ・コーラはAIを使って、感情、願望、色、フレーバーを通して人々がどのように未来を思い描くかを理解しました。

不正確または偏ったデータと必要なメンテナンス

AIはデータに大きく依存しており、使用されるデータの質はAIのパフォーマンスに大きく影響します。不正確なデータや偏ったデータは、欠陥のある予測や推奨につながる可能性があります。さらに、AI主導のマーケティングに消費者データを使用すると、プライバシーの問題が生じ、GDPRやCCPAのようなデータ保護法の遵守が求められます。AIは人間の創造性や感情的知性に欠けますが、それでもデータを評価し、データ主導の意思決定を行うことはできます。しかしながら、AIはデータを評価し、データに基づいた意思決定を行うことができます。しかし、純粋に創造的で感情に響くコンテンツを生成し、深いレベルで顧客を惹きつけることは難しいかもしれません。

マーケティングにAIを導入するのは複雑で、リソースを必要とします。AIモデルやシステムを開発・維持するためには、専門的なスキルやノウハウが必要となります。中小企業は、リソースの制約からAIの導入に課題を抱える可能性があります。マーケティングの意思決定をAIのアルゴリズムだけに頼ると、人間の監視が行き届かなくなる可能性があります。人間のマーケティング担当者は、AIが生成したインサイトを解釈し、戦略的な意思決定を行う役割を果たすべきです。

目次

第1章 調査手法と調査範囲

第2章 定義と概要

第3章 エグゼクティブサマリー

第4章 市場力学

• 影響要因
  • 促進要因
    • 予測分析に対する需要の高まり
    • 企業間のコラボレーションが市場を活性化
    • AIアルゴリズムによるマーケティング能力の強化
  • 抑制要因
    • 不正確または偏ったデータとメンテナンスの必要性
  • 影響分析

第5章 業界分析

• ポーターのファイブフォース分析
• サプライチェーン分析
• 価格分析
• 規制分析
• ロシア・ウクライナ戦争の影響分析
• DMIの見解

第6章 COVID-19分析

第7章 提供別

• ハードウェア
• ソフトウェア
• サービス

第8章 展開タイプ別

• クラウド
• オンプレミス

第9章 技術別

• 機械学習
• コンテキストアウェア・コンピューティング
• 自然言語処理
• コンピュータビジョン

第10章 用途別

• ソーシャルメディア広告
• 検索広告
• コンテンツキュレーション
• 販売・マーケティングオートメーション
• 分析プラットフォーム
• その他

第11章 エンドユーザー別

• BFSI
• 小売業
• 消費財
• メディア・エンターテインメント
• 企業
• その他

第12章 地域別

• 北米
  • 米国
  • カナダ
  • メキシコ
• 欧州
  • ドイツ
  • 英国
  • フランス
  • イタリア
  • ロシア
  • その他欧州
• 南米
  • ブラジル
  • アルゼンチン
  • その他南米
• アジア太平洋
  • 中国
  • インド
  • 日本
  • オーストラリア
  • その他アジア太平洋
• 中東・アフリカ

第13章 競合情勢

• 競合シナリオ
• 市況/シェア分析
• M&A分析

第14章 企業プロファイル

• IBM Corporation
  • 会社概要
  • 製品ポートフォリオと説明
  • 財務概要
  • 主な動向
• Intel Corporation
• Alphabet Inc
• Microsoft Corporation
• Twitter, Inc.
• Samsung India Electronics Pvt. Ltd.
• Amazon.com, Inc.
• NVIDIA Corporation
• Albert Technologies Ltd.
• H2O.ai, Inc.

第15章 付録

Overview:

Global Artificial Intelligence (AI) in Marketing Market reached US$ 12.7 billion in 2022 and is expected to reach US$ 77.3 billion by 2030, growing with a CAGR of 25.1% during the forecast period 2023-2030.

Data is increasing as a result of industry digitization. As data is the core foundation of AI, the more data there is, the more useful AI can be for marketing. The sophisticated marketing activities that AI systems can tackle easily include consumer segmentation, customization and predictive analytics. Because high-performance computing resources are easily accessible, AI can process massive datasets rapidly and effectively, enabling real-time decision-making.

For instance, on 25 May 2023, Appier, a prominent artificial intelligence (AI) software-as-a-service company, is partnering with leading retail and e-commerce brands in Southeast Asia to transform their marketing strategies and provide highly personalized shopping experiences across digital platforms. The rise of Generative AI is significantly impacting the retail industry, enabling retailers to automate tasks, scale personalized marketing efforts, enhance chatbot customer service support and generate actionable insights.

Asia-Pacific is among the growing regions in the global artificial intelligence (AI) in marketing market covering more than 1/3rd of the market and with a huge population having access to the internet, the area experienced major digitalization, which has enhanced data collection and provided useful insights for AI-driven marketing and there is a demand for AI-powered recommendation engines, personalization and customer support due to the expansion of e-commerce platforms in nations like China, India and Southeast Asian countries.

Dynamics:

Rising Demand for Predictive Analysis

Automation of routine tasks and processes allows legal professionals to focus on higher-value tasks, such as legal analysis and strategy development and this leads to increased efficiency and productivity within law firms and legal departments. Automation helps reduce operational costs by minimizing the need for manual labor in tasks like document review, contract analysis and legal research, this cost reduction is appealing to legal organizations seeking to optimize their budgets.

According to Squarkai.com, AI and predictive analytics enable marketers to create highly personalized campaigns by analyzing individual customer data and this tailored approach increases customer engagement and conversion rates. Predictive analytics automates data analysis, saving time and resources. Marketers can allocate their efforts to more strategic tasks, improving overall efficiency. According to Spiralytics, in 2021, 80% of professionals have AI-based solutions that have a major impact on data protection.

Collaboration Between Companies Boosts the Market

Companies can combine their capabilities, such as AI algorithms, data analytics, marketing platforms and awareness of particular industries, through collaboration to provide more efficient AI marketing solutions. By encouraging the exchange of ideas and studying novel technologies, collaboration promotes innovation. Companies can collaborate to create cutting-edge AI tools and methodologies that expand the potential of marketing.

For instance, on 16 August 2023, Langoor Digital and Quilt AI entered into a strategic partnership with the aim of transforming the marketing landscape using advanced artificial intelligence (AI) technologies and this collaboration will redefine how marketers engage with and comprehend their audiences. By merging Langoor's innovative marketing strategies with Quilt AI's expertise in Diagnostic, Predictive and Generative AI, this partnership seeks to revolutionize how marketers harness the potential of AI in their endeavors.

Enhancing Marketing Capabilities with AI Algorithms

The creation of more sophisticated machine learning models and algorithms has greatly enhanced AI's marketing capabilities. These models and algorithms can analyze huge datasets, spot trends and make incredibly precise predictions, resulting in more successful marketing efforts. As big data sources become more accessible, marketers will have the opportunity to utilize an abundance of data to use and evaluate, these huge databases can be processed by AI, which will help marketers make decisions based on data.

For instance, on 12 September 2023, Coca-Cola launched a new beverage called Coca-Cola Y3000, which is touted as the first flavor co-created with both human and artificial intelligence (AI) and this product is part of Coca-Cola's Creations platform, which aims to appeal to younger consumers while highlighting its signature soda. Coca-Cola Y3000, like other beverages in the Creations platform, does not emphasize a specific flavor but focuses on providing a unique mood or experience. Coca-Cola used AI to understand how people envision the future through emotions, aspirations, colors and flavors.

Inaccurate or Biased Data and Required Maintenance

AI relies heavily on data and the quality of the data used can significantly impact AI's performance. Inaccurate or biased data can lead to flawed predictions and recommendations. Additionally, using consumer data for AI-driven marketing creates privacy issues and demands compliance with data protection laws like GDPR and CCPA. AI lacks human creativity and emotional intelligence, nevertheless, it can evaluate data and make data-driven decisions. It may struggle to generate genuinely creative and emotionally resonant content that engages customers on a deep level.

Implementing AI in marketing is complex and resource-intensive. It requires specialized skills and expertise to develop and maintain AI models and systems. Small and mid-sized businesses may face challenges in adopting AI due to resource constraints. Relying solely on AI algorithms to make marketing decisions can lead to a lack of human oversight. Human marketers should still play a role in interpreting AI-generated insights and making strategic decisions.

Segment Analysis:

The global artificial intelligence (AI) in marketing market is segmented based on offering, deployment type, technology, application, end-user and region.

Adoption of Cloud-Based Artificial Intelligence (AI) Platforms

The increasing volume of data generated by online activities provides a wealth of information for marketers. Cloud-based AI solutions can efficiently process and analyze this data to derive valuable insights and improve marketing strategies. Cloud-based AI platforms offer scalability, allowing businesses to easily expand their AI capabilities as their marketing needs grow and this scalability is crucial in handling large datasets and complex AI models.

For instance, on 8 May 2023, Salesforce introduced new AI-powered innovations for its Marketing Cloud, aimed as 78% of the marketers say that they drive the market and help companies to create more personalized and humanized interactions with customers. The new features include Einstein Engagement Scoring in Salesforce CDP, Einstein Designer, Interaction Studio Templates and Datorama Connectors. In today's digital-first world, companies need to deliver connected and relevant experiences to meet changing customer expectations.

Geographical Penetration:

Technological Infrastructure and AI-driven Campaign Decisions Boosts the Market

North America is dominating the global artificial intelligence (AI) in marketing market covering more than 1/3rd of the market and the region, particularly U.S., boasts advanced technological infrastructure that supports AI development and deployment and this includes robust cloud computing services, high-speed internet and access to cutting-edge hardware. North America generates huge amounts of data daily and this data serves as the lifeblood of AI, enabling machine learning algorithms to make data-driven marketing decisions.

For instance, on 14 June 2023, Scibids partnered with Tinuiti, a performance marketing agency, to launch the Scibids AI Insights Solution and this solution offers transparency and control over the ad decisioning process within Scibids' AI-powered algorithms, providing media buyers with insights into AI-driven campaign decisions. It analyzes variables such as URLs, creative elements, location and time of day to understand their impact on campaign performance.

Competitive Landscape

The major global players in the market include: IBM Corporation, Intel Corporation, Alphabet Inc, Microsoft Corporation, Twitter, Inc., Samsung India Electronics Pvt. Ltd., Amazon.com, Inc., NVIDIA Corporation, Albert Technologies Ltd. and H2O.ai, Inc.

COVID-19 Impact Analysis

The pandemic forced many businesses to expedite their digital transformation efforts, including the adoption of AI-powered marketing technologies. Physical stores closed and consumers spending more time online, companies turned to AI to enhance their digital marketing strategies. As in-person shopping declined, e-commerce experienced significant growth. AI-driven recommendation engines, chatbots and virtual shopping assistants became essential tools for online retailers to personalize the shopping experience and manage increased customer inquiries.

Content generation and curation tools powered by AI became crucial as companies needed to maintain an online presence and communicate with customers. AI helped create and distribute content at scale while minimizing the need for manual labor. Due to economic uncertainties, many businesses adjusted their marketing budgets. AI tools that provided cost-effective and measurable results gained favor, leading to an increased allocation of resources to AI-driven campaigns.

Consumer behavior changed rapidly during the pandemic. AI was used to analyze these shifts in real time, helping marketers adapt their strategies to meet evolving customer needs and preferences. AI was employed in supply chain and inventory management to predict demand fluctuations, optimize product availability and reduce disruptions caused by supply chain challenges.

AI Impact

AI-powered tools lead to processing a large amount of data in real-time, providing marketers with valuable insights into consumer behavior, preferences and trends, this data-driven approach enables more effective targeting and personalization of marketing campaigns. Marketers could produce highly targeted and relevant content for various audience categories using AI algorithms that can segment customers based on their demographics, behavior and goals, this segmentation boosts audience engagement and conversion rates.

AI enables dynamic content generation and personalized recommendations. Marketers can deliver tailored messages, product recommendations and offers to individual customers, enhancing the customer experience and driving sales. AI-powered chatbots and virtual assistants can provide instant customer support, answer queries and guide users through the purchase process and they offer 24/7 availability and can handle routine tasks, freeing up human agents for more complex issues.

For instance, on 13 September 2023, e-Core, a technology services partner specializing in digital transformation, introduced Orbit AI, a strategic approach to leverage artificial intelligence (AI) for business expansion and productivity enhancement and this initiative aims to boost the productivity of digital services and expedite project delivery times. It empowers e-Core's teams with AI Agents, resulting in significant milestones such as a 55% increase in code delivery speed and a 43% overall productivity improvement since its implementation.

Russia- Ukraine War Impact

The ongoing conflict has created economic uncertainty, both in the region and globally. Economic instability can affect marketing budgets and investment in AI technologies. Companies may become more cautious about adopting new AI marketing tools during uncertain times. The war has strained international relations, leading to increased geopolitical tensions. Such tensions can impact global trade and collaboration, which may affect the availability and accessibility of AI-powered marketing solutions.

The conflict has disrupted supply chains, especially in industries with ties to the region. AI hardware components, software development and data centers can be affected by these disruptions, potentially impacting the AI marketing ecosystem. Geopolitical tensions can lead to concerns about data privacy and security. Companies using AI for marketing must ensure the protection of customer data, especially if they have operations or customers in the affected regions.

By Offering

• Hardware
• Software
• Services

By Deployment Type

• Cloud
• On-Premise

By Deployment Type

• Machine Learning
• Context-Aware Computing
• Natural Language Processing
• Computer Vision

By Application

• Social Media Advertising
• Search Advertising
• Content Curation
• Sales Marketing Automation
• Analytics Platforms
• Others

By End-User

• BFSI
• Retail
• Consumer Goods
• Media Entertainment
• Enterprise
• Others

By Region

• North America
  • U.S.
  • Canada
  • Mexico

• Europe
  • Germany
  • UK
  • France
  • Italy
  • Russia
  • Rest of Europe

• South America
  • Brazil
  • Argentina
  • Rest of South America

• Asia-Pacific
  • China
  • India
  • Japan
  • Australia
  • Rest of Asia-Pacific

• Middle East and Africa

Key Developments

• In March 2023, HubSpot launched two new tools powered by artificial intelligence (AI) Content Assistant and ChatSpot.ai. These tools aim to help customers save time and improve audience engagement. Content Assistant and ChatSpot.ai leverage industry-leading AI systems from OpenAI to enhance efficiency for marketing, sales and customer service professionals.
• In July 2023, Interpublic Group (IPG) and its global creative network McCann Worldgroup joined the Partnership on AI to Benefit People and Society (PAI), becoming the first global marketing and advertising services company to join the group. PAI is a nonprofit partnership that works to advance responsible governance and best practices in artificial intelligence (AI).
• In July 2023, HCL Software launched HCL Marketing Cloud, an AI-powered SaaS solution designed to assist marketers in managing end-to-end marketing needs. It provides predictive and generative AI capabilities, allowing marketers to create tailored campaigns, address complexities across the organization, execute real-time customer behaviors, capitalize on revenue opportunities and deliver connected customer experiences.

Why Purchase the Report?

• To visualize the global artificial intelligence (AI) in marketing market segmentation based on offering, deployment type, technology, application, 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 artificial intelligence (AI) in marketing 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 artificial intelligence (AI) in marketing market report would provide approximately 77 tables, 83 figures and 199 Pages.

Target Audience 2023

• Manufacturers/ Buyers
• Industry Investors/Investment Bankers
• Research Professionals
• Emerging Companies

Table of Contents

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 Offering
• 3.2. Snippet by Deployment Type
• 3.3. Snippet by Technology
• 3.4. Snippet by Application
• 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 Predictive Analysis
    • 4.1.1.2. Collaboration Between Companies Boosts the Market
    • 4.1.1.3. Enhancing Marketing Capabilities with AI Algorithms
  • 4.1.2. Restraints
    • 4.1.2.1. Inaccurate or Baised Data and Required Maintenance Opportunity
  • 4.1.3. 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
  • 6.1.2. Scenario During COVID
  • 6.1.3. Scenario Post COVID
• 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 Offering

• 7.1. Introduction
  • 7.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Offering
  • 7.1.2. Market Attractiveness Index, By Offering
• 7.2. Hardware*
  • 7.2.1. Introduction
  • 7.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
• 7.3. Software
• 7.4. Services

8. By Deployment Type

• 8.1. Introduction
  • 8.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Type
  • 8.1.2. Market Attractiveness Index, By Deployment Type
• 8.2. Cloud*
  • 8.2.1. Introduction
  • 8.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
• 8.3. On Premises

9. By Technology

• 9.1. Introduction
  • 9.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Technology
  • 9.1.2. Market Attractiveness Index, By Technology
• 9.2. Machine Learning*
  • 9.2.1. Introduction
  • 9.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
• 9.3. Context-Aware Computing
• 9.4. Natural Language Processing
• 9.5. Computer Vision

10. By Application

• 10.1. Introduction
  • 10.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
  • 10.1.2. Market Attractiveness Index, By Application
• 10.2. Social Media Advertising*
  • 10.2.1. Introduction
  • 10.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
• 10.3. Search Advertising
• 10.4. Content Curation
• 10.5. Sales Marketing Automation
• 10.6. Analytics Platforms
• 10.7. Others

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
• 11.4. Consumer Goods
• 11.5. Media Entertainment
• 11.6. Enterprise
• 11.7. Others

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 Offering
  • 12.2.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Type
  • 12.2.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Technology
  • 12.2.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
  • 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. U.S.
    • 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 Offering
  • 12.3.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Type
  • 12.3.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Technology
  • 12.3.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
  • 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. Russia
    • 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 Offering
  • 12.4.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Type
  • 12.4.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Technology
  • 12.4.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
  • 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 Offering
  • 12.5.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Type
  • 12.5.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Technology
  • 12.5.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
  • 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 Offering
  • 12.6.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Type
  • 12.6.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Technology
  • 12.6.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
  • 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. IBM Corporation*
  • 14.1.1. Company Overview
  • 14.1.2. Product Portfolio and Description
  • 14.1.3. Financial Overview
  • 14.1.4. Key Developments
• 14.2. Intel Corporation
• 14.3. Alphabet Inc
• 14.4. Microsoft Corporation
• 14.5. Twitter, Inc.
• 14.6. Samsung India Electronics Pvt. Ltd.
• 14.7. Amazon.com, Inc.
• 14.8. NVIDIA Corporation
• 14.9. Albert Technologies Ltd.
• 14.10. H2O.ai, Inc.

LIST NOT EXHAUSTIVE

15. Appendix

• 15.1. About Us and Services
• 15.2. Contact Us