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1360031

全球行銷市場人工智慧 (AI) - 2023-2030

Global Artificial Intelligence (AI) in Marketing Market - 2023-2030

出版日期: 2023年10月11日 | 出版商:

DataM Intelligence | 英文 199 Pages | 商品交期: 約2個工作天內

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簡介目錄

概述：

2022年，全球人工智慧（AI）行銷市場規模達到127億美元，預計到2030年將達到773億美元，2023-2030年預測期間複合年成長率為25.1%。

由於行業數位化，數據不斷增加。資料是人工智慧的核心基礎，資料越多，人工智慧對行銷就越有用。人工智慧系統可以輕鬆應對複雜的行銷活動，包括消費者細分、客製化和預測分析。由於高效能運算資源易於獲取，人工智慧可以快速有效地處理大量資料集，從而實現即時決策。

例如，2023 年 5 月 25 日，著名的人工智慧 (AI) 軟體即服務公司 Appier 正在與東南亞領先的零售和電子商務品牌合作，轉變他們的行銷策略並提供高度個人化的購物體驗跨數位平台。生成式人工智慧的興起正在對零售業產生重大影響，使零售商能夠實現任務自動化、擴大個人化行銷工作、增強聊天機器人客戶服務支援並產生可行的見解。

亞太地區是全球人工智慧（AI）行銷市場成長的地區之一，覆蓋了超過1/3的市場，並且擁有大量接入網際網路的人口，該地區經歷了大規模的數位化，這增強了資料收集並為人工智慧驅動的行銷提供了有用的見解，並且由於中國、印度和東南亞國家等國家電子商務平台的擴張，對人工智慧驅動的推薦引擎、個人化和客戶支援的需求。

動態：

對預測分析的需求不斷成長

日常任務和流程的自動化使法律專業人員能夠專注於更高價值的任務，例如法律分析和策略制定，從而提高律師事務所和法律部門的效率和生產力。自動化透過最大限度地減少文件審查、合約分析和法律研究等任務中對體力勞動的需求，有助於降低營運成本，這種成本降低對於尋求最佳化預算的法律組織來說很有吸引力。

據 Squarkai.com 稱，人工智慧和預測分析使行銷人員能夠透過分析個人客戶資料來創建高度個人化的行銷活動，這種量身定做的方法可以提高客戶參與度和轉換率。預測分析可自動進行資料分析，進而節省時間和資源。行銷人員可以將精力分配到更具策略性的任務上，從而提高整體效率。據 Spiralytics 稱，到 2021 年，80% 的專業人士擁有基於人工智慧的解決方案，對資料保護產生重大影響。

公司間的合作推動市場發展

企業可以透過協作，結合AI演算法、資料分析、行銷平台、產業認知等能力，提供更有效率的AI行銷解決方案。透過鼓勵思想交流和研究新技術，協作促進創新。公司可以合作創建尖端的人工智慧工具和方法，以擴大行銷的潛力。

例如，2023 年8 月16 日，Langoor Digital 和Quilt AI 建立了策略合作夥伴關係，旨在利用先進的人工智慧(AI) 技術改變行銷格局，此次合作將重新定義行銷人員與受眾互動和理解的方式。透過將 Langoor 的創新行銷策略與 Quilt AI 在診斷、預測和生成人工智慧方面的專業知識相結合，此次合作旨在徹底改變行銷人員在其工作中利用人工智慧潛力的方式。

AI演算法提升行銷能力

更複雜的機器學習模型和演算法的創建極大地增強了AI的行銷能力。這些模型和演算法可以分析龐大的資料集、發現趨勢並做出極其精確的預測，從而使行銷工作更加成功。隨著大資料來源變得越來越容易獲取，行銷人員將有機會利用大量資料進行使用和評估，這些龐大的資料庫可以透過人工智慧進行處理，這將有助於行銷人員根據資料做出決策。

例如，2023年9月12日，可口可樂推出了一款名為Coca-Cola Y3000的新飲料，被譽為首款由人類和人工智慧（AI）共同創造的口味，該產品是可口可樂創意的一部分平台，旨在吸引年輕消費者，同時突出其招牌蘇打水。可口可樂Y3000與Creations平台中的其他飲料一樣，並不強調特定的口味，而是專注於提供獨特的心情或體驗。可口可樂利用人工智慧來了解人們如何透過情感、願望、顏色和口味來展望未來。

不準確或有偏差的數據以及所需的維護

人工智慧嚴重依賴資料，所用資料的品質可以顯著影響人工智慧的效能。不準確或有偏見的資料可能會導致有缺陷的預測和建議。此外，使用消費者資料進行人工智慧驅動的行銷會產生隱私問題，並需要遵守 GDPR 和 CCPA 等資料保護法。人工智慧缺乏人類的創造力和情緒智商，但它可以評估資料並做出數據驅動的決策。它可能很難產生真正有創意且能引起情感共鳴的內容，從而深入吸引客戶。

在行銷中實施人工智慧是複雜且資源密集的。開發和維護人工智慧模型和系統需要專門的技能和專業知識。由於資源限制，中小企業在採用人工智慧方面可能面臨挑戰。僅依靠人工智慧演算法來做出行銷決策可能會導致缺乏人工監督。人類行銷人員仍然應該在解釋人工智慧產生的見解和製定策略決策方面發揮作用。

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

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