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市场调查报告书
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人工智慧训练资料集集市场：按类型、最终用户划分 - 2025-2030 年全球预测

AI Training Dataset Market by Type (Audio, Image/Video, Text), End-User (Automotive, Banking, Financial Services & Insurance (BFSI), Government) - Global Forecast 2025-2030
出版日期: | 出版商: 360iResearch | 英文 191 Pages | 商品交期: 最快1-2个工作天内

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2023年人工智慧训练资料集市场价值为17.1亿美元，预计到2024年将达到21.2亿美元，复合年增长率为26.41%，预计到2030年将达到88.3亿美元。

人工智慧训练资料集集市场是更广泛的人工智慧产业中快速发展的部分，专注于提供训练强大的人工智慧模型所需的结构化资料。其范围广泛涵盖各种资料类型，包括从不同来源收集的图像、文字、音频和视频，用于训练人工智慧演算法。由于医疗保健、汽车、金融和零售等行业对人工智慧应用的需求不断增长，该市场极为重要。 AI 模型的效能与用于训练的资料集集直接相关，因此对高品质、多样化和代表性资料的需求至关重要。 AI 训练资料集集用于多种领域，包括聊天机器人、自动驾驶汽车、医疗诊断和情绪分析。最终用途应用正在扩展到包括需要业务效率、改善的客户体验和先进分析能力的行业。

主要市场统计
基准年[2023] 17.1亿美元
预测年份 [2024] 21.2亿美元
预测年份 [2030] 88.3亿美元
复合年增长率（%） 26.41%

影响该市场的主要成长要素包括人工智慧技术的快速成长、机器学习演算法的进步以及对大规模资料集集有效训练这些模型的需求。人工智慧在新兴领域和地区的不断渗透将创造巨大的商机。公司可以透过投资资料收集和註释技术并建立伙伴关係来存取不同的资料集集来利用这些优势。然而，资料隐私问题、资料使用的道德问题以及资料管理和标籤的高成本等挑战可能会阻碍市场成长。

合成资料生成、联合学习和自动资料标记等领域的创新对于克服这些挑战至关重要。研究资料公平性和消除偏见的最佳实践也可以提供竞争优势。在技​​术进步和不断变化的监管环境的推动下，市场本质上是高度动态的。回应这些变化并主动调整您的策略可以为您带来显着的优势。随着人工智慧渗透到各个领域，训练资料集集的角色将变得更加重要，重点是高品质、易于存取且来源合乎道德的资料。

市场动态：揭示快速发展的人工智慧训练资料集市场的关键市场洞察

供需的动态交互作用正在改变人工智慧训练资料集集市场。了解这些不断变化的市场动态可以帮助企业做出明智的投资决策、策略决策并抓住新的商机。全面了解这些趋势可以帮助企业降低政治、地理、技术、社会和经济领域的风险，同时消费行为及其对製造成本的影响以及对采购趋势的影响。

  • 市场驱动因素
    • 透过工业领域的人工智慧整合实现工业营运自动化
    • 政府支持的人工智慧在各个最终用户产业整合的倡议
  • 市场限制因素
    • AI训练资料集的局限性
  • 市场机会
    • AI训练资料模型的技术进步
    • 有利的投资环境为人工智慧训练资料平台提供动力
  • 市场挑战
    • 资料标籤和基准测试问题

波特五力：驾驭人工智慧训练资料集市场的策略工具

波特五力框架是了解人工智慧训练资料集市场竞争格局的关键工具。波特的五力框架为评估公司的竞争地位和探索策略机会提供了清晰的方法。该框架可帮助公司评估市场动态并确定新业务的盈利。这些见解使公司能够利用自己的优势，解决弱点并避免潜在的挑战，从而确保更强大的市场地位。

PESTLE分析：了解人工智慧训练资料集集市场的外部影响

外部宏观环境因素在塑造人工智慧训练资料集市场的绩效动态方面发挥着至关重要的作用。对政治、经济、社会、技术、法律和环境因素的分析提供了应对这些影响所需的资讯。透过调查 PESTLE 因素，公司可以更了解潜在的风险和机会。这种分析可以帮助公司预测法规、消费者偏好和经济趋势的变化，并为他们做出积极主动的决策做好准备。

市场占有率分析 了解AI训练资料集集市场的竞争格局

对人工智慧训练资料集集市场的详细市场占有率分析可以对供应商绩效进行全面评估。公司可以透过比较收益、客户群和成长率等关键指标来发现自己的竞争定位。该分析揭示了市场集中、分散和整合的趋势，为供应商提供了製定策略决策所需的洞察力，使他们能够在日益激烈的竞争中占有一席之地。

FPNV 定位矩阵人工智慧训练资料集集市场供应商的绩效评估

FPNV 定位矩阵是评估 AI 训练资料集集市场供应商的关键工具。此矩阵允许业务组织根据供应商的商务策略和产品满意度评估供应商，从而做出符合其目标的明智决策。四个象限清楚且准确地划分了供应商，帮助使用者辨识最能满足其策略目标的合作伙伴和解决方案。

本报告提供了涵盖关键重点领域的全面市场分析：

1. 市场渗透率：对当前市场环境的详细回顾，包括行业主要企业的大量资料。

2. 市场开拓：辨识新兴市场的成长机会，评估现有领域的扩张潜力，并提供未来成长的策略蓝图。

3. 市场多元化：分析近期产品发布、开拓地区、关键产业进展、塑造市场的策略投资。

4. 竞争评估与情报：彻底分析竞争格局，检验市场占有率、业务策略、产品系列、认证、监理核准、专利趋势、主要企业的技术进步等。

5. 产品开发与创新：重点在于有望推动未来市场成长的最尖端科技、研发活动和产品创新。

我们也回答重要问题，以帮助相关人员做出明智的决策：

1.目前的市场规模和未来的成长预测是多少？

2. 哪些产品、区隔市场和地区提供最佳投资机会？

3.塑造市场的主要技术趋势和监管影响是什么？

4.主要厂商的市场占有率和竞争地位如何？

5. 推动供应商市场进入和退出策略的收益来源和策略机会是什么？

目录

第一章 前言

第二章调查方法

第三章执行摘要

第四章市场概况

第五章市场洞察

  • 市场动态
    • 促进因素
      • 透过人工智慧在工业领域的整合实现工业营运自动化
      • 政府支持人工智慧在各终端用户产业整合的倡议
    • 抑制因素
      • AI训练资料集的局限性
    • 机会
      • AI训练资料模型的技术进步
      • 有利的投资环境为人工智慧培训资料平台提供动力
    • 任务
      • 资料标籤和基准测试问题
  • 市场区隔分析
    • 类型：采用以文本为基础的AI训练资料集集进行各行业的文本分类与情感分析
    • 最终用户：全球资讯科技中心的扩张需要采用先进的人工智慧训练资料集
  • 波特五力分析
  • PESTEL分析
    • 政治的
    • 经济
    • 社群
    • 技术的
    • 合法地
    • 环境

第 6 章 AI 训练资料集市场：按类型

  • 音讯的
  • 图片/影片
  • 句子

第七章 人工智慧训练资料集市场：按最终用户划分

  • 车
  • 银行、金融服务和保险 (BFSI)
  • 政府
  • 卫生保健
  • 资讯科技
  • 零售/电子商务

第 8 章美洲人工智慧训练资料集市场

  • 阿根廷
  • 巴西
  • 加拿大
  • 墨西哥
  • 美国

第九章亚太人工智慧训练资料集市场

  • 澳洲
  • 中国
  • 印度
  • 印尼
  • 日本
  • 马来西亚
  • 菲律宾
  • 新加坡
  • 韩国
  • 台湾
  • 泰国
  • 越南

第十章 欧洲/中东/非洲AI训练资料集市场

  • 丹麦
  • 埃及
  • 芬兰
  • 法国
  • 德国
  • 以色列
  • 义大利
  • 荷兰
  • 奈及利亚
  • 挪威
  • 波兰
  • 卡达
  • 俄罗斯
  • 沙乌地阿拉伯
  • 南非
  • 西班牙
  • 瑞典
  • 瑞士
  • 土耳其
  • 阿拉伯聯合大公国
  • 英国

第十一章竞争格局

  • 2023 年市场占有率分析
  • FPNV 定位矩阵，2023
  • 竞争情境分析
    • IBM 和 SAP SE 凭藉着增强型人工智慧和特定产业云端解决方案向前迈进
    • 华为在GITEX GLOBAL 2023发布面向大型模型时代的AI储存新品
    • Meta 的新人工智慧聊天机器人接受了来自 Facebook 和 Instagram 的公共贴文的训练
    • Railtown AI 发布基于知识的人工智慧助理并申请人工智慧临时专利
    • IBM 承诺在三年内培训 200 万人接受人工智慧培训，特别关注代表性不足的社区
    • 诺基亚发布了在 Google Cloud 上运行的 AVA Data Suite，以加速 AI/ML 开发。
    • CGI 将投资 10 亿美元扩展其人工智慧能力，帮助客户设计和执行负责任的、投资回报率主导的策略。
    • Databricks 完成对 MosaicML 的收购
    • RWS 推出用于自然语言处理的人工智慧训练资料集
    • 澳鹏发布三款新产品，用于建构可靠的生成式人工智慧应用
    • BioNTech 收购 InstaDeep，以加强在人工智慧驱动的药物发现、设计和开发领域的地位
    • Accenture与Google云端扩大伙伴关係，加速释放技术、资料和人工智慧的价值

公司名单

  • ADLINK Technology Inc.
  • Alegion Inc.
  • Amazon Web Services, Inc.
  • Anolytics
  • Appen Limited
  • Atos SE
  • Automaton AI Infosystem Pvt. Ltd.
  • Clarifai, Inc.
  • Clickworker GmbH
  • Cogito Tech LLC
  • DataClap
  • DataRobot, Inc.
  • Deep Vision Data by Kinetic Vision
  • Deeply, Inc.
  • Google LLC by Alphabet, Inc.
  • Gretel Labs, Inc.
  • Huawei Technologies Co., Ltd.
  • International Business Machines Corporation
  • Lionbridge Technologies, LLC
  • Meta Platforms, Inc.
  • Microsoft Corporation
  • Mindtech Global Limited
  • Mostly AI Solutions MP GmbH
  • NVIDIA Corporation
  • Oracle Corporation
  • PIXTA Inc.
  • Samasource Impact Sourcing, Inc.
  • SAP SE
  • Scale AI, Inc.
  • Siemens AG
  • Snorkel AI, Inc.
  • Sony Group Corporation
  • SuperAnnotate AI, Inc.
  • TagX
  • UniCourt Inc.
  • Wisepl Private Limited
Product Code: MRR-742BD517A2F2

The AI Training Dataset Market was valued at USD 1.71 billion in 2023, expected to reach USD 2.12 billion in 2024, and is projected to grow at a CAGR of 26.41%, to USD 8.83 billion by 2030.

The AI Training Dataset market is a rapidly evolving segment within the broader AI industry, focusing on providing structured data required for training robust AI models. Its scope broadly covers various data types including images, text, audio, and video collected from diverse sources to train AI algorithms. This market is crucial due to the growing demand for AI applications in industries such as healthcare, automotive, finance, and retail. The necessity for high-quality, diverse, and representative data is paramount, as the performance of AI models is directly linked to the datasets used for training. Application-wise, AI training datasets find use in developing chatbots, autonomous vehicles, medical diagnostics, sentiment analysis, and many other domains. The end-use scope extends to industries seeking operational efficiencies, enhanced customer experiences, and advanced analytical capabilities.

KEY MARKET STATISTICS
Base Year [2023] USD 1.71 billion
Estimated Year [2024] USD 2.12 billion
Forecast Year [2030] USD 8.83 billion
CAGR (%) 26.41%

Key growth factors influencing this market include the exponential growth of AI technologies, advancements in machine learning algorithms, and the need for large-scale datasets to train these models effectively. The increasing penetration of AI in emerging sectors and regions opens up significant opportunities. Companies can capitalize on these by investing in data acquisition, annotation technologies, and forming partnerships to access diversified datasets. However, challenges such as data privacy concerns, ethical issues surrounding data use, and the high cost of data curation and labeling can hinder market growth.

To navigate these challenges, innovation in areas like synthetic data generation, federated learning, and automated data labeling becomes essential. Researching best practices for ensuring data fairness and bias elimination can also offer competitive advantages. The nature of the market is highly dynamic, driven by technological advancements and evolving regulatory landscapes. Staying attuned to these changes and proactively adapting strategies can offer a significant edge. As AI's footprint across sectors broadens, the role of training datasets becomes even more critical, placing a premium on high-quality, accessible, and ethically sourced data.

Market Dynamics: Unveiling Key Market Insights in the Rapidly Evolving AI Training Dataset Market

The AI Training Dataset Market is undergoing transformative changes driven by a dynamic interplay of supply and demand factors. Understanding these evolving market dynamics prepares business organizations to make informed investment decisions, refine strategic decisions, and seize new opportunities. By gaining a comprehensive view of these trends, business organizations can mitigate various risks across political, geographic, technical, social, and economic domains while also gaining a clearer understanding of consumer behavior and its impact on manufacturing costs and purchasing trends.

  • Market Drivers
    • Integration of AI in industrial sectors to automate industrial operations
    • Supportive government initiatives for AI-integration across various end-user industries
  • Market Restraints
    • Limitations of AI training datasets
  • Market Opportunities
    • Technological advancements in AI training data models
    • Favorable investment landscape to enhance AI training data platforms
  • Market Challenges
    • Issues with the data labeling and benchmarking

Porter's Five Forces: A Strategic Tool for Navigating the AI Training Dataset Market

Porter's five forces framework is a critical tool for understanding the competitive landscape of the AI Training Dataset Market. It offers business organizations with a clear methodology for evaluating their competitive positioning and exploring strategic opportunities. This framework helps businesses assess the power dynamics within the market and determine the profitability of new ventures. With these insights, business organizations can leverage their strengths, address weaknesses, and avoid potential challenges, ensuring a more resilient market positioning.

PESTLE Analysis: Navigating External Influences in the AI Training Dataset Market

External macro-environmental factors play a pivotal role in shaping the performance dynamics of the AI Training Dataset Market. Political, Economic, Social, Technological, Legal, and Environmental factors analysis provides the necessary information to navigate these influences. By examining PESTLE factors, businesses can better understand potential risks and opportunities. This analysis enables business organizations to anticipate changes in regulations, consumer preferences, and economic trends, ensuring they are prepared to make proactive, forward-thinking decisions.

Market Share Analysis: Understanding the Competitive Landscape in the AI Training Dataset Market

A detailed market share analysis in the AI Training Dataset Market provides a comprehensive assessment of vendors' performance. Companies can identify their competitive positioning by comparing key metrics, including revenue, customer base, and growth rates. This analysis highlights market concentration, fragmentation, and trends in consolidation, offering vendors the insights required to make strategic decisions that enhance their position in an increasingly competitive landscape.

FPNV Positioning Matrix: Evaluating Vendors' Performance in the AI Training Dataset Market

The Forefront, Pathfinder, Niche, Vital (FPNV) Positioning Matrix is a critical tool for evaluating vendors within the AI Training Dataset Market. This matrix enables business organizations to make well-informed decisions that align with their goals by assessing vendors based on their business strategy and product satisfaction. The four quadrants provide a clear and precise segmentation of vendors, helping users identify the right partners and solutions that best fit their strategic objectives.

Key Company Profiles

The report delves into recent significant developments in the AI Training Dataset Market, highlighting leading vendors and their innovative profiles. These include ADLINK Technology Inc., Alegion Inc., Amazon Web Services, Inc., Anolytics, Appen Limited, Atos SE, Automaton AI Infosystem Pvt. Ltd., Clarifai, Inc., Clickworker GmbH, Cogito Tech LLC, DataClap, DataRobot, Inc., Deep Vision Data by Kinetic Vision, Deeply, Inc., Google LLC by Alphabet, Inc., Gretel Labs, Inc., Huawei Technologies Co., Ltd., International Business Machines Corporation, Lionbridge Technologies, LLC, Meta Platforms, Inc., Microsoft Corporation, Mindtech Global Limited, Mostly AI Solutions MP GmbH, NVIDIA Corporation, Oracle Corporation, PIXTA Inc., Samasource Impact Sourcing, Inc., SAP SE, Scale AI, Inc., Siemens AG, Snorkel AI, Inc., Sony Group Corporation, SuperAnnotate AI, Inc., TagX, UniCourt Inc., and Wisepl Private Limited.

Market Segmentation & Coverage

This research report categorizes the AI Training Dataset Market to forecast the revenues and analyze trends in each of the following sub-markets:

  • Based on Type, market is studied across Audio, Image/Video, and Text.
  • Based on End-User, market is studied across Automotive, Banking, Financial Services & Insurance (BFSI), Government, Healthcare, Information Technology, and Retail & e-Commerce.
  • Based on Region, market is studied across Americas, Asia-Pacific, and Europe, Middle East & Africa. The Americas is further studied across Argentina, Brazil, Canada, Mexico, and United States. The United States is further studied across Arizona, California, Florida, Illinois, Indiana, Massachusetts, Nevada, New Jersey, New York, Ohio, Pennsylvania, and Texas. The Asia-Pacific is further studied across Australia, China, India, Indonesia, Japan, Malaysia, Philippines, Singapore, South Korea, Taiwan, Thailand, and Vietnam. The Europe, Middle East & Africa is further studied across Denmark, Egypt, Finland, France, Germany, Israel, Italy, Netherlands, Nigeria, Norway, Poland, Qatar, Russia, Saudi Arabia, South Africa, Spain, Sweden, Switzerland, Turkey, United Arab Emirates, and United Kingdom.

The report offers a comprehensive analysis of the market, covering key focus areas:

1. Market Penetration: A detailed review of the current market environment, including extensive data from top industry players, evaluating their market reach and overall influence.

2. Market Development: Identifies growth opportunities in emerging markets and assesses expansion potential in established sectors, providing a strategic roadmap for future growth.

3. Market Diversification: Analyzes recent product launches, untapped geographic regions, major industry advancements, and strategic investments reshaping the market.

4. Competitive Assessment & Intelligence: Provides a thorough analysis of the competitive landscape, examining market share, business strategies, product portfolios, certifications, regulatory approvals, patent trends, and technological advancements of key players.

5. Product Development & Innovation: Highlights cutting-edge technologies, R&D activities, and product innovations expected to drive future market growth.

The report also answers critical questions to aid stakeholders in making informed decisions:

1. What is the current market size, and what is the forecasted growth?

2. Which products, segments, and regions offer the best investment opportunities?

3. What are the key technology trends and regulatory influences shaping the market?

4. How do leading vendors rank in terms of market share and competitive positioning?

5. What revenue sources and strategic opportunities drive vendors' market entry or exit strategies?

Table of Contents

1. Preface

  • 1.1. Objectives of the Study
  • 1.2. Market Segmentation & Coverage
  • 1.3. Years Considered for the Study
  • 1.4. Currency & Pricing
  • 1.5. Language
  • 1.6. Stakeholders

2. Research Methodology

  • 2.1. Define: Research Objective
  • 2.2. Determine: Research Design
  • 2.3. Prepare: Research Instrument
  • 2.4. Collect: Data Source
  • 2.5. Analyze: Data Interpretation
  • 2.6. Formulate: Data Verification
  • 2.7. Publish: Research Report
  • 2.8. Repeat: Report Update

3. Executive Summary

4. Market Overview

5. Market Insights

  • 5.1. Market Dynamics
    • 5.1.1. Drivers
      • 5.1.1.1. Integration of AI in industrial sectors to automate industrial operations
      • 5.1.1.2. Supportive government initiatives for AI-integration across various end-user industries
    • 5.1.2. Restraints
      • 5.1.2.1. Limitations of AI training datasets
    • 5.1.3. Opportunities
      • 5.1.3.1. Technological advancements in AI training data models
      • 5.1.3.2. Favorable investment landscape to enhance AI training data platforms
    • 5.1.4. Challenges
      • 5.1.4.1. Issues with the data labeling and benchmarking
  • 5.2. Market Segmentation Analysis
    • 5.2.1. Type: Adoption of text-based AI training datasets for text classification and sentiment analysis in various industries
    • 5.2.2. End-user: Expansion of information technology hubs across the world necessitating deployment of advanced AI training dataset
  • 5.3. Porter's Five Forces Analysis
    • 5.3.1. Threat of New Entrants
    • 5.3.2. Threat of Substitutes
    • 5.3.3. Bargaining Power of Customers
    • 5.3.4. Bargaining Power of Suppliers
    • 5.3.5. Industry Rivalry
  • 5.4. PESTLE Analysis
    • 5.4.1. Political
    • 5.4.2. Economic
    • 5.4.3. Social
    • 5.4.4. Technological
    • 5.4.5. Legal
    • 5.4.6. Environmental

6. AI Training Dataset Market, by Type

  • 6.1. Introduction
  • 6.2. Audio
  • 6.3. Image/Video
  • 6.4. Text

7. AI Training Dataset Market, by End-User

  • 7.1. Introduction
  • 7.2. Automotive
  • 7.3. Banking, Financial Services & Insurance (BFSI)
  • 7.4. Government
  • 7.5. Healthcare
  • 7.6. Information Technology
  • 7.7. Retail & e-Commerce

8. Americas AI Training Dataset Market

  • 8.1. Introduction
  • 8.2. Argentina
  • 8.3. Brazil
  • 8.4. Canada
  • 8.5. Mexico
  • 8.6. United States

9. Asia-Pacific AI Training Dataset Market

  • 9.1. Introduction
  • 9.2. Australia
  • 9.3. China
  • 9.4. India
  • 9.5. Indonesia
  • 9.6. Japan
  • 9.7. Malaysia
  • 9.8. Philippines
  • 9.9. Singapore
  • 9.10. South Korea
  • 9.11. Taiwan
  • 9.12. Thailand
  • 9.13. Vietnam

10. Europe, Middle East & Africa AI Training Dataset Market

  • 10.1. Introduction
  • 10.2. Denmark
  • 10.3. Egypt
  • 10.4. Finland
  • 10.5. France
  • 10.6. Germany
  • 10.7. Israel
  • 10.8. Italy
  • 10.9. Netherlands
  • 10.10. Nigeria
  • 10.11. Norway
  • 10.12. Poland
  • 10.13. Qatar
  • 10.14. Russia
  • 10.15. Saudi Arabia
  • 10.16. South Africa
  • 10.17. Spain
  • 10.18. Sweden
  • 10.19. Switzerland
  • 10.20. Turkey
  • 10.21. United Arab Emirates
  • 10.22. United Kingdom

11. Competitive Landscape

  • 11.1. Market Share Analysis, 2023
  • 11.2. FPNV Positioning Matrix, 2023
  • 11.3. Competitive Scenario Analysis
    • 11.3.1. IBM and SAP SE Forge Ahead with Enhanced AI and Industry-Specific Cloud Solutions
    • 11.3.2. Huawei Launches New AI Storage Product for the Era of Large Model at GITEX GLOBAL 2023
    • 11.3.3. Meta's new AI chatbot trained on public Facebook and Instagram posts
    • 11.3.4. Railtown AI Launches Knowledge-based AI Assistant and Files Provisional Patent Application Relating to AI
    • 11.3.5. IBM Commits to Train 2 Million in Artificial Intelligence in Three Years, with a Focus on Underrepresented Communities
    • 11.3.6. Nokia launches AVA Data Suite to run on Google Cloud to facilitate AI/ML development
    • 11.3.7. CGI to Invest USD 1 Billion On Expansion Of Ai Capabilities To Help Clients Design And Deliver Responsible, Roi-Led Strategies
    • 11.3.8. Databricks Completes Acquisition of MosaicML
    • 11.3.9. RWS Launches AI Training Dataset for Natural Language Processing
    • 11.3.10. Appen Launches Three New Products to Build Trustworthy Generative AI Applications
    • 11.3.11. BioNTech to Acquire InstaDeep to Strengthen the Position in the Field of AI-powered Drug Discovery, Design and Development
    • 11.3.12. Accenture and Google Cloud Expand Partnership to Accelerate Value from Technology, Data and AI

Companies Mentioned

  • 1. ADLINK Technology Inc.
  • 2. Alegion Inc.
  • 3. Amazon Web Services, Inc.
  • 4. Anolytics
  • 5. Appen Limited
  • 6. Atos SE
  • 7. Automaton AI Infosystem Pvt. Ltd.
  • 8. Clarifai, Inc.
  • 9. Clickworker GmbH
  • 10. Cogito Tech LLC
  • 11. DataClap
  • 12. DataRobot, Inc.
  • 13. Deep Vision Data by Kinetic Vision
  • 14. Deeply, Inc.
  • 15. Google LLC by Alphabet, Inc.
  • 16. Gretel Labs, Inc.
  • 17. Huawei Technologies Co., Ltd.
  • 18. International Business Machines Corporation
  • 19. Lionbridge Technologies, LLC
  • 20. Meta Platforms, Inc.
  • 21. Microsoft Corporation
  • 22. Mindtech Global Limited
  • 23. Mostly AI Solutions MP GmbH
  • 24. NVIDIA Corporation
  • 25. Oracle Corporation
  • 26. PIXTA Inc.
  • 27. Samasource Impact Sourcing, Inc.
  • 28. SAP SE
  • 29. Scale AI, Inc.
  • 30. Siemens AG
  • 31. Snorkel AI, Inc.
  • 32. Sony Group Corporation
  • 33. SuperAnnotate AI, Inc.
  • 34. TagX
  • 35. UniCourt Inc.
  • 36. Wisepl Private Limited

LIST OF FIGURES

  • FIGURE 1. AI TRAINING DATASET MARKET RESEARCH PROCESS
  • FIGURE 2. AI TRAINING DATASET MARKET SIZE, 2023 VS 2030
  • FIGURE 3. GLOBAL AI TRAINING DATASET MARKET SIZE, 2018-2030 (USD MILLION)
  • FIGURE 4. GLOBAL AI TRAINING DATASET MARKET SIZE, BY REGION, 2023 VS 2024 VS 2030 (USD MILLION)
  • FIGURE 5. GLOBAL AI TRAINING DATASET MARKET SIZE, BY COUNTRY, 2023 VS 2024 VS 2030 (USD MILLION)
  • FIGURE 6. GLOBAL AI TRAINING DATASET MARKET SIZE, BY TYPE, 2023 VS 2030 (%)
  • FIGURE 7. GLOBAL AI TRAINING DATASET MARKET SIZE, BY TYPE, 2023 VS 2024 VS 2030 (USD MILLION)
  • FIGURE 8. GLOBAL AI TRAINING DATASET MARKET SIZE, BY END-USER, 2023 VS 2030 (%)
  • FIGURE 9. GLOBAL AI TRAINING DATASET MARKET SIZE, BY END-USER, 2023 VS 2024 VS 2030 (USD MILLION)
  • FIGURE 10. AMERICAS AI TRAINING DATASET MARKET SIZE, BY COUNTRY, 2023 VS 2030 (%)
  • FIGURE 11. AMERICAS AI TRAINING DATASET MARKET SIZE, BY COUNTRY, 2023 VS 2024 VS 2030 (USD MILLION)
  • FIGURE 12. UNITED STATES AI TRAINING DATASET MARKET SIZE, BY STATE, 2023 VS 2030 (%)
  • FIGURE 13. UNITED STATES AI TRAINING DATASET MARKET SIZE, BY STATE, 2023 VS 2024 VS 2030 (USD MILLION)
  • FIGURE 14. ASIA-PACIFIC AI TRAINING DATASET MARKET SIZE, BY COUNTRY, 2023 VS 2030 (%)
  • FIGURE 15. ASIA-PACIFIC AI TRAINING DATASET MARKET SIZE, BY COUNTRY, 2023 VS 2024 VS 2030 (USD MILLION)
  • FIGURE 16. EUROPE, MIDDLE EAST & AFRICA AI TRAINING DATASET MARKET SIZE, BY COUNTRY, 2023 VS 2030 (%)
  • FIGURE 17. EUROPE, MIDDLE EAST & AFRICA AI TRAINING DATASET MARKET SIZE, BY COUNTRY, 2023 VS 2024 VS 2030 (USD MILLION)
  • FIGURE 18. AI TRAINING DATASET MARKET SHARE, BY KEY PLAYER, 2023
  • FIGURE 19. AI TRAINING DATASET MARKET, FPNV POSITIONING MATRIX, 2023

LIST OF TABLES

  • TABLE 1. AI TRAINING DATASET MARKET SEGMENTATION & COVERAGE
  • TABLE 2. UNITED STATES DOLLAR EXCHANGE RATE, 2018-2023
  • TABLE 3. GLOBAL AI TRAINING DATASET MARKET SIZE, 2018-2030 (USD MILLION)
  • TABLE 4. GLOBAL AI TRAINING DATASET MARKET SIZE, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 5. GLOBAL AI TRAINING DATASET MARKET SIZE, BY COUNTRY, 2018-2030 (USD MILLION)
  • TABLE 6. AI TRAINING DATASET MARKET DYNAMICS
  • TABLE 7. GLOBAL AI TRAINING DATASET MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 8. GLOBAL AI TRAINING DATASET MARKET SIZE, BY AUDIO, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 9. GLOBAL AI TRAINING DATASET MARKET SIZE, BY IMAGE/VIDEO, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 10. GLOBAL AI TRAINING DATASET MARKET SIZE, BY TEXT, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 11. GLOBAL AI TRAINING DATASET MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 12. GLOBAL AI TRAINING DATASET MARKET SIZE, BY AUTOMOTIVE, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 13. GLOBAL AI TRAINING DATASET MARKET SIZE, BY BANKING, FINANCIAL SERVICES & INSURANCE (BFSI), BY REGION, 2018-2030 (USD MILLION)
  • TABLE 14. GLOBAL AI TRAINING DATASET MARKET SIZE, BY GOVERNMENT, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 15. GLOBAL AI TRAINING DATASET MARKET SIZE, BY HEALTHCARE, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 16. GLOBAL AI TRAINING DATASET MARKET SIZE, BY INFORMATION TECHNOLOGY, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 17. GLOBAL AI TRAINING DATASET MARKET SIZE, BY RETAIL & E-COMMERCE, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 18. AMERICAS AI TRAINING DATASET MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 19. AMERICAS AI TRAINING DATASET MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 20. AMERICAS AI TRAINING DATASET MARKET SIZE, BY COUNTRY, 2018-2030 (USD MILLION)
  • TABLE 21. ARGENTINA AI TRAINING DATASET MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 22. ARGENTINA AI TRAINING DATASET MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 23. BRAZIL AI TRAINING DATASET MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 24. BRAZIL AI TRAINING DATASET MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 25. CANADA AI TRAINING DATASET MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 26. CANADA AI TRAINING DATASET MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 27. MEXICO AI TRAINING DATASET MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 28. MEXICO AI TRAINING DATASET MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 29. UNITED STATES AI TRAINING DATASET MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 30. UNITED STATES AI TRAINING DATASET MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 31. UNITED STATES AI TRAINING DATASET MARKET SIZE, BY STATE, 2018-2030 (USD MILLION)
  • TABLE 32. ASIA-PACIFIC AI TRAINING DATASET MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 33. ASIA-PACIFIC AI TRAINING DATASET MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 34. ASIA-PACIFIC AI TRAINING DATASET MARKET SIZE, BY COUNTRY, 2018-2030 (USD MILLION)
  • TABLE 35. AUSTRALIA AI TRAINING DATASET MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 36. AUSTRALIA AI TRAINING DATASET MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 37. CHINA AI TRAINING DATASET MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 38. CHINA AI TRAINING DATASET MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 39. INDIA AI TRAINING DATASET MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 40. INDIA AI TRAINING DATASET MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 41. INDONESIA AI TRAINING DATASET MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 42. INDONESIA AI TRAINING DATASET MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 43. JAPAN AI TRAINING DATASET MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 44. JAPAN AI TRAINING DATASET MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 45. MALAYSIA AI TRAINING DATASET MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 46. MALAYSIA AI TRAINING DATASET MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 47. PHILIPPINES AI TRAINING DATASET MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 48. PHILIPPINES AI TRAINING DATASET MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 49. SINGAPORE AI TRAINING DATASET MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 50. SINGAPORE AI TRAINING DATASET MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 51. SOUTH KOREA AI TRAINING DATASET MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 52. SOUTH KOREA AI TRAINING DATASET MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 53. TAIWAN AI TRAINING DATASET MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 54. TAIWAN AI TRAINING DATASET MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 55. THAILAND AI TRAINING DATASET MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 56. THAILAND AI TRAINING DATASET MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 57. VIETNAM AI TRAINING DATASET MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 58. VIETNAM AI TRAINING DATASET MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 59. EUROPE, MIDDLE EAST & AFRICA AI TRAINING DATASET MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 60. EUROPE, MIDDLE EAST & AFRICA AI TRAINING DATASET MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 61. EUROPE, MIDDLE EAST & AFRICA AI TRAINING DATASET MARKET SIZE, BY COUNTRY, 2018-2030 (USD MILLION)
  • TABLE 62. DENMARK AI TRAINING DATASET MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 63. DENMARK AI TRAINING DATASET MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 64. EGYPT AI TRAINING DATASET MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 65. EGYPT AI TRAINING DATASET MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 66. FINLAND AI TRAINING DATASET MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 67. FINLAND AI TRAINING DATASET MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 68. FRANCE AI TRAINING DATASET MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 69. FRANCE AI TRAINING DATASET MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 70. GERMANY AI TRAINING DATASET MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 71. GERMANY AI TRAINING DATASET MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 72. ISRAEL AI TRAINING DATASET MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 73. ISRAEL AI TRAINING DATASET MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 74. ITALY AI TRAINING DATASET MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 75. ITALY AI TRAINING DATASET MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 76. NETHERLANDS AI TRAINING DATASET MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 77. NETHERLANDS AI TRAINING DATASET MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 78. NIGERIA AI TRAINING DATASET MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 79. NIGERIA AI TRAINING DATASET MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 80. NORWAY AI TRAINING DATASET MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 81. NORWAY AI TRAINING DATASET MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 82. POLAND AI TRAINING DATASET MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 83. POLAND AI TRAINING DATASET MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 84. QATAR AI TRAINING DATASET MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 85. QATAR AI TRAINING DATASET MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 86. RUSSIA AI TRAINING DATASET MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 87. RUSSIA AI TRAINING DATASET MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 88. SAUDI ARABIA AI TRAINING DATASET MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 89. SAUDI ARABIA AI TRAINING DATASET MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 90. SOUTH AFRICA AI TRAINING DATASET MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 91. SOUTH AFRICA AI TRAINING DATASET MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 92. SPAIN AI TRAINING DATASET MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 93. SPAIN AI TRAINING DATASET MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 94. SWEDEN AI TRAINING DATASET MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 95. SWEDEN AI TRAINING DATASET MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 96. SWITZERLAND AI TRAINING DATASET MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 97. SWITZERLAND AI TRAINING DATASET MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 98. TURKEY AI TRAINING DATASET MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 99. TURKEY AI TRAINING DATASET MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 100. UNITED ARAB EMIRATES AI TRAINING DATASET MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 101. UNITED ARAB EMIRATES AI TRAINING DATASET MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 102. UNITED KINGDOM AI TRAINING DATASET MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 103. UNITED KINGDOM AI TRAINING DATASET MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
  • TABLE 104. AI TRAINING DATASET MARKET SHARE, BY KEY PLAYER, 2023
  • TABLE 105. AI TRAINING DATASET MARKET, FPNV POSITIONING MATRIX, 2023