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人工智慧訓練資料集集市場：按類型、最終用戶分類 - 2025-2030 年全球預測

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個工作天內

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2023年人工智慧訓練資料集市場價值為17.1億美元，預計到2024年將達到21.2億美元，複合年成長率為26.41%，預計到2030年將達到88.3億美元。

人工智慧訓練資料集集市場是更廣泛的人工智慧產業中快速發展的部分，專注於提供訓練強大的人工智慧模型所需的結構化資料。其範圍廣泛涵蓋各種資料類型，包括從不同來源收集的圖像、文字、音頻和影片，用於訓練人工智慧演算法。由於醫療保健、汽車、金融和零售等行業對人工智慧應用的需求不斷成長，該市場極為重要。 AI 模型的效能與用於訓練的資料集集直接相關，因此對高品質、多樣化和代表性資料的需求至關重要。 AI 訓練資料集集用於多種領域，包括聊天機器人、自動駕駛汽車、醫療診斷和情緒分析。最終用途應用正在擴展到包括需要業務效率、改善的客戶體驗和先進分析能力的行業。

主要市場統計
基準年[2023] 17.1億美元
預測年份 [2024] 21.2億美元
預測年份 [2030] 88.3億美元
複合年成長率（%） 26.41%

影響該市場的主要成長要素包括人工智慧技術的快速成長、機器學習演算法的進步以及對大規模資料集集有效訓練這些模型的需求。人工智慧在新興領域和地區的不斷滲透將創造巨大的商機。公司可以透過投資資料收集和註釋技術並建立夥伴關係來存取不同的資料集集來利用這些優勢。然而，資料隱私問題、資料使用的道德問題以及資料管理和標籤的高成本等挑戰可能會阻礙市場成長。

合成資料生成、聯合學習和自動資料標記等領域的創新對於克服這些挑戰至關重要。研究資料公平性和消除偏見的最佳實踐也可以提供競爭優勢。在技​​術進步和不斷變化的監管環境的推動下，市場本質上是高度動態的。回應這些變化並主動調整您的策略可以為您帶來顯著的優勢。隨著人工智慧滲透到各個領域，訓練資料集集的角色將變得更加重要，重點是高品質、易於存取且來源合乎道德的資料。

市場動態：揭示快速發展的人工智慧訓練資料集市場的關鍵市場洞察

供需的動態交互作用正在改變人工智慧訓練資料集集市場。了解這些不斷變化的市場動態可以幫助企業做出明智的投資決策、策略決策並抓住新的商機。全面了解這些趨勢可以幫助企業降低政治、地理、技術、社會和經濟領域的風險，同時消費行為及其對製造成本的影響以及對採購趨勢的影響。

  • 市場促進因素
    • 透過工業領域的人工智慧整合實現工業營運自動化
    • 政府支持的人工智慧在各個最終用戶產業整合的舉措
  • 市場限制因素
    • AI訓練資料集的局限性
  • 市場機會
    • AI訓練資料模型的技術進步
    • 有利的投資環境為人工智慧訓練資料平台提供動力
  • 市場挑戰
    • 資料標籤和基準測試問題

波特五力：駕馭人工智慧訓練資料集市場的策略工具

波特五力框架是了解人工智慧訓練資料集市場競爭格局的關鍵工具。波特的五力框架為評估公司的競爭地位和探索策略機會提供了清晰的方法。該框架可幫助公司評估市場動態並確定新業務的盈利。這些見解使公司能夠利用自己的優勢，解決弱點並避免潛在的挑戰，從而確保更強大的市場地位。

PESTLE分析：了解人工智慧訓練資料集集市場的外部影響

外部宏觀環境因素在塑造人工智慧訓練資料集市場的績效動態方面發揮著至關重要的作用。對政治、經濟、社會、技術、法律和環境因素的分析提供了應對這些影響所需的資訊。透過調查 PESTLE 因素，公司可以更了解潛在的風險和機會。這種分析可以幫助公司預測法規、消費者偏好和經濟趨勢的變化，並為他們做出積極主動的決策做好準備。

市場佔有率分析 了解AI訓練資料集集市場的競爭格局

對人工智慧訓練資料集集市場的詳細市場佔有率分析可以對供應商績效進行全面評估。公司可以透過比較收益、客戶群和成長率等關鍵指標來發現自己的競爭定位。該分析揭示了市場集中、分散和整合的趨勢，為供應商提供了製定策略決策所需的洞察力，使他們能夠在日益激烈的競爭中佔有一席之地。

FPNV 定位矩陣人工智慧訓練資料集集市場供應商的績效評估

FPNV 定位矩陣是評估 AI 訓練資料集集市場供應商的關鍵工具。此矩陣允許業務組織根據供應商的商務策略和產品滿意度評估供應商，從而做出符合其目標的明智決策。四個象限清楚且準確地分類了供應商，幫助使用者辨識最能滿足其策略目標的合作夥伴和解決方案。

本報告提供了涵蓋關鍵重點領域的全面市場分析：

1. 市場滲透率：對當前市場環境的詳細回顧，包括行業主要企業的大量資料。

2. 市場開拓：辨識新興市場的成長機會，評估現有領域的擴張潛力，並提供未來成長的策略藍圖。

3. 市場多元化：分析近期產品發布、開拓地區、關鍵產業進展、塑造市場的策略投資。

4. 競爭評估與情報：徹底分析競爭格局，檢驗市場佔有率、業務策略、產品系列、認證、監理核准、專利趨勢、主要企業的技術進步等。

5. 產品開發與創新：重點在於有望推動未來市場成長的最尖端科技、研發活動和產品創新。

我們也回答重要問題，以幫助相關人員做出明智的決策：

1.目前的市場規模和未來的成長預測是多少？

2. 哪些產品、區隔市場和地區提供最佳投資機會？

3.塑造市場的主要技術趨勢和監管影響是什麼？

4.主要廠商的市場佔有率和競爭地位如何？

5. 推動供應商市場進入和退出策略的收益來源和策略機會是什麼？

目錄

第1章 前言

第2章調查方法

第3章執行摘要

第4章市場概況

第5章市場洞察

  • 市場動態
    • 促進因素
      • 透過人工智慧在工業領域的整合實現工業營運自動化
      • 政府支持人工智慧在各終端用戶產業整合的舉措
    • 抑制因素
      • AI訓練資料集的局限性
    • 機會
      • AI訓練資料模型的技術進步
      • 有利的投資環境為人工智慧培訓資料平台提供動力
    • 任務
      • 資料標籤和基準測試問題
  • 市場區隔分析
    • 類型：採用以文本為基礎的AI訓練資料集集進行各行業的文本分類與情感分析
    • 最終用戶：全球資訊科技中心的擴張需要採用先進的人工智慧訓練資料集
  • 波特五力分析
  • PESTEL分析
    • 政治的
    • 經濟
    • 社群
    • 技術的
    • 合法地
    • 環境

第 6 章 AI 訓練資料集市場：按類型

  • 音訊的
  • 圖片/影片
  • 句子

第7章 人工智慧訓練資料集市場：按最終用戶分類

  • 車
  • 銀行、金融服務和保險 (BFSI)
  • 政府
  • 衛生保健
  • 資訊科技
  • 零售/電子商務

第 8 章美洲人工智慧訓練資料集市場

  • 阿根廷
  • 巴西
  • 加拿大
  • 墨西哥
  • 美國

第9章亞太人工智慧訓練資料集市場

  • 澳洲
  • 中國
  • 印度
  • 印尼
  • 日本
  • 馬來西亞
  • 菲律賓
  • 新加坡
  • 韓國
  • 台灣
  • 泰國
  • 越南

第10章 歐洲/中東/非洲AI訓練資料集市場

  • 丹麥
  • 埃及
  • 芬蘭
  • 法國
  • 德國
  • 以色列
  • 義大利
  • 荷蘭
  • 奈及利亞
  • 挪威
  • 波蘭
  • 卡達
  • 俄羅斯
  • 沙烏地阿拉伯
  • 南非
  • 西班牙
  • 瑞典
  • 瑞士
  • 土耳其
  • 阿拉伯聯合大公國
  • 英國

第11章競爭格局

  • 2023 年市場佔有率分析
  • FPNV 定位矩陣，2023
  • 競爭情境分析
    • IBM 和 SAP SE 憑藉著增強型人工智慧和特定產業雲端解決方案向前邁進
    • 華為在GITEX GLOBAL 2023發布面向大型模型時代的AI儲存新品
    • Meta 的新人工智慧聊天機器人接受了來自 Facebook 和 Instagram 的公共貼文的訓練
    • Railtown AI 發布基於知識的人工智慧助理並申請人工智慧臨時專利
    • IBM 承諾在三年內培訓 200 萬人接受人工智慧培訓，特別關注代表性不足的社區
    • 諾基亞發布了在 Google Cloud 上運行的 AVA Data Suite，以加速 AI/ML 開發。
    • CGI 將投資 10 億美元擴展其人工智慧能力，幫助客戶設計和執行負責任的、投資回報率主導的策略。
    • Databricks 完成對 MosaicML 的收購
    • RWS 推出用於自然語言處理的人工智慧訓練資料集
    • 澳鵬發布三款新產品，用於建構可靠的生成式人工智慧應用
    • BioNTech 收購 InstaDeep，以加強在人工智慧驅動的藥物發現、設計和開發領域的地位
    • Accenture與Google雲端擴大夥伴關係，加速釋放技術、資料和人工智慧的價值

公司名單

  • 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