AIトレーニングデータセット市場：タイプ別、エンドユーザー別-2025-2030年の世界予測

AIトレーニングデータセット市場は、2023年に17億1,000万米ドルと評価され、2024年には21億2,000万米ドルに達すると予測され、CAGR 26.41％で成長し、2030年には88億3,000万米ドルに達すると予測されています。

AIトレーニングデータセット市場は、広範なAI業界の中で急速に発展しているセグメントであり、堅牢なAIモデルの学習に必要な構造化データの提供に焦点を当てています。その範囲は、AIアルゴリズムを訓練するために多様なソースから収集された画像、テキスト、音声、ビデオなど、さまざまなデータタイプを幅広くカバーしています。ヘルスケア、自動車、金融、小売などの業界でAIアプリケーションの需要が高まっているため、この市場は極めて重要です。AIモデルの性能はトレーニングに使用されるデータセットに直結するため、高品質で多様な代表的データの必要性は最も重要です。AIトレーニング用データセットは、チャットボット、自律走行車、医療診断、感情分析など、さまざまな分野で活用されています。最終用途の範囲は、業務の効率化、顧客体験の向上、高度な分析能力を求める産業にまで広がっています。

この市場に影響を与える主な成長要因には、AI技術の急激な成長、機械学習アルゴリズムの進歩、これらのモデルを効果的に訓練するための大規模データセットの必要性などがあります。新興の分野や地域におけるAIの普及が進むことで、大きなビジネスチャンスが生まれます。企業は、データ取得やアノテーション技術に投資し、多様なデータセットにアクセスするためのパートナーシップを形成することで、これらを活用することができます。しかし、データのプライバシーに関する懸念、データ利用をめぐる倫理的問題、データのキュレーションとラベリングにかかる高コストといった課題が、市場の成長を阻害する可能性があります。

こうした課題を克服するためには、合成データ生成、連携学習、自動データラベリングなどの分野におけるイノベーションが不可欠となります。データの公平性と偏りを排除するためのベストプラクティスを調査することも、競争優位性をもたらします。市場の性質は非常にダイナミックで、技術の進歩や規制状況の進化に後押しされています。こうした変化に敏感に反応し、積極的に戦略を適応させることで、大きなアドバンテージを得ることができます。AIが各分野に普及するにつれ、学習用データセットの役割はさらに重要になり、高品質でアクセスしやすく、倫理的に入手されたデータが重視されるようになります。

市場力学：急速に進化するAIトレーニングデータセット市場の主要な市場インサイトを公開

AIトレーニングデータセット市場は、需要と供給のダイナミックな相互作用によって変貌を遂げています。このような市場力学の進化を理解することで、企業は十分な情報に基づいた投資決定、戦略的意思決定、新たなビジネスチャンスの獲得を行うことができます。これらの動向を包括的に把握することで、企業は政治的、地理的、技術的、社会的、経済的な領域にわたる様々なリスクを軽減することができるとともに、消費者行動とそれが製造コストや購買動向に与える影響をより明確に理解することができます。

• 市場促進要因
  • 産業部門におけるAI統合による産業オペレーションの自動化
  • 様々なエンドユーザー産業におけるAI統合に向けた政府の支援イニシアティブ
• 市場抑制要因
  • AIトレーニングデータセットの限界
• 市場機会
  • AIトレーニングデータモデルの技術的進歩
  • AIトレーニングデータプラットフォームを強化するための有利な投資環境
• 市場の課題
  • データのラベリングとベンチマークの問題

ポーターの5つの力：AIトレーニングデータセット市場をナビゲートする戦略ツール

ポーターの5つの力フレームワークは、AIトレーニングデータセット市場の競合情勢を理解するための重要なツールです。ポーターのファイブフォース・フレームワークは、企業の競争力を評価し、戦略的機会を探るための明確な手法を提供します。このフレームワークは、企業が市場内の勢力図を評価し、新規事業の収益性を判断するのに役立ちます。これらの洞察により、企業は自社の強みを活かし、弱みに対処し、潜在的な課題を回避することができ、より強靭な市場でのポジショニングを確保することができます。

PESTLE分析：AIトレーニングデータセット市場における外部からの影響の把握

外部マクロ環境要因は、AIトレーニングデータセット市場の業績ダイナミクスを形成する上で極めて重要な役割を果たします。政治的、経済的、社会的、技術的、法的、環境的要因の分析は、これらの影響をナビゲートするために必要な情報を提供します。PESTLE要因を調査することで、企業は潜在的なリスクと機会をよりよく理解することができます。この分析により、企業は規制、消費者の嗜好、経済動向の変化を予測し、先を見越した積極的な意思決定を行う準備ができます。

市場シェア分析AIトレーニングデータセット市場における競合情勢の把握

AIトレーニングデータセット市場の詳細な市場シェア分析により、ベンダーの業績を包括的に評価することができます。企業は、収益、顧客ベース、成長率などの主要指標を比較することで、競争上のポジショニングを明らかにすることができます。この分析により、市場の集中、断片化、統合の動向が明らかになり、ベンダーは競争が激化する中で自社の地位を高める戦略的意思決定を行うために必要な知見を得ることができます。

FPNVポジショニング・マトリックスAIトレーニングデータセット市場におけるベンダーのパフォーマンス評価

FPNVポジショニングマトリックスは、AIトレーニングデータセット市場においてベンダーを評価するための重要なツールです。このマトリックスにより、ビジネス組織はベンダーのビジネス戦略と製品満足度に基づき評価することで、目標に沿った十分な情報に基づいた意思決定を行うことができます。4つの象限はベンダーを明確かつ正確に区分し、ユーザーが戦略目標に最適なパートナーやソリューションを特定するのに役立ちます。

本レポートは、主要な注目分野を網羅した包括的な市場分析を提供しています：

1.市場の浸透度：業界主要企業の広範なデータを含む、現在の市場環境の詳細なレビュー。

2.市場の開拓度：新興市場における成長機会を特定し、既存分野における拡大可能性を評価し、将来の成長に向けた戦略的ロードマップを提供します。

3.市場の多様化：最近の製品発売、未開拓の地域、業界の主要な進歩、市場を形成する戦略的投資を分析します。

4.競合の評価と情報：競合情勢を徹底的に分析し、市場シェア、事業戦略、製品ポートフォリオ、認証、規制当局の承認、特許動向、主要企業の技術進歩などを検証します。

5.製品開発およびイノベーション：将来の市場成長を促進すると期待される最先端技術、研究開発活動、製品イノベーションをハイライトしています。

また、利害関係者が十分な情報を得た上で意思決定できるよう、重要な質問にも答えています：

1.現在の市場規模と今後の成長予測は？

2.最高の投資機会を提供する製品、セグメント、地域はどこか？

3.市場を形成する主な技術動向と規制の影響とは？

4.主要ベンダーの市場シェアと競合ポジションは？

5.ベンダーの市場参入・撤退戦略の原動力となる収益源と戦略的機会は何か？

目次

第1章 序文

第2章 調査手法

第3章 エグゼクティブサマリー

第4章 市場の概要

第5章 市場洞察

• 市場力学
  • 促進要因
    • 産業分野におけるAIの統合による産業オペレーションの自動化
    • さまざまなエンドユーザー産業におけるAI統合を支援する政府の取り組み
  • 抑制要因
    • AIトレーニングデータセットの限界
  • 機会
    • AIトレーニングデータモデルの技術的進歩
    • AIトレーニングデータプラットフォームを強化するための好ましい投資情勢
  • 課題
    • データのラベル付けとベンチマークに関する問題
• 市場セグメンテーション分析
  • タイプ：さまざまな業界でのテキスト分類と感情分析のためのテキストベースのAIトレーニングデータセットの採用
  • エンドユーザー：世界中の情報技術ハブの拡大により、高度なAIトレーニングデータセットの導入が必要
• ポーターのファイブフォース分析
• PESTEL分析
  • 政治的
  • 経済
  • 社交
  • 技術的
  • 法律上
  • 環境

第6章 AIトレーニングデータセット市場：タイプ別

• オーディオ
• 画像/動画
• 文章

第7章 AIトレーニングデータセット市場：エンドユーザー別

• 自動車
• 銀行、金融サービス、保険（BFSI）
• 政府
• ヘルスケア
• 情報技術
• 小売・eコマース

第8章 南北アメリカのAIトレーニングデータセット市場

• アルゼンチン
• ブラジル
• カナダ
• メキシコ
• 米国

第9章 アジア太平洋地域のAIトレーニングデータセット市場

• オーストラリア
• 中国
• インド
• インドネシア
• 日本
• マレーシア
• フィリピン
• シンガポール
• 韓国
• 台湾
• タイ
• ベトナム

第10章 欧州・中東・アフリカのAIトレーニングデータセット市場

• デンマーク
• エジプト
• フィンランド
• フランス
• ドイツ
• イスラエル
• イタリア
• オランダ
• ナイジェリア
• ノルウェー
• ポーランド
• カタール
• ロシア
• サウジアラビア
• 南アフリカ
• スペイン
• スウェーデン
• スイス
• トルコ
• アラブ首長国連邦
• 英国

第11章 競合情勢

• 市場シェア分析2023
• FPNVポジショニングマトリックス, 2023
• 競合シナリオ分析
  • IBMとSAP SE、強化されたAIと業界固有のクラウドソリューションで前進
  • ファーウェイ、GITEX GLOBALで大規模モデル時代に向けた新しいAIストレージ製品を発表2023
  • Metaの新しいAIチャットボットは、FacebookとInstagramの公開投稿でトレーニングされています
  • Railtown AIが知識ベースのAIアシスタントをリリースし、AIに関する暫定特許を申請
  • IBMは、3年間で200万人の人工知能のトレーニングを実施し、特に過小評価されているコミュニティに重点を置くことを約束
  • Nokiaは、AI/ML開発を促進するためにGoogle Cloud上で実行されるAVA Data Suiteをリリースしました。
  • CGIはAI機能の拡張に10億米ドルを投資し、クライアントが責任あるROI主導の戦略を設計および実行できるよう支援します。
  • DatabricksがMosaicMLの買収を完了
  • RWS、自然言語処理のためのAIトレーニングデータセットを発表
  • Appen、信頼性の高い生成AIアプリケーションを構築するための3つの新製品をリリース
  • BioNTech、AIを活用した医薬品の発見、設計、開発分野での地位強化を目指しInstaDeepを買収
  • アクセンチュアとGoogle Cloudがパートナーシップを拡大し、テクノロジー、データ、AIから価値を引き出すことを加速

企業一覧

• 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

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

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 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