自動機械学習（AutoML）の世界市場レポート 2025年

自動機械学習（AutoML）市場規模は、今後数年で飛躍的な成長が見込まれます。2029年にはCAGR46.8％で109億3,000万米ドルに成長します。予測期間の成長は、業界を超えたAI統合、IoTとビッグデータの拡大、エッジコンピューティングの台頭、クラウドとオンプレミスのハイブリッドソリューション、規制コンプライアンス要件に起因すると考えられます。予測期間の主な動向には、自動フィーチャーエンジニアリング、連携学習の進歩、説明可能なAIとモデルの解釈可能性、非構造化データのAutoML、自律システムのAutoMLなどがあります。

高度な不正検知ソリューションに対する需要の高まりが、今後の自動機械学習（AutoML）市場の成長を牽引すると予測されます。不正検知とは、システムや組織内での不正行為や行動を特定し、防止するプロセスを指します。自動機械学習（AutoML）は、大量のデータを処理・分析し、パターンを認識し、不正行為を示唆する異常を特定する能力を活用することで、不正検知を支援することができます。例えば、2024年2月、ドイツを拠点に保険および資産運用サービスを提供するAllianz Insurance plcは、2023年に9,520万米ドル（7,740万英ポンド）の保険金詐欺が検出されたと報告しており、2022年の8,696万米ドル（7,070万英ポンド）から増加しています。このように、高度な不正検知ソリューションに対する需要の高まりが、自動機械学習（AutoML）市場の成長を後押ししています。

IoTデバイスの普及は、自動機械学習（AutoML）市場の成長に貢献すると見られています。モノのインターネット（IoT）デバイスは、センサー、ソフトウェア、その他の技術を組み込み、インターネットを介して他のデバイスやシステムとデータを交換します。IoTデバイスの急激な増加により、価値ある洞察に活用できる膨大な量のデータが生成されます。AutoMLは、IoT機器から生成されるデータから意味のある情報を抽出するための機械学習モデルの開発を容易にします。チェコ共和国を拠点とするオンライン・メディア企業TechJury Officialによると、2022年に設置されたIoTデバイス、センサー、アクチュエーターは約426億2,000万台で、2021年の358億2,000万台、2020年の307億3,000万台から大幅に増加しました。その結果、IoTデバイスの増加が自動機械学習（AutoML）市場の成長の起爆剤となっています。

目次

第1章 エグゼクティブサマリー

第2章 市場の特徴

第3章 市場動向と戦略

第4章 市場：金利、インフレ、地政学、コロナ禍、回復が市場に与える影響を含むマクロ経済シナリオ

第5章 世界の成長分析と戦略分析フレームワーク

• 世界自動機械学習（AutoML） PESTEL分析（政治、社会、技術、環境、法的要因、促進要因、抑制要因）
• 最終用途産業の分析
• 世界の自動機械学習（AutoML）市場：成長率分析
• 世界の自動機械学習（AutoML）市場の実績：規模と成長, 2019-2024
• 世界の自動機械学習（AutoML）市場の予測：規模と成長, 2024-2029, 2034F
• 世界自動機械学習（AutoML）総アドレス可能市場（TAM）

第6章 市場セグメンテーション

• 世界の自動機械学習（AutoML）市場：提供別、実績と予測, 2019-2024, 2024-2029F, 2034F
• ソリューション
• サービス
• 世界の自動機械学習（AutoML）市場：展開別、実績と予測, 2019-2024, 2024-2029F, 2034F
• クラウド
• オンプレミス
• 世界の自動機械学習（AutoML）市場エンタープライズ、実績と予測, 2019-2024, 2024-2029F, 2034F
• 中小企業
• 大企業
• 世界の自動機械学習（AutoML）市場：用途別、実績と予測, 2019-2024, 2024-2029F, 2034F
• データ処理
• 機能エンジニアリング
• モデルの選択
• ハイパーパラメータの最適化とチューニング
• モデルの組み立て
• その他の用途
• 世界の自動機械学習（AutoML）市場：エンドユーザー別、実績と予測, 2019-2024, 2024-2029F, 2034F
• 銀行、金融サービス、保険（BFSI）
• 小売業とeコマース
• ヘルスケア
• 製造業
• その他のエンドユーザー
• 世界の自動機械学習（AutoML）市場、ソリューションのサブセグメンテーション、タイプ別、実績と予測, 2019-2024, 2024-2029F, 2034F
• クラウドベースのソリューション
• オンプレミスソリューション
• 統合開発環境（IDE）
• 世界の自動機械学習（AutoML）市場、サービスの種類別の細分化、実績と予測, 2019-2024, 2024-2029F, 2034F
• コンサルティングサービス
• 実装サービス
• トレーニングおよびサポートサービス

第7章 地域別・国別分析

• 世界の自動機械学習（AutoML）市場：地域別、実績と予測, 2019-2024, 2024-2029F, 2034F
• 世界の自動機械学習（AutoML）市場：国別、実績と予測, 2019-2024, 2024-2029F, 2034F

第8章 アジア太平洋市場

第9章 中国市場

第10章 インド市場

第11章 日本市場

第12章 オーストラリア市場

第13章 インドネシア市場

第14章 韓国市場

第15章 西欧市場

第16章 英国市場

第17章 ドイツ市場

第18章 フランス市場

第19章 イタリア市場

第20章 スペイン市場

第21章 東欧市場

第22章 ロシア市場

第23章 北米市場

第24章 米国市場

第25章 カナダ市場

第26章 南米市場

第27章 ブラジル市場

第28章 中東市場

第29章 アフリカ市場

第30章 競合情勢と企業プロファイル

• 自動機械学習（AutoML）市場：競合情勢
• 自動機械学習（AutoML）市場：企業プロファイル
  • Google LLC Overview, Products and Services, Strategy and Financial Analysis
  • Microsoft Corporation Overview, Products and Services, Strategy and Financial Analysis
  • Amazon Web Services Inc. Overview, Products and Services, Strategy and Financial Analysis
  • International Business Machines Corporation Overview, Products and Services, Strategy and Financial Analysis
  • Oracle Corporation Overview, Products and Services, Strategy and Financial Analysis

第31章 その他の大手企業と革新的企業

• Salesforce Inc.
• Teradata Corporation
• Alteryx
• Altair Engineering Inc.
• EdgeVerve Systems Limited
• TIBCO Software Inc.
• DataRobot Inc.
• Dataiku
• BigPanda.
• H2O.ai Inc.
• KNIME
• Cognitivescale
• Anyscale Inc.
• RapidMiner
• Squark AI Inc.

第32章 世界の市場競合ベンチマーキングとダッシュボード

第33章 主要な合併と買収

第34章 最近の市場動向

第35章 市場の潜在力が高い国、セグメント、戦略

• 自動機械学習（AutoML）市場2029：新たな機会を提供する国
• 自動機械学習（AutoML）市場2029：新たな機会を提供するセグメント
• 自動機械学習（AutoML）市場2029：成長戦略
  • 市場動向に基づく戦略
  • 競合の戦略

第36章 付録

Automated machine learning (AutoML) is the application of machine learning to practical problems, automating the selection, composition, and parameterization of machine learning models. AutoML streamlines the machine learning process, making it more user-friendly and often yielding faster and more accurate outputs compared to manually coded algorithms.

The primary offerings in automated machine learning (AutoML) include solutions and services. Solutions involve the implementation of software tools to address specific organizational issues. Automated machine learning solutions enable business users to easily adopt machine learning, allowing data scientists to focus on more complex challenges. These solutions can be deployed in various settings, such as cloud and on-premises, catering to both small and medium enterprises as well as large enterprises. They find applications in data processing, feature engineering, model selection, hyperparameter optimization and tuning, model assembling, and other areas. AutoML is utilized by various end-users, including industries such as banking, financial services, and insurance (BFSI), retail and e-commerce, healthcare, manufacturing, among others.

The automated machine learning (AutoML) market research report is one of a series of new reports from The Business Research Company that provides automated machine learning (AutoML) market statistics, including automated machine learning (AutoML) industry global market size, regional shares, competitors with an automated machine learning (AutoML) market share, detailed automated machine learning (AutoML) market segments, market trends and opportunities, and any further data you may need to thrive in the automated machine learning (AutoML) industry. This automated machine learning (AutoML) market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenarios of the industry.

The automated machine learning (AutoML) market size has grown exponentially in recent years. It will grow from $1.64 billion in 2024 to $2.35 billion in 2025 at a compound annual growth rate (CAGR) of 43.6%. The growth in the historic period can be attributed to complexity of machine learning, scarcity of data science talent, demand for speedy solutions, advancements in ai and computing power, cost efficiency

The automated machine learning (AutoML) market size is expected to see exponential growth in the next few years. It will grow to $10.93 billion in 2029 at a compound annual growth rate (CAGR) of 46.8%. The growth in the forecast period can be attributed to ai integration across industries, expansion of IoT and big data, rise of edge computing, hybrid cloud and on-premises solutions, regulatory compliance requirements. Major trends in the forecast period include automated feature engineering, federated learning advancements, explainable ai and model interpretability, AutoML for unstructured data, AutoML for autonomous systems.

The increasing demand for advanced fraud detection solutions is anticipated to drive the growth of the automated machine learning (AutoML) market in the future. Fraud detection refers to the process of identifying and preventing fraudulent activities or behaviors within a system or organization. Automated machine learning (AutoML) can assist in fraud detection by utilizing its ability to process and analyze large amounts of data, recognize patterns, and identify anomalies that may suggest fraudulent activities. For example, in February 2024, Allianz Insurance plc, a Germany-based company providing insurance and asset management services, reported that $95.2 million (£77.4 million) in claims fraud was detected in 2023, an increase from $86.96 million (£70.7 million) in 2022. Thus, the rising demand for advanced fraud detection solutions is propelling the growth of the automated machine learning (AutoML) market.

The proliferation of IoT devices is poised to contribute to the growth of the automated machine learning (AutoML) market. Internet of Things (IoT) devices, embedded with sensors, software, and other technologies, exchange data with other devices or systems over the internet. The exponential growth in IoT devices results in a vast amount of data that can be utilized for valuable insights. AutoML facilitates the development of machine learning models to extract meaningful information from the data generated by IoT devices. According to TechJury Official, a Czech Republic-based online media company, there were approximately 42.62 billion installed IoT devices, sensors, and actuators in 2022, marking a significant increase from 35.82 billion in 2021 and 30.73 billion in 2020. Consequently, the growing number of IoT devices is a catalyst for the growth of the automated machine learning (AutoML) market.

The automated machine learning (AutoML) market is witnessing a significant trend in technological innovations, with major companies adopting new advancements to maintain their market positions. For example, in April 2023, AND Solutions Pte Ltd., a fintech company based in Singapore, launched the NIKO AutoML platform-a cutting-edge machine-learning tool designed to simplify and accelerate the creation of prediction models. Offering various tools and functionalities, NIKO AutoML enables users to swiftly create and deploy high-quality machine learning models without the need for coding or data science expertise. The user-friendly interface guides users through each stage of the process, delivering optimal results in a fraction of the time required by traditional methods. NIKO AutoML offers key benefits, including fast and accurate model creation, streamlined workflows, increased productivity, and cost-effectiveness.

Major players in the AutoML market are dedicated to developing innovative solutions, such as an AutoML platform for Arm compilers. AutoML for Arm compiler involves integrating AutoML capabilities with the Arm compiler, which generates machine code for Arm processors. In March 2023, TDK Corporation, a Tokyo-based electronic solutions manufacturer, introduced the 'Qeexo AutoML' platform tailored for lightweight Cortex-M0 to -M4 class processors. This platform supports various machine learning algorithms, excelling in ultra-low latency and power consumption. Qeexo AutoML empowers users to rapidly create and implement machine learning solutions using sensor data, making it ideal for deployment in resource-constrained environments such as industrial, IoT, wearables, automotive, and mobile.

In May 2023, Infineon Technologies AG, a Germany-based semiconductor manufacturer, acquired Imagimob AB for an undisclosed sum. This acquisition enables Infineon Technologies to bolster its position in the expanding market for embedded AI solutions and tiny machine learning, improving its ability to provide advanced functionalities and energy-efficient control in IoT applications. Imagimob AB is a Sweden-based company focused on edge AI and tinyML, aimed at facilitating the intelligent products of the future.

Major companies operating in the automated machine learning (AutoML) market include Google LLC, Microsoft Corporation, Amazon Web Services Inc., International Business Machines Corporation, Oracle Corporation, Salesforce Inc., Teradata Corporation, Alteryx, Altair Engineering Inc., EdgeVerve Systems Limited, TIBCO Software Inc., DataRobot Inc., Dataiku, BigPanda., H2O.ai Inc., KNIME, Cognitivescale, Anyscale Inc., RapidMiner, Squark AI Inc., Auger.AI, DotData Inc., BigML Inc., Valohai, DarwinAI, Aible Inc., SigOpt, Zerion, Xpanse AI, Neptune Labs

North America was the largest region in the automated machine learning (AutoML) market in 2024. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the automated machine learning (automl) market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa

The countries covered in the automated machine learning (automl) market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, USA, Italy, Spain, Canada.

The automated machine learning (AutoML) market includes revenues earned by entities by providing data visualization, deployment of technology, monitoring and problem cracking, fraud detection, neural architecture search (NAS), and workflow optimization. The market value includes the value of related goods sold by the service provider or included within the service offering. Only goods and services traded between entities or sold to end consumers are included.

The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD, unless otherwise specified).

The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.

Automated Machine Learning (AutoML) Global Market Report 2025 from The Business Research Company provides strategists, marketers and senior management with the critical information they need to assess the market.

This report focuses on automated machine learning (automl) market which is experiencing strong growth. The report gives a guide to the trends which will be shaping the market over the next ten years and beyond.

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Where is the largest and fastest growing market for automated machine learning (automl) ? How does the market relate to the overall economy, demography and other similar markets? What forces will shape the market going forward? The automated machine learning (automl) market global report from the Business Research Company answers all these questions and many more.

The report covers market characteristics, size and growth, segmentation, regional and country breakdowns, competitive landscape, market shares, trends and strategies for this market. It traces the market's historic and forecast market growth by geography.

• The market characteristics section of the report defines and explains the market.
• The market size section gives the market size ($b) covering both the historic growth of the market, and forecasting its development.
• The forecasts are made after considering the major factors currently impacting the market. These include:

The forecasts are made after considering the major factors currently impacting the market. These include the Russia-Ukraine war, rising inflation, higher interest rates, and the legacy of the COVID-19 pandemic.

• Market segmentations break down the market into sub markets.
• The regional and country breakdowns section gives an analysis of the market in each geography and the size of the market by geography and compares their historic and forecast growth. It covers the growth trajectory of COVID-19 for all regions, key developed countries and major emerging markets.
• The competitive landscape chapter gives a description of the competitive nature of the market, market shares, and a description of the leading companies. Key financial deals which have shaped the market in recent years are identified.
• The trends and strategies section analyses the shape of the market as it emerges from the crisis and suggests how companies can grow as the market recovers.

Scope

• Markets Covered:1) By Offering: Solutions; Services
• 2) By Deployment: Cloud; On-Premises
• 3) By Enterprise: Small And Medium Enterprise; Large Enterprise
• 4) By Application: Data Processing; Feature Engineering; Model Selection; Hyperparameter Optimization And Tuning; Model Assembling; Other Applications
• 5) By End User: Banking, Financial Services And Insurance (BFSI); Retail And E-Commerce; Healthcare; Manufacturing; Other End Users
• Subsegments:
• 1) By Solutions: Cloud-Based Solutions; On-Premises Solutions; Integrated Development Environments (IDEs)
• 2) By Services: Consulting Services; Implementation Services; Training And Support Services
• Companies Mentioned: Google LLC; Microsoft Corporation; Amazon Web Services Inc.; International Business Machines Corporation; Oracle Corporation
• Countries: Australia; Brazil; China; France; Germany; India; Indonesia; Japan; Russia; South Korea; UK; USA; Canada; Italy; Spain
• Regions: Asia-Pacific; Western Europe; Eastern Europe; North America; South America; Middle East; Africa
• Time series: Five years historic and ten years forecast.
• Data: Ratios of market size and growth to related markets, GDP proportions, expenditure per capita,
• Data segmentations: country and regional historic and forecast data, market share of competitors, market segments.
• Sourcing and Referencing: Data and analysis throughout the report is sourced using end notes.
• Delivery format: PDF, Word and Excel Data Dashboard.

Table of Contents

1. Executive Summary

2. Automated Machine Learning (AutoML) Market Characteristics

3. Automated Machine Learning (AutoML) Market Trends And Strategies

4. Automated Machine Learning (AutoML) Market - Macro Economic Scenario including the impact of Interest Rates, Inflation, Geopolitics and Covid And Recovery on the Market

5. Global Automated Machine Learning (AutoML) Growth Analysis And Strategic Analysis Framework

• 5.1. Global Automated Machine Learning (AutoML) PESTEL Analysis (Political, Social, Technological, Environmental and Legal Factors, Drivers and Restraints)
• 5.2. Analysis Of End Use Industries
• 5.3. Global Automated Machine Learning (AutoML) Market Growth Rate Analysis
• 5.4. Global Automated Machine Learning (AutoML) Historic Market Size and Growth, 2019 - 2024, Value ($ Billion)
• 5.5. Global Automated Machine Learning (AutoML) Forecast Market Size and Growth, 2024 - 2029, 2034F, Value ($ Billion)
• 5.6. Global Automated Machine Learning (AutoML) Total Addressable Market (TAM)

6. Automated Machine Learning (AutoML) Market Segmentation

• 6.1. Global Automated Machine Learning (AutoML) Market, Segmentation By Offering, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
• Solutions
• Services
• 6.2. Global Automated Machine Learning (AutoML) Market, Segmentation By Deployment, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
• Cloud
• On-Premises
• 6.3. Global Automated Machine Learning (AutoML) Market, Segmentation By Enterprise, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
• Small And Medium Enterprise
• Large Enterprise
• 6.4. Global Automated Machine Learning (AutoML) Market, Segmentation By Application, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
• Data Processing
• Feature Engineering
• Model Selection
• Hyperparameter Optimization And Tuning
• Model Assembling
• Other Applications
• 6.5. Global Automated Machine Learning (AutoML) Market, Segmentation By End User, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
• Banking, Financial Services And Insurance (BFSI)
• Retail And E-Commerce
• Healthcare
• Manufacturing
• Other End Users
• 6.6. Global Automated Machine Learning (AutoML) Market, Sub-Segmentation Of Solutions, By Type, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
• Cloud-Based Solutions
• On-Premises Solutions
• Integrated Development Environments (IDEs)
• 6.7. Global Automated Machine Learning (AutoML) Market, Sub-Segmentation Of Services, By Type, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
• Consulting Services
• Implementation Services
• Training And Support Services

7. Automated Machine Learning (AutoML) Market Regional And Country Analysis

• 7.1. Global Automated Machine Learning (AutoML) Market, Split By Region, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
• 7.2. Global Automated Machine Learning (AutoML) Market, Split By Country, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

8. Asia-Pacific Automated Machine Learning (AutoML) Market

• 8.1. Asia-Pacific Automated Machine Learning (AutoML) Market Overview
• Region Information, Market Information, Background Information, Government Initiatives, Regulations, Regulatory Bodies, Major Associations, Taxes Levied, Corporate Tax Structure, Investments, Major Companies
• 8.2. Asia-Pacific Automated Machine Learning (AutoML) Market, Segmentation By Offering, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
• 8.3. Asia-Pacific Automated Machine Learning (AutoML) Market, Segmentation By Deployment, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
• 8.4. Asia-Pacific Automated Machine Learning (AutoML) Market, Segmentation By Enterprise, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

9. China Automated Machine Learning (AutoML) Market

• 9.1. China Automated Machine Learning (AutoML) Market Overview
• 9.2. China Automated Machine Learning (AutoML) Market, Segmentation By Offering, Historic and Forecast, 2019-2024, 2024-2029F, 2034F,$ Billion
• 9.3. China Automated Machine Learning (AutoML) Market, Segmentation By Deployment, Historic and Forecast, 2019-2024, 2024-2029F, 2034F,$ Billion
• 9.4. China Automated Machine Learning (AutoML) Market, Segmentation By Enterprise, Historic and Forecast, 2019-2024, 2024-2029F, 2034F,$ Billion

10. India Automated Machine Learning (AutoML) Market

• 10.1. India Automated Machine Learning (AutoML) Market, Segmentation By Offering, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
• 10.2. India Automated Machine Learning (AutoML) Market, Segmentation By Deployment, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
• 10.3. India Automated Machine Learning (AutoML) Market, Segmentation By Enterprise, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

11. Japan Automated Machine Learning (AutoML) Market

• 11.1. Japan Automated Machine Learning (AutoML) Market Overview
• 11.2. Japan Automated Machine Learning (AutoML) Market, Segmentation By Offering, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
• 11.3. Japan Automated Machine Learning (AutoML) Market, Segmentation By Deployment, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
• 11.4. Japan Automated Machine Learning (AutoML) Market, Segmentation By Enterprise, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

12. Australia Automated Machine Learning (AutoML) Market

• 12.1. Australia Automated Machine Learning (AutoML) Market, Segmentation By Offering, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
• 12.2. Australia Automated Machine Learning (AutoML) Market, Segmentation By Deployment, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
• 12.3. Australia Automated Machine Learning (AutoML) Market, Segmentation By Enterprise, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

13. Indonesia Automated Machine Learning (AutoML) Market

• 13.1. Indonesia Automated Machine Learning (AutoML) Market, Segmentation By Offering, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
• 13.2. Indonesia Automated Machine Learning (AutoML) Market, Segmentation By Deployment, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
• 13.3. Indonesia Automated Machine Learning (AutoML) Market, Segmentation By Enterprise, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

14. South Korea Automated Machine Learning (AutoML) Market

• 14.1. South Korea Automated Machine Learning (AutoML) Market Overview
• 14.2. South Korea Automated Machine Learning (AutoML) Market, Segmentation By Offering, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
• 14.3. South Korea Automated Machine Learning (AutoML) Market, Segmentation By Deployment, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
• 14.4. South Korea Automated Machine Learning (AutoML) Market, Segmentation By Enterprise, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

15. Western Europe Automated Machine Learning (AutoML) Market

• 15.1. Western Europe Automated Machine Learning (AutoML) Market Overview
• 15.2. Western Europe Automated Machine Learning (AutoML) Market, Segmentation By Offering, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
• 15.3. Western Europe Automated Machine Learning (AutoML) Market, Segmentation By Deployment, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
• 15.4. Western Europe Automated Machine Learning (AutoML) Market, Segmentation By Enterprise, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

16. UK Automated Machine Learning (AutoML) Market

• 16.1. UK Automated Machine Learning (AutoML) Market, Segmentation By Offering, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
• 16.2. UK Automated Machine Learning (AutoML) Market, Segmentation By Deployment, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
• 16.3. UK Automated Machine Learning (AutoML) Market, Segmentation By Enterprise, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

17. Germany Automated Machine Learning (AutoML) Market

• 17.1. Germany Automated Machine Learning (AutoML) Market, Segmentation By Offering, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
• 17.2. Germany Automated Machine Learning (AutoML) Market, Segmentation By Deployment, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
• 17.3. Germany Automated Machine Learning (AutoML) Market, Segmentation By Enterprise, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

18. France Automated Machine Learning (AutoML) Market

• 18.1. France Automated Machine Learning (AutoML) Market, Segmentation By Offering, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
• 18.2. France Automated Machine Learning (AutoML) Market, Segmentation By Deployment, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
• 18.3. France Automated Machine Learning (AutoML) Market, Segmentation By Enterprise, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

19. Italy Automated Machine Learning (AutoML) Market

• 19.1. Italy Automated Machine Learning (AutoML) Market, Segmentation By Offering, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
• 19.2. Italy Automated Machine Learning (AutoML) Market, Segmentation By Deployment, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
• 19.3. Italy Automated Machine Learning (AutoML) Market, Segmentation By Enterprise, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

20. Spain Automated Machine Learning (AutoML) Market

• 20.1. Spain Automated Machine Learning (AutoML) Market, Segmentation By Offering, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
• 20.2. Spain Automated Machine Learning (AutoML) Market, Segmentation By Deployment, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
• 20.3. Spain Automated Machine Learning (AutoML) Market, Segmentation By Enterprise, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

21. Eastern Europe Automated Machine Learning (AutoML) Market

• 21.1. Eastern Europe Automated Machine Learning (AutoML) Market Overview
• 21.2. Eastern Europe Automated Machine Learning (AutoML) Market, Segmentation By Offering, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
• 21.3. Eastern Europe Automated Machine Learning (AutoML) Market, Segmentation By Deployment, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
• 21.4. Eastern Europe Automated Machine Learning (AutoML) Market, Segmentation By Enterprise, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

22. Russia Automated Machine Learning (AutoML) Market

• 22.1. Russia Automated Machine Learning (AutoML) Market, Segmentation By Offering, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
• 22.2. Russia Automated Machine Learning (AutoML) Market, Segmentation By Deployment, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
• 22.3. Russia Automated Machine Learning (AutoML) Market, Segmentation By Enterprise, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

23. North America Automated Machine Learning (AutoML) Market

• 23.1. North America Automated Machine Learning (AutoML) Market Overview
• 23.2. North America Automated Machine Learning (AutoML) Market, Segmentation By Offering, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
• 23.3. North America Automated Machine Learning (AutoML) Market, Segmentation By Deployment, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
• 23.4. North America Automated Machine Learning (AutoML) Market, Segmentation By Enterprise, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

24. USA Automated Machine Learning (AutoML) Market

• 24.1. USA Automated Machine Learning (AutoML) Market Overview
• 24.2. USA Automated Machine Learning (AutoML) Market, Segmentation By Offering, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
• 24.3. USA Automated Machine Learning (AutoML) Market, Segmentation By Deployment, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
• 24.4. USA Automated Machine Learning (AutoML) Market, Segmentation By Enterprise, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

25. Canada Automated Machine Learning (AutoML) Market

• 25.1. Canada Automated Machine Learning (AutoML) Market Overview
• 25.2. Canada Automated Machine Learning (AutoML) Market, Segmentation By Offering, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
• 25.3. Canada Automated Machine Learning (AutoML) Market, Segmentation By Deployment, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
• 25.4. Canada Automated Machine Learning (AutoML) Market, Segmentation By Enterprise, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

26. South America Automated Machine Learning (AutoML) Market

• 26.1. South America Automated Machine Learning (AutoML) Market Overview
• 26.2. South America Automated Machine Learning (AutoML) Market, Segmentation By Offering, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
• 26.3. South America Automated Machine Learning (AutoML) Market, Segmentation By Deployment, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
• 26.4. South America Automated Machine Learning (AutoML) Market, Segmentation By Enterprise, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

27. Brazil Automated Machine Learning (AutoML) Market

• 27.1. Brazil Automated Machine Learning (AutoML) Market, Segmentation By Offering, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
• 27.2. Brazil Automated Machine Learning (AutoML) Market, Segmentation By Deployment, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
• 27.3. Brazil Automated Machine Learning (AutoML) Market, Segmentation By Enterprise, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

28. Middle East Automated Machine Learning (AutoML) Market

• 28.1. Middle East Automated Machine Learning (AutoML) Market Overview
• 28.2. Middle East Automated Machine Learning (AutoML) Market, Segmentation By Offering, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
• 28.3. Middle East Automated Machine Learning (AutoML) Market, Segmentation By Deployment, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
• 28.4. Middle East Automated Machine Learning (AutoML) Market, Segmentation By Enterprise, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

29. Africa Automated Machine Learning (AutoML) Market

• 29.1. Africa Automated Machine Learning (AutoML) Market Overview
• 29.2. Africa Automated Machine Learning (AutoML) Market, Segmentation By Offering, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
• 29.3. Africa Automated Machine Learning (AutoML) Market, Segmentation By Deployment, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
• 29.4. Africa Automated Machine Learning (AutoML) Market, Segmentation By Enterprise, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

30. Automated Machine Learning (AutoML) Market Competitive Landscape And Company Profiles

• 30.1. Automated Machine Learning (AutoML) Market Competitive Landscape
• 30.2. Automated Machine Learning (AutoML) Market Company Profiles
  • 30.2.1. Google LLC Overview, Products and Services, Strategy and Financial Analysis
  • 30.2.2. Microsoft Corporation Overview, Products and Services, Strategy and Financial Analysis
  • 30.2.3. Amazon Web Services Inc. Overview, Products and Services, Strategy and Financial Analysis
  • 30.2.4. International Business Machines Corporation Overview, Products and Services, Strategy and Financial Analysis
  • 30.2.5. Oracle Corporation Overview, Products and Services, Strategy and Financial Analysis

31. Automated Machine Learning (AutoML) Market Other Major And Innovative Companies

• 31.1. Salesforce Inc.
• 31.2. Teradata Corporation
• 31.3. Alteryx
• 31.4. Altair Engineering Inc.
• 31.5. EdgeVerve Systems Limited
• 31.6. TIBCO Software Inc.
• 31.7. DataRobot Inc.
• 31.8. Dataiku
• 31.9. BigPanda.
• 31.10. H2O.ai Inc.
• 31.11. KNIME
• 31.12. Cognitivescale
• 31.13. Anyscale Inc.
• 31.14. RapidMiner
• 31.15. Squark AI Inc.

32. Global Automated Machine Learning (AutoML) Market Competitive Benchmarking And Dashboard

33. Key Mergers And Acquisitions In The Automated Machine Learning (AutoML) Market

34. Recent Developments In The Automated Machine Learning (AutoML) Market

35. Automated Machine Learning (AutoML) Market High Potential Countries, Segments and Strategies

• 35.1 Automated Machine Learning (AutoML) Market In 2029 - Countries Offering Most New Opportunities
• 35.2 Automated Machine Learning (AutoML) Market In 2029 - Segments Offering Most New Opportunities
• 35.3 Automated Machine Learning (AutoML) Market In 2029 - Growth Strategies
  • 35.3.1 Market Trend Based Strategies
  • 35.3.2 Competitor Strategies

36. Appendix

• 36.1. Abbreviations
• 36.2. Currencies
• 36.3. Historic And Forecast Inflation Rates
• 36.4. Research Inquiries
• 36.5. The Business Research Company
• 36.6. Copyright And Disclaimer