Edit Content
Bizwit-Logo-Final

Bizwit Research & Consulting LLP is a global provider of business intelligence & consulting services. We have a strong primary base of key industry leaders along with the chain of industry analysts to analyze the market trends and its future impact in order to estimates and forecast different business segments and markets. 

Global AI Training Dataset Market to reach USD 4.0 billion by 2027.

Global AI Training Dataset Market Size study, By Type (Text, Image/Video, Audio), By Vertical (IT, Automotive, Government, Healthcare, BFSI) and Regional Forecasts 2021-2027

Product Code: ENGE-15272531
Publish Date: 7-11-2021
Page: 200

Global AI Training Dataset Market is valued approximately USD 1.15 billion in 2020 and is anticipated to grow with a healthy growth rate of more than 19.50 % over the forecast period 2021-2027. AI Training data is basically used to provide AI based training and machine learning data to make necessary decisions. For example, if a model for a self-driving car is build, the training dataset will include videos and images labeled to recognize street signs, car signals vs people. Rise in demand of artificial intelligence in various applications such as video, audio recognition pushes the market growth of AI training dataset. For Instance: according to IRDS International Roadmap for Devices The global AI market is estimated to attain USD 390.9 billion by 2025, with CAGR of 55.6%. It also states that AI applications, industrial robotics industries in the big data, medical, video and audio recognition, and autonomous vehicles, can provide those opportunities. Increasing adoption of AI and machine learning by government, defense, and private organization will enhance the market growth However, complex implementation and lack of technical active understanding impedes the growth of the market over the forecast period of 2021-2027. Also, rise in adoption for human and machine interaction is likely to increase the market growth during the forecast period.

The regional analysis of global AI Training Dataset Market is considered for the key regions such as Asia Pacific, North America, Europe, Latin America and Rest of the World. North America is the leading region across the world in terms of market share owing to the vendors actively focusing on launching latest datasets to enhance the adoption of AI technology various sectors. Whereas Asia-Pacific is also anticipated to exhibit highest growth rate over the forecast period 2021-2027. Factors such as increasing adoption rate of rising technologies would create lucrative growth prospects for the AI Training Dataset Market across Asia-Pacific region.

Major market player included in this report are:
Google, LLC (Kaggle)
Appen Limited
Cogito Tech LLC
Lionbridge Technologies, Inc.
Amazon Web Services, Inc.
Microsoft Corporation
Scale AI Inc.
Samasource Inc.
Alegion
Deep Vision Data

The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming eight years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within each of the regions and countries involved in the study. Furthermore, the report also caters the detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, the report shall also incorporate available opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and product offerings of key players. The detailed segments and sub-segment of the market are explained below:
By Type:
Text
Image/Video
Audio
By Vertical:
IT
Automotive, Government
Healthcare
BFSI
By Region:
North America
U.S.
Canada
Europe
UK
Germany
France
Spain
Italy
ROE

Asia Pacific
China
India
Japan
Australia
South Korea
RoAPAC
Latin America
Brazil
Mexico
Rest of the World

Furthermore, years considered for the study are as follows:

Historical year – 2018, 2019
Base year – 2020
Forecast period – 2021 to 2027

Target Audience of the Global AI Training Dataset Market in Market Study:

Key Consulting Companies & Advisors
Large, medium-sized, and small enterprises
Venture capitalists
Value-Added Resellers (VARs)
Third-party knowledge providers
Investment bankers
Investors

Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2019-2027 (USD Billion)
1.2.1. Global AI Training Dataset Market, by Region, 2019-2027 (USD Billion)
1.2.2. Global AI Training Dataset Market, by Type, 2019-2027 (USD Billion)
1.2.3. Global AI Training Dataset Market, by Vertical, 2019-2027 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global AI Training Dataset Market Definition and Scope
2.1. Objective of the Study
2.2. Market Definition & Scope
2.2.1. Scope of the Study
2.2.2. Industry Evolution
2.3. Years Considered for the Study
2.4. Currency Conversion Rates
Chapter 3. Global AI Training Dataset Market Dynamics
3.1. AI Training Dataset Market Impact Analysis (2019-2027)
3.1.1. Market Drivers
3.1.1.1. Rise in demand of artificial intelligence in various applications
3.1.1.2. Increasing adoption of AI and machine learning by government, defence, and private organizations.
3.1.2. Market Challenges
3.1.2.1. Complex implementation and lack of technical active understanding
3.1.3. Market Opportunities
3.1.3.1. Rise in adoption for human and machine interaction
Chapter 4. Global AI Training Dataset Market Industry Analysis
4.1. Porter’s 5 Force Model
4.1.1. Bargaining Power of Suppliers
4.1.2. Bargaining Power of Buyers
4.1.3. Threat of New Entrants
4.1.4. Threat of Substitutes
4.1.5. Competitive Rivalry
4.1.6. Futuristic Approach to Porter’s 5 Force Model (2018-2027)
4.2. PEST Analysis
4.2.1. Political
4.2.2. Economical
4.2.3. Social
4.2.4. Technological
4.3. Investment Adoption Model
4.4. Analyst Recommendation & Conclusion
Chapter 5. Global AI Training Dataset Market, by Type
5.1. Market Snapshot
5.2. Global AI Training Dataset Market by Type, Performance – Potential Analysis
5.3. Global AI Training Dataset Market Estimates & Forecasts by Type 2018-2027 (USD Billion)
5.4. Global AI Training Dataset Market, Sub Segment Analysis
5.4.1. Text
5.4.2. Image/Video
5.4.3. Audio
Chapter 6. Global AI Training Dataset Market, by Vertical,
6.1. Market Snapshot
6.2. Global AI Training Dataset Market by Vertical, Performance – Potential Analysis
6.3. Global AI Training Dataset Market Estimates & Forecasts by Vertical, 2018-2027 (USD Billion)
6.4. Global AI Training Dataset Market, Sub Segment Analysis
6.4.1. IT
6.4.2. Automotive
6.4.3. Government
6.4.4. Healthcare
6.4.5. BFSI
Chapter 7. Global AI Training Dataset Market, Regional Analysis
7.1. Global AI Training Dataset Market, Regional Market Snapshot
7.2. North America AI Training Dataset Market
7.2.1. U.S. AI Training Dataset Market
7.2.1.1. Type breakdown estimates & forecasts, 2018-2027
7.2.1.2. Vertical breakdown estimates & forecasts, 2018-2027
7.2.2. Canada AI Training Dataset Market
7.3. Europe AI Training Dataset Market Snapshot
7.3.1. U.K. AI Training Dataset Market
7.3.2. Germany AI Training Dataset Market
7.3.3. France AI Training Dataset Market
7.3.4. Spain AI Training Dataset Market
7.3.5. Italy AI Training Dataset Market
7.3.6. Rest of Europe AI Training Dataset Market
7.4. Asia-Pacific AI Training Dataset Market Snapshot
7.4.1. China AI Training Dataset Market
7.4.2. India AI Training Dataset Market
7.4.3. Japan AI Training Dataset Market
7.4.4. Australia AI Training Dataset Market
7.4.5. South Korea AI Training Dataset Market
7.4.6. Rest of Asia Pacific AI Training Dataset Market
7.5. Latin America AI Training Dataset Market Snapshot
7.5.1. Brazil AI Training Dataset Market
7.5.2. Mexico AI Training Dataset Market
7.6. Rest of The World AI Training Dataset Market

Chapter 8. Competitive Intelligence
8.1. Top Market Strategies
8.2. Company Profiles
8.2.1. Google, LLC (Kaggle)
8.2.1.1. Key Information
8.2.1.2. Overview
8.2.1.3. Financial (Subject to Data Availability)
8.2.1.4. Product Summary
8.2.1.5. Recent Developments
8.2.2. Deep Vision Data
8.2.3. Appen Limited
8.2.4. Cogito Tech LLC
8.2.5. Lionbridge Technologies, Inc.
8.2.6. Amazon Web Services, Inc.
8.2.7. Microsoft Corporation
8.2.8. Scale AI Inc.
8.2.9. Samasource Inc.
8.2.10. Alegion
Chapter 9. Research Process
9.1. Research Process
9.1.1. Data Mining
9.1.2. Analysis
9.1.3. Market Estimation
9.1.4. Validation
9.1.5. Publishing
9.2. Research Attributes
9.3. Research Assumption

At Bizwit Research and Consultancy, we employ a thorough and iterative research methodology with the goal of minimizing discrepancies, ensuring the provision of highly accurate estimates and predictions over the forecast period. Our approach involves a combination of bottom-up and top-down strategies to effectively segment and estimate quantitative aspects of the market, utilizing our proprietary data & AI tools. Our Proprietary Tools allow us for the creation of customized models specific to the research objectives. This enables us to develop tailored statistical models and forecasting algorithms to estimate market trends, future growth, or consumer behavior. The customization enhances the accuracy and relevance of the research findings.
We are dedicated to clearly communicating the purpose and objectives of each research project in the final deliverables. Our process begins by identifying the specific problem or challenge our client wishes to address, and from there, we establish precise research questions that need to be answered. To gain a comprehensive understanding of the subject matter and identify the most relevant trends and best practices, we conduct an extensive review of existing literature, industry reports, case studies, and pertinent academic research.
Critical elements of methodology employed for all our studies include:
Data Collection:
To determine the appropriate methods of data collection based on the research objectives, we consider both primary and secondary sources. Primary data collection involves gathering information directly from various industry experts in core and related fields, original equipment manufacturers (OEMs), vendors, suppliers, technology developers, alliances, and organizations. These sources encompass all segments of the value chain within the specific industry. Through in-depth interviews, we engage with key industry participants, subject-matter experts, C-level executives of major market players, industry consultants, and other relevant experts. This allows us to obtain and validate critical qualitative and quantitative information while evaluating market prospects. AI and Big Data are instrumental in our primary research, providing us with powerful tools to collect, analyze, and derive insights from data efficiently. These technologies contribute to the advancement of research methodologies, enabling us to make data-driven decisions and uncover valuable findings.
In addition to primary sources, we extensively utilize secondary sources to enhance our research. These include directories, databases, journals focusing on related industries, company newsletters, and information portals such as Bloomberg, D&B Hoovers, and Factiva. These secondary sources enable us to identify and gather valuable information for our comprehensive, technical, market-oriented, and commercial study of the market. Additionally, we utilize AI algorithms to automate the collection of vast amounts of data from various sources such as surveys, social media platforms, online transactions, and web scraping. And employ Big Data technologies for storage and processing of large datasets, ensuring that no valuable information is missed during the data collection process.
Data Analysis:
Our team of experts carefully examine the gathered data using suitable statistical techniques and qualitative analysis methods. For quantitative analysis, we employ descriptive statistics, regression analysis, and other advanced statistical methods, depending on the characteristics of the data. This analysis may also incorporate the utilization of AI tools and big data analysis techniques to extract meaningful insights.
To ensure the accuracy and reliability of our findings, we extensively leverage data science techniques, which help us minimize discrepancies and uncertainties in our analysis. We employ Data Science to clean and preprocess the data, ensuring its quality and reliability. This involves handling missing data, removing outliers, standardizing variables, and transforming data into suitable formats for analysis. The application of data science techniques enhances our accuracy, efficiency, and depth of analysis, enabling us to stay competitive in dynamic market environments.
Market Size Estimation:
Our proprietary data tools play a crucial role in deriving our market estimates and forecasts. Each study involves the creation of a unique and customized model. The model incorporates the gathered information on market dynamics, technology landscape, application development, and pricing trends. AI techniques, such as machine learning and deep learning, aid us to analyze patterns within the data to identify correlations, trends, and relationships. By recognizing patterns in consumer behavior, purchasing habits, or market dynamics, our AI algorithms aid us in more precise estimations of market size. These factors are simultaneously analyzed within the model, allowing for a comprehensive assessment. To quantify their impact over the forecast period, correlation, regression, and time series analysis are employed.
To estimate and validate the market size, we employ both top-down and bottom-up approaches. The preference is given to a bottom-up approach, where key regional markets are analyzed as separate entities. This data is then integrated to obtain global estimates. This approach is crucial as it provides a deep understanding of the industry and helps minimize errors.
In our forecasting process, we consider various parameters such as economic tools, technological analysis, industry experience, and domain expertise. By taking all these factors into account, we strive to produce accurate and reliable market forecasts. When forecasting, we take into consideration several parameters, which include:
Market driving trends and favorable economic conditions
Restraints and challenges that are expected to be encountered during the forecast period.
Anticipated opportunities for growth and development
Technological advancements and projected developments in the market
Consumer spending trends and dynamics
Shifts in consumer preferences and behaviors.
The current state of raw materials and trends in supply versus pricing
Regulatory landscape and expected changes or developments.
The existing capacity in the market and any expected additions or expansions up to the end of the forecast period.
To assess the market impact of these parameters, we assign weights to each one and utilize weighted average analysis. This process allows us to quantify their influence on the market and derive an expected growth rate for the forecasted period. By considering these various factors and applying a weighted analysis approach, we strive to provide accurate and reliable market forecasts.
Insight Generation & Report Presentation:
After conducting the research, our experts analyze the findings in relation to the research objectives and the specific needs of the client. They generate valuable insights and recommendations that directly address the client’s business challenges. These insights are carefully connected to the research findings to provide a comprehensive understanding.
Next, we create a well-structured research report that effectively communicates the research findings, insights, and recommendations to the client. To enhance clarity and comprehension, we utilize visual aids such as charts, graphs, and tables. These visual elements are employed to present the data in an engaging and easily understandable format, ensuring that the information is accessible and visually appealing to the client. Our aim is to deliver a clear and concise report that conveys the research findings effectively and provides actionable recommendations to meet the client’s specific needs.

Need Assistance

Contact Person -
Krishant Mennon
Call us @
+ 91 99931 15879
Email: sales@bizwitresearch.com

Checkout

Why Choose Us?

Quality over Quantity

Backed by 60+ paid data sources our reports deliver crisp insights with no compromise quality.

Analyst Support

24x7 Chat Support plus
free analyst hours with every purchase

Flawless Methodology

Our 360-degree approach of market study, our research methods leave stones unturned.

Enquiry Now