Acknowledging the kind of traction gained by this market, recently published a study report by industry data analytics asserts the global AI Training Data Market is expected to grow from $1.5 billion in 2021, registering a phenomenal CAGR of 19.7% during the review period (2022 to 2027).
Artificial Intelligence (AI) is gaining important importance in various industrial applications such as manufacturing, IT, BFSI, retail and e-commerce, and healthcare. The rising demand for application-specific training data is also opening opportunities for new entrants. AI is becoming vital to big data as the technology allows the extraction of high-level and complex abstractions using a hierarchical learning process important to the need for mining and extracting meaningful patterns from voluminous data.
The growing need for enterprise internetworking among employees, partners, distributors, suppliers, and others in the business value chain has given way to the growing employment of the enterprise social software market products across desktops, laptops, and mobile personal devices. Though enterprises across the globe are looking forward to incubating Enterprise Social Software into their current work scenarios, ESS providers look forward to gaining a better competitive advantage in the emerging market by creating new technological features that facilitate the quicker adoption of these. AI Training data is essentially used to provide AI-based training and machine learning data to make essential decisions. For example, if a model for a self-driving car is built, the training dataset will include videos and images labeled to recognize street signs, car signals vs people. The rise in demand for artificial intelligence in various applications such as video, audio recognition pushes the market growth of AI training datasets.
The AI Training Data Market is rising at a very fast pace and has seen the focus of many local and regional vendors offering precise application products for numerous end users. The three dependencies for the status of major companies in the market are company profile, profitable gross margin, the prices they charge. These are the main players in this market includes 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
Google Cloud Introduce Vertex AI- At Google I/O today Google Cloud announced Vertex AI, a new managed machine learning platform that is meant to make it easier for developers to deploy and maintain their AI models. It’s a bit of an odd announcement at I/O, which tends to focus on mobile and web developers and doesn’t traditionally feature a lot of Google Cloud news, but the fact that Google decided to announce Vertex today goes to show how important it thinks this new service is for a wide range of developers.
Tesla to launch its in-house chip for the training of AI models in data centers- Tesla launch chip to train AI: Recently Tesla director Ganesh Venkataraman unveiled an innovation of Tesla’s and that innovation is a computer chip which is designed and built in the entire house, and the company is utilizing it for running their supercomputers which are known as Dojo.
AI Training Data Market is segmented based on the type, applications, companies, and regions.
By Type, it is segmented into
By Applications, it is segmented into
Asia-Pacific is likely to witness a important growth, owing to emerging frugalities such as India, China, and South Korea. These nations are developing as industrial hubs, owing to which many industries in the region are adopting AI and automatic solutions to gain a modest edge and achieve extreme output, which fuels growth of the market.
The AI Training Data Market describes the factors driving the global growth opportunities in upcoming years and highlights market channels. In addition, the report analyzes market size and share, trends, by geographic region, end-use type, and segment. It focuses extensively on revealing a detailed regional analysis. The Global AI Training Data Market report also conducted a PESTEL analysis of the industry to study the main influencing factors and entry barriers of the industry.
Report Attributes | Report Details |
Forecast Period 2022 to 2028 CAGR | CAGR of 19.7% during the review period (2022 to 2027). |
By Type |
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By Application |
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By Companies | Accenture, Amdocs, Capgemini SE, CSG Systems International, Inc., Hewlett Packard Enterprise, |
Regions Covered |
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Countries Covered |
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Base Year | 2022 |
Historical Year | 2017 to 2021 |
Forecast Year | 2022 to 2027 |
Number of Pages | 116 |
Customization Available | Yes, the report can be customized as per your needs |
All our reports are custom made to your company's needs to a certain extent, we do provide 5 free consulting hours along with the purchase of each report, and this will allow you to request any additional data to customize the report as your needs.
How big is the AI training dataset market?
The global AI training dataset market size was estimated at USD 1,408.5 million in 2021 and is expected to reach USD 1,728.2 million in 2022.
What are the key driving factors and tasks in the AI training dataset market?
Several developments in the field of AI training dataset are driving the market in coming years, though, lack of skill have incomplete the growth of the market.
What are the key driving factors for the AI Training Dataset Market?
Artificial intelligence (AI) is gaining important prominence due to rising adoption across various data-driven requests, The amount of data made across various end-use governments has driven the acceptance of AI.
Who are the key players in the AI training dataset market?
Some key players working in the AI training dataset market include Google, LLC (Kaggle); Appen Partial; Cogito Tech LLC; Lionbridge Technologies, Inc.; Amazon Web Services, Inc.; and Microsoft Corporation.
SECONDARY RESEARCH
Secondary Research Information is collected from a number of publicly available as well as paid databases. Public sources involve publications by different associations and governments, annual reports and statements of companies, white papers and research publications by recognized industry experts and renowned academia etc. Paid data sources include third party authentic industry databases.
PRIMARY RESEARCH
Once data collection is done through secondary research, primary interviews are conducted with different stakeholders across the value chain like manufacturers, distributors, ingredient/input suppliers, end customers and other key opinion leaders of the industry. Primary research is used both to validate the data points obtained from secondary research and to fill in the data gaps after secondary research.
MARKET ENGINEERING
The market engineering phase involves analyzing the data collected, market breakdown and forecasting. Macroeconomic indicators and bottom-up and top-down approaches are used to arrive at a complete set of data points that give way to valuable qualitative and quantitative insights. Each data point is verified by the process of data triangulation to validate the numbers and arrive at close estimates.
EXPERT VALIDATION
The market engineered data is verified and validated by a number of experts, both in-house and external.
REPORT WRITING/ PRESENTATION
After the data is curated by the mentioned highly sophisticated process, the analysts begin to write the report. Garnering insights from data and forecasts, insights are drawn to visualize the entire ecosystem in a single report.
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