Data Annotation Tools Market To Reach US$ 5.4 Billion by 2028 | CAGR of 25.5%

IMARC Group's latest report, titled "Data Annotation Tools Market: Global Industry Trends, Share, Size, Growth, Opportunity and Forecast 2023-2028", the global data annotation tools market size reached US$ 1.4 Billion in 2022. Looking forward, IMARC Group expects the market to reach US$ 5.4 Billion by 2028, exhibiting a growth rate (CAGR) of 25.5% during 2023-2028.

Data Annotation Tools Market Advanced Technology, Development and Future Demand:

The global market is primarily driven by the escalating demand for annotated data for training and improving machine learning (ML) models. This can be attributed to the incorporation of advanced technologies, such as artificial intelligence (AI), big data analytics, and deep learning, across various industries. In line with this, the growing volume of unorganized data from numerous organizations across the globe is propelling the market. The market is also fueled by extensive research and development (R&D) activities conducted by key players focusing on enhancing the accuracy and efficiency of data annotation tools.

Furthermore, the rising adoption of cloud-based operation models for improved scalability and flexibility across various end-use sectors, such as healthcare, automotive, and e-commerce, is providing an impetus to the market. Some of the other factors contributing to the market include rapid digitization, rising internet penetration, increasing usage of smart devices, and the advent of Industry 4.0.

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Competitive Landscape with Key Players:

• Alegion
• Amazon Web Services Inc. (Amazon.com Inc.)
• Appen Limited
• clickworker GmbH
• CloudFactory Limited
• Cogito Tech LLC
• Labelbox Inc
• Lionbridge Technologies LLC
• Scale AI Inc
• tagtog Sp. z o.o
• TELUS International (TELUS Corporation)

Data Annotation Tools Trends:

Data annotation tools refer to the software applications which assist in labeling, tagging, and categorizing data, commonly used in machine learning and natural language processing to create training data sets. They are designed for ease of use and adaptability to different data types and annotation tasks. Users can label objects, regions, and features in images, annotate text data, such as named entities, sentiment, and intent, and annotate speech and video data, such as speech segments, speaker detection and diarization, and action recognition. These tools facilitate collaborative projects as well as consistency and accuracy in the annotations. Moreover, they ensure precise annotation of large datasets, as well as reduce costs by crowdsourcing and automating some aspects of the process.

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Key Market Segmentation:

Breakup by Data Type:

• Text
• Image/Video
• Audio

Breakup by Annotation Type:

• Manual
• Semi-supervised
• Automatic

Breakup by End User:

• BFSI
• Healthcare
• Government
• Automotive
• IT and Telecommunication
• Retail and E-Commerce
• Others

Breakup by Region:

• North America (United States, Canada)
• Europe (Germany, France, United Kingdom, Italy, Spain, Others)
• Asia Pacific (China, Japan, India, Australia, Indonesia, Korea, Others)
• Latin America (Brazil, Mexico, Others)
• Middle East and Africa (United Arab Emirates, Saudi Arabia, Qatar, Iraq, Other)

Key Highlights of the Report:

• Market Performance (2017-2022)
• Market Outlook (2023-2028)
• Porter's Five Forces Analysis
• Market Drivers and Success Factors
• SWOT Analysis
• Value Chain
• Comprehensive Mapping of the Competitive Landscape

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This release was published on openPR.