Global Data Annotation Tools Market to Grow at 21.8% During 2024-2032, Impelled by Increasing Need to Improve ML Models

According to the latest report by IMARC Group, titled “Data Annotation Tools Market Report by Data Type (Text, Image/Video, Audio), Annotation Type (Manual, Semi-supervised, Automatic), End User (BFSI, Healthcare, Government, Automotive, IT and Telecommunication, Retail and E-Commerce, and Others), and Region 2024-2032," the global data annotation tools market is expected to grow at a CAGR of 21.8% during 2024-2032. Data annotation tools are cloud-based, on-premises, or containerized software-based solutions designed for labeling production-grade training data for machine learning (ML). They are generally designed with an explicit set of data types, such as spreadsheet, audio, video, text, image, and sensor data, that are used in different deployment models, including software as a service (SaaS), on-premises, container, and open-source systems. The data annotation includes sorting, cloning, filtering, and searching datasets that help enhance user experience, integrate labeling services and security, and improve precision.

Global Data Annotation Tools Market Trends:

The significant growth in the automotive industry across the globe is creating a positive outlook for the market. Data annotation tools are widely used to develop advanced autonomous driving technologies and deploy self-driving mechanisms, such as detecting vehicles, objects, and road signs and recognizing surroundings. Additionally, the increasing industrial need to improve machine learning (ML) models and the widespread utilization of artificial intelligence (AI) in various facial recognition and detection technologies are favoring the market growth. Apart from this, the development of specialized and predictive data annotation tools that enhance the accuracy of annotated videos and images and deliver high-precision datasets for AI-based applications are providing a thrust to the market growth. Furthermore, the widespread adoption of AI in the healthcare industry for increasing efficiency, sensing patterns, identifying injuries, and helping in automatically generating reports is acting as another growth-inducing factor. Besides this, the growing necessity of high-quality, well-labeled input data for improving the accuracy of ML algorithms, extensive research and development (R&D) activities, and increasing adoption of big data analytics to speed up data collecting and assimilation processes are supporting the market growth.

Market Summary:

• On the basis of the data type, the market has been classified into text, image or video, and audio.
• Based on the annotation type, the market has been divided into manual, semi-supervised, and automatic.
• On the basis of the end user, the market has been classified into BFSI, healthcare, government, automotive, IT and telecommunication, retail and e-commerce, and others.
• On a regional basis, the market has been categorized into North America (the United States and Canada), Asia Pacific (China, Japan, India, South Korea, Australia, Indonesia and others), Europe (Germany, France, the United Kingdom, Italy, Spain, Russia and others) Latin America (Brazil, Mexico and others), and Middle East and Africa.
• The competitive landscape of the industry has also been examined, with some of the key players being 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. and TELUS International (TELUS Corporation).

Report Scope:

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