Data Annotation Tools Market Size & Share 2023 to 2032
Market Size by Data Type (Image/Video [Bounding Box, Semantic Annotation, Polygon Annotation, Lines and Splines], Text, Audio), by Annotation Approach (Manual, Automated), by End Use & Global Forecast.
Report ID: GMI3823
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Published Date: April 2023
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Report Format: PDF
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Authors:
Preeti Wadhwani, Aishvarya Ambekar
Data Annotation Tools Market Size
Data Annotation Tools Market size was valued at USD 1.8 billion in 2022 and is predicted to record over 25% CAGR from 2023 to 2032.
Data Annotation Tools Market Key Takeaways
Market Size & Growth
Key Market Drivers
Challenges
Growing significance of high-quality, well-labeled input data to improve the accuracy of machine learning algorithms has driven the use of data annotation tools. Data labeling methods help to develop complex AI applications like facial recognition, natural language processing, and marketing automation by converting massive amounts of unstructured data into structured information.
Furthermore, unlike manual labeling which takes a very lengthy time, these techniques help with the speedy classification and labeling of vast data repositories. As an illustration, in June 2021, Innotescus introduced its picture and video annotation platform for machine learning. The platform offers a user-friendly annotation workspace, thorough analytics, and a collaborative setting for teams to create datasets of the highest caliber.
One of the main challenges to the development of data annotation technologies is poor data quality. The annotation process is complicated due to the low-resolution photos, missing data values, and data from unreliable sources, which dramatically reduces the performance of the AI model created using such training data. According to the report released by MIT Sloan University, in the United States, more than 50% of AI projects failed owing to a lack of high-quality training data, and over 70% of the firms failed to advance their AI solutions into commercial production.
Data Annotation Tools Market Analysis
Data annotation tools market share from the image/video segment will grow at a CAGR of 30% between 2023 and 2032. Tools for classifying and annotating picture and video-based data are included in the category of image/video annotation. The usefulness of image/video labeling tools for enhancing computer vision and object recognition has multiplied since images and videos make up the majority of the data collected by sensors. Due to accurate and highly precise data labeling, enterprises are accomplishing their strategic goals of creating cutting-edge artificial intelligence technologies, such as facial recognition, self-driving cars, and robotic automation.
Data annotation tools market share from the automated data annotation segment is set to cross USD 9 billion by 2032. Though less accurate than manual data annotation, automated data annotation techniques are ideal for big data annotation on a wide scale. Fully automated data labeling helps businesses to speed up the development of their AI-based initiatives by reliably and quickly converting datasets into high-quality input training data. The huge cost savings compared to manual data labeling is another reason influencing the adoption of automated data annotation. Hourly expenses charged by manual data annotators translate into significant costs for large datasets with millions of data points.
The data annotation tools market share from the healthcare application segment is anticipated to witness over 35% CAGR through 2032. Healthcare organizations can conduct faster research in the area of automated patient diagnosis due to the adoption of healthcare training data for developing sophisticated AI applications. The development of high-performing healthcare solutions has increased the demand for quality annotated medical datasets. Medical imaging data such as X-rays, CT scans, and other image-based test results can be labeled, which enables AI systems to automatically evaluate the data for diseases, speeding up drug discovery, and advancing precision medicine.
North America data annotation tools market size is expected to reach USD 12 billion by 2032. The widespread use of data labeling tools has been aided by the growing trend of AI and machine learning technology used by businesses of all kinds. Federal institutions in North America are among the first to deploy data labeling technologies to improve general economic growth and give better public administration through the integration of AI. Furthermore, it is anticipated that the presence of major industry companies like IBM, Microsoft, Google, and AWS will hasten the spread of data annotation tools in the region. Rapid developments in the AI and deep learning industries is likely make North America a lucrative revenue ground for industry.
Data Annotation Tools Market Share
Some of the leading companies involved in the data annotation tools market include:
Companies in the data annotation tools business place a high priority on forming strategic alliances and enhancing their research capabilities in order to offer novel solutions and routinely release software upgrades, bolstering their market position and acquiring a competitive edge.
In November 2022, Medcase, a well-known developer of healthcare AI solutions, and NTT DATA, a top supplier of digital business and IT services, signed a legally binding agreement. The two businesses claimed to jointly provide data discovery and enrichment solutions for medical imaging through this partnership. Through this cooperation, Medcase's clients will have access to the Advocate AI data cooperative network from NTT DATA, allowing innovators to get patient studies for their projects, including medical imaging.
This data annotation tools market research report includes in-depth coverage of the industry with estimates & forecasts in terms of revenue in USD from 2018 to 2032 for the following segments:
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Market, By Data Type
Market, By Annotation approach
Market, By Application
The above information has been provided for the following regions and countries:
Research methodology, data sources & validation process
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Our 6-step research process
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