Data Annotation Tools Market Size, Share & Trends Report

Data Annotation Tools Market Size, Share & Trends Analysis Report By Type (Text, Image/Video, Audio), By Annotation Type (Manual, Automatic, Semi-supervised), By Vertical, By Region, And Segment Forecasts, 2020 - 2027

  • Published Date: Mar, 2020
  • Base Year for Estimate: 2019
  • Report ID: GVR-2-68038-938-8
  • Format: Electronic (PDF)
  • Historical Data: 2016 - 2018
  • Number of Pages: 100

Industry Insights

The global data annotation tools market size was valued at USD 390.1 million in 2019 and is projected to register a CAGR of 26.9% from 2020 to 2027. Increasing adoption of image data annotation tools in the automotive, retail, and healthcare sectors is a key factor driving the market. These tools enable users to enhance the value of data by adding attribute tags to it or labeling it.

The key benefit of using annotation tools is that the combination of data attributes enables users to manage the data definition at a single location and eliminates the need to rewrite similar rules in multiple places. The rise of big data and increase in the number of large datasets are likely to necessitate the use of artificial intelligence technologies in the field of data annotations.

Europe data annotation tools market

Data annotation is expected to play a major role in enhancing the applications of AI in the healthcare sector. AI-backed machines use machine vision or computer vision in medical imaging data technologies to sense patterns and identify possible injuries, which assists medical practitioners in automatically generating reports after the individual is examined. The database of CT scan, MRI, and X-Ray images can be easily screened by the AI to determine various injuries. Data annotation tools help train AI systems in differentiating data obtained from normal and injured medical images to generate the final reports of the examined individuals.

Technologies such as Internet of Things (IoT), Machine Learning (ML), robotics, advanced predictive analytics, and Artificial Intelligence (AI) generate massive data. With changing technologies, data efficiency proves to be essential for creating new business innovations, infrastructure, and economics. These factors have significantly contributed to the growth of the market. With the widening scope of growth in data labelling, companies developing AI-enabled healthcare applications are collaborating with data annotation tool companies providing the required datasets that can assist them in enhancing their machine learning and deep learning capabilities.

However, inaccuracy of data annotation tools acts as a restraint to the growth of the market. For instance, a given image may have low resolution and can include multiple objects that makes it difficult to label. The primary challenge faced by the market is issues related to inaccuracy in the quality of data labelled. In some cases, the data labeled manually may contain erroneous labeling and the time to detect such erroneous labels may vary, which further adds to the cost of the entire annotation process. However, with the development of sophisticated algorithms, the accuracy of automated tools is improving, thus reducing the dependency on manual annotation and cost of the tools in the near future.

Type Insights

Based on type, the global data annotation tools market is segmented into text, image/video, and audio. In 2019, the text annotation tool segment accounted for the largest market share and is expected to expand at a promising pace over the forecast period. This is attributed to rising applications in e-commerce and clinical research. The audio segment is expected to witness moderate growth in the years to come.

The image/video annotation tool segment is expected to dominate the market over the forecast period. Some of the major applications of image annotation tools are in the medical industry, particularly in the field of medical imaging. For example, in 2017, the total investment in startups developing machine learning solutions and tools using medical images was more than USD 200 million. Startups such as Infervision, Zebra Medical Vision, and Arterys are some of the prominent startups in the healthcare data annotation market.

Annotation Type Insights

In 2019, the manual segment accounted for the largest market share. Manual data annotation is a process of labeling or annotating any data by humans. The approach is popular owing to its benefits such as accuracy, high level of integrity, need for minimal administration of data annotation efforts, and a higher chance of discovering intriguing insights pertaining to the data as compared to automatic annotation tools, which can be later integrated into an algorithm. However, as manual annotation tools can be expensive and time -consuming, labeled data gathered through crowdsourcing activities is used for a variety of applications.

The automatic segment is expected to witness promising growth over the forecast period. AI is becoming vital to the data annotation tools industry as the technology allows the extraction of high-level and complex abstractions from the datasets using a hierarchical learning process. Need for mining and extracting meaningful patterns from voluminous data is fueling the growth of AI, which is expected to further drive the demand for automatic annotation tools. The semi-supervised tools can be used to identify specific labeled data or classify the unlabeled data. Limited use of this annotation tool type will contribute to moderate growth of the segment.

Vertical Insights

The healthcare segment is expected to witness significant growth over the forecast period. AI is widely adopted in the healthcare sector for various applications such as treatment prediction, diagnostic automation, drug development, and gene sequencing. The datasets in healthcare are required to be trained with the machine learning algorithms. The quality of the training significantly impacts the efficacy and accuracy of the algorithm used for developing AI-based applications. Access to accurate and high-quality datasets is the key step in developing a successful AI-enabled product in the healthcare sector. Thus, data annotation tools boost the development of the sector by providing training datasets to the AI.

Global data annotation tools market

The automotive segment is anticipated to witness steady growth over the forecast period as data annotation tools are gaining wide acceptance in self-driving vehicles. Increasing R&D spending on the improvement of image annotation for the developments in the field of self-driving vehicles is boosting the growth of the market. For instance, in 2018, the BMW Group invested the largest share of its revenue in the research and development activities. The company is mainly focusing on the development of autonomous and electric vehicles.

Regional Insights

North America accounted for the dominant share in the market in 2019. This is due to rapid product and geographic expansion strategy undertaken by vendors in order to gain an edge in the market. Europe is expected to witness steady growth over the forecast period. Rising focus on image annotation is anticipated to enhance the operations of retail and automotive verticals in Europe.

Asia Pacific is anticipated to register the highest CAGR over the forecast period. Emerging economies in Asia Pacific hold significant potential for the widespread adoption of data annotation tools, particularly in the healthcare and financial services verticals. The positive growth of the healthcare industry in Asia Pacific is marked by increasing adoption of technology and innovative healthcare access programs. These factors are anticipated to boost the demand for image annotation tools in this region in the near future. 

Data Annotation Tools Market Share Insights

Key players offering exclusive products and services in the market include Annotate.com; Appen Limited; CloudApp; Cogito Tech LLC; Deep Systems; Labelbox, Inc.; LightTag;Lotus Quality Assurance; Playment Inc.; Tagtog Sp. z o.o; CloudFactory Limited; Clickworker GmbH; Alegion; Figure Eight Inc.; Amazon Mechanical Turk, Inc.; Explosion AI; Mighty AI, Inc.; Trilldata Technologies Pvt. Ltd. (Data Turks); Scale Inc.; and Google, LLC.

Vendors are focusing on raising funds for product launches and geographical expansion. For instance, in August 2018, Scale Inc., a U.S. based company providing data annotation tools and solutions, announced that it had raised funds worth USD 18 million to label data gathered by companies developing self-driving cars, such as General Motors and Lyft, Inc.

Report Scope

Attribute

Details

Base year for estimation

2019

Actual estimates/Historical data

2016 - 2018

Forecast period

2020 - 2027

Market representation

Revenue in USD Million & CAGR from 2020 to 2027

Regional scope

North America, Europe, Asia-Pacific, South America, and MEA

Country scope

U.S., Canada, Mexico, U.K., Germany, France, China, Japan, India, and Brazil

Report coverage

Revenue forecast, company share, competitive landscape, growth factors, and trends

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Segments Covered in the Report

This report forecasts revenue growth at the global, regional, and country levels and provides an analysis of the latest industry trends and opportunities in each of the sub-segments from 2016 to 2027. For the purpose of this study, Grand View Research has segmented the global data annotation tools market report based on type, annotation type, vertical, and region:

  • Type Outlook (Revenue, USD Million, 2016 - 2027)

    • Text

    • Image/Video

    • Audio

  • Annotation Type Outlook (Revenue, USD Million, 2016 - 2027)

    • Manual

    • Semi-supervised

    • Automatic

  • Vertical Outlook (Revenue, USD Million, 2016 - 2027)

    • IT

    • Automotive

    • Government

    • Healthcare

    • Financial Services

    • Retail

    • Others

  • Regional Outlook (Revenue, USD Million, 2016 - 2027)

    • North America

      • U.S.

      • Canada

      • Mexico

    • Europe

      • Germany

      • U.K.

      • France

    • Asia Pacific

      • China

      • Japan

      • India

    • South America

      • Brazil

    • Middle East and Africa

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