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Data Annotation Tools Market Size By Data Type (Image/Video [Bounding Box, Semantic Annotation, Polygon Annotation, Lines and Splines], Text, Audio), By Annotation Approach (Manual Annotation, Automated Annotation), By End Use (Telecom, BFSI, Healthcare, Retail, Automotive, Agriculture), COVID-19 Impact Analysis, Regional Outlook, Growth Potential, Competitive Market Share & Forecast, 2022 – 2028

  • Report ID: GMI3823
  • Published Date: Feb 2022
  • Report Format: PDF

Industry Trends

Data Annotation Tools Market size exceeded USD 1 billion in 2021 and is anticipated to grow at a CAGR of over 30% between 2022 and 2028. The growing importance of high-quality and well-labeled input data for augmenting the accuracy of machine learning algorithms is likely to drive the industry growth. Data annotation tools are highly suited for situations where unlabeled data is available in large volumes and will create new opportunities for the market expansion.

Data Annotation Tools Market

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The industry has witnessed rapid amplification during the ongoing COVID-19 pandemic. As enterprises realize the importance of the latest, accurately labeled updated datasets, which depict the most recent impact of COVID-19 on supply chains and demand, the adoption of data annotation tools has risen sharply across the globe. The importance of accurately labeled datasets in the healthcare industry has become even more paramount, considering that multiple strains of COVID-19 have evolved.

AI-based data annotation tools are vastly aiding the healthcare sector in detecting COVID-19 hotspots, predicting new patient inflow, and ensuring timely supply of critical medicines & medical care equipment.

A spike in the deployment of image/video text annotation for empowering computer vision across Germany

Germany Data Annotation Tools Market Share, By Data Type

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The image/video annotation tools market in Germany held about 45% in 2021 and is expected to continue its dominance through 2028. This is attributed to the increasing uptake of data annotation tools for labeling image/video to improve entity recognition.

With the continuously evolving machine learning landscape in the region, data annotation tool vendors are developing new technologies for improving the accuracy of annotated images/videos and delivering high precision datasets for AI-based applications.

Reduced chances of errors and expertise in handling complex datasets are boosting demand in China

China Data Annotation Tools Market Size, By Annotation Approach

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In China, the manual data annotation tools market is poised to account for about USD 400 million by 2028 driven by the surging adoption to ensure high-quality input data. Manually labeled data is less prone to errors due to the involvement of highly trained domain experts, who can handle complex data labeling scenarios, where machine-based algorithms would perform poorly. Medical image labeling requires the expertise of specialist medical professionals in cases where the machine learning systems cannot accurately label the data.

Data annotation service providers in the China are offering innovative data labeling services & annotated healthcare training data validated by medical experts to strengthen their market presence and add value to their offerings. As enterprises focus strongly on developing new & innovative solutions to cater to the growing demand, the market will witness a sharp expansion.

Accelerated developments in connected car technologies and autonomous mobility in the U.S.

The automotive application in the U.S. data annotation tools market is estimated to register substantial gains of nearly 35% through 2028 as the automotive manufacturers are transitioning toward leveraging AI for developing self-driving vehicles and connected cars. A gradual shift of the U.S. automotive industry toward full autonomy has been fueled with the development in AI and ML technologies, which make heavy use of labeled data to deploy self-driving mechanisms. The accurately labeled data assists on-board AI to make instantaneous decisions during complex road situations, avoiding major accidents and object collision.

For instance, in December 2021, Tesla launched a new auto labeling tool for its self-driving vehicles. The auto labeling tool is able to use an extensive data set to improve its neural nets powering suite of autopilot feature. As automotive enterprises gradually acknowledge the benefits of high-quality labeled data to develop reliable onboard AI, the market will undergo a rapid growth.

Abundance of skilled workforce and rise of multiple data labeling start-ups in Asia Pacific

Asia Pacific Data Annotation Tools Market Share, By Country

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Asia Pacific captured a significant portion of the data labelling tools market with over 20% revenue share in 2021. Rapid growth of IT infrastructure, increasing number of data labeling start-ups, and wide-scale adoption of AI technologies have accentuated the regional market growth.

With improvement in ICT landscape, abundance of skilled workforce, and increasing awareness regarding reliable training data among AI-related SMEs, the region is projected to become a major potential market. For instance, in June 2021, ByteBridge launched the world’s first mobile 3D cloud point data labeling service, which is the collaboration of various dots spread around 3D space. It is widely used for product development & analysis in aerospace, traffic, and others.

Hefty R&D investments to fuel innovation and amplify product performance are emerging as the key go-to-market strategies

The prominent players operating in the data annotation tools market are propelling investments in new data labeling tools to improve software performance and promote the adoption of AI technologies. For instance, in June 2020, SuperAnnotate raised USD 3 million in venture funding. The investment was led by Point Nine Capital and used to speed up data labeling capabilities.

Startups, such as Mighty AI, iMerit, and MonkeyLearn, are focusing on developing low-cost data labeling tools with innovative features, such as big data support and fully automated data labeling, to expand their market share. Established players, such as AWS, Appen, and Google, have turned their focus on complementing the existing data annotation tool features to gain a wider share and bridge white gaps in the existing ecosystem.

Some of the key data annotation tools market players include Alegion Inc., Appen Limited, Amazon Web Services, Inc. (Amazon.com, Inc.), Clickworker GmbH, CloudApp, Inc., CloudFactory Limited, Cogito Tech LLC., Dataturks, Defined AI, Google LLC., Hive, IBM Corporation, iMerit, Labelbox, Inc., Landing AI, Lionbridge AI, MonkeyLearn Inc., Neurala Inc., Playment Inc., Samasource Inc., Scale AI., Sigma AI, and Webtunix AI.

This market research report on data annotation tools includes in-depth coverage of the industry with estimates & forecast in terms of revenue in USD from 2018 to 2028 for the following segments:

Market, By Data Type

  • Image/video
    • Bounding Box
    • Semantic Annotation
    • Polygon Annotation
    • Lines & Splines
    • Others
  • Text
  • Audio

Market, By Annotation Approach

  • Manual Annotation
  • Automated Annotation

Market, By End-use

  • IT & Telecom
  • BFSI
  • Healthcare
  • Retail
  • Automotive
  • Agriculture
  • Others

The above information has been provided for the following regions and countries:

  • North America
    • U.S.
    • Canada
  • Europe
    • UK
    • Germany
    • France
    • Italy
    • Spain
    • Netherlands
    • Nordics
  • Asia Pacific
    • China
    • India
    • Japan
    • South Korea
    • Australia
    • Singapore
  • Latin America
    • Brazil
    • Mexico
    • Colombia
  • MEA
    • Saudi Arabia
    • UAE
    • South Africa
    • Israel


Authors: Preeti Wadhwani, Smriti Loomba

Frequently Asked Questions (FAQ) :

The market size of data annotation tools surpassed $1 billion in 2021 and is expected to record more than 30% CAGR during 2022-2028, says this GMI report.

The image/video annotation tools segment captured more than 45% share of Germany market in 2021 due to the growing use of data annotation tools to label images and videos and enhance entity recognition.

Manual data annotation tools are likely to generate a revenue of over $400 million in China market by 2028 as manually labelled data is less prone to mistakes given that it is done by highly trained domain experts who are capable of handling complex data labeling scenarios.

Well-known companies, such as Google, Appen, Alegion Inc., AWS, Clickworker GmbH, CloudApp, Inc., Dataturks, Cogito Tech LLC., and IBM Corporation, among many others.

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Premium Report Details

  • Base Year: 2021
  • Companies covered: 23
  • Tables & Figures: 372
  • Countries covered: 22
  • Pages: 322

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