GVR Report cover 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, 2021 - 2028

  • Published Date: May, 2021
  • Base Year for Estimate: 2020
  • Report ID: GVR-2-68038-938-8
  • Format: Electronic (PDF)
  • Historical Data: 2017 - 2019
  • Number of Pages: 101

Report Overview

The global data annotation tools market size was valued at USD 494.0 million in 2020 and is expected to expand at a compound annual growth rate (CAGR) of 27.1% from 2021 to 2028. The growth is majorly driven by the increasing adoption of image data annotation tools in the automotive, retail, and healthcare sectors. The data annotation 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 the rise in the number of large datasets are likely to necessitate the use of artificial intelligence technologies in the field of data annotations.

Asia Pacific data annotation tools market size, by type, 2017 - 2028 (USD Million)

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. Thus, data annotation tools are expected to play a major role in enhancing the applications of AI in the healthcare sector.

For instance, in June 2018, Innodata Inc., a U.S.-based company that offers consulting and business process technology services has announced the launch of managed data annotation and labeling services for its customers in industries including healthcare, financial services, legal, and pharma. The company aims to provide advanced data annotation tools to its clients along with attributes such as high-quality and accurate data annotated, user-friendly, and quick processing time. Further, the solution comprises features such as labeling content for search, building intents, and utterances for conversational agents, mapping data for ontologies, document classification, recommendation engines, and customer insights.

Technologies such as the 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 new economics. These factors have significantly contributed to the growth of the market. Owing to the rising scope of growth in data labeling, companies developing AI-enabled healthcare applications are collaborating with data annotation companies providing the required data sets that can assist them in enhancing their machine learning and deep learning capabilities. For instance, in November 2020, Telus International, a provider of digital customer experience (CX), and digital IT solutions and services announced to acquire Lionbridge AI, which offers training data and annotation platform solutions used for designing AI algorithms to power machine learning. The acquisition is expected to enhance Telus International’s next-generation digital solution portfolio and expand its reach worldwide.

However, the 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 make it difficult to label. The primary challenge faced by the market is issues related to inaccuracy in the quality of data labeled. 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 data annotation tools is improving and thus reducing the dependency on manual annotation and the cost of the tools in the near future.

Type Insights

The text segment dominated the market and accounted for the largest revenue share of over 35.0% in 2020. Based on type, the market is segmented into text, image/video, and audio. The image/video annotation segment is expected to dominate the market over the forecast period. Some of the major applications of image data annotation are in the medical industry in the field of medical imaging. For example, the total investment in startups developing machine learning solutions using medical images reached $522 million by the first half of 2018. Startups such as Infer vision, Zebra Medical Vision, and Arterys are some of the prominent startups within the healthcare sector in the data annotation market.

The text segment is expected to expand at a promising pace over the forecast period, owing to the rising applications in e-commerce and clinical research applications. The audio segment is expected to witness the highest CAGR over the forecast period. For instance, in April 2021, Zoom, a video telephony software, announced the launch of numerous updates to its platforms such as enhanced screen annotation, advanced hardware solutions for zoom rooms, expanded management abilities for zoom chat, and advancement in user experience based on customer feedback. With these updated features, users can highlight text or objects without the need to erase highlighted annotation. Users can make use of a new pen feature named the vanishing pen feature to highlight text or objects.

Annotation Type Insights

The manual segment dominated the market and accounted for the largest revenue share of over 80.0% in 2020. Based on annotation type, the market is categorized into manual, semi-supervised, and automatic. Manual data annotation is a process of labeling or annotating any data by humans. The approach is popular due to its benefits such as accuracy, high level of integrity, minimal data annotation efforts, and a higher chance of discovering intriguing insights pertaining to the data compared to automatic annotation, which can be later integrated into an algorithm. However, as manual annotation can be expensive and time-consuming, labeled data gathered through crowdsourcing activities is used for various applications.

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

Vertical Insights

The IT segment dominated the data annotation tools market and accounted for the largest revenue share of over 30.0% in 2020. Based on vertical, the market has been segmented into IT, automotive, government, healthcare, financial services, retail, and others. The healthcare segment is expected to grow at a good pace 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 data sets in healthcare are required to be trained with 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 data sets is the key step in developing a successful AI-enabled product in the healthcare sector. Thus, data annotation tools drive the development of the sector by providing training data sets to the AI.

Global data annotation tools market share, by vertical, 2020 (%)

The automotive segment is anticipated to grow at the highest rate over the forecast period as data annotation tools find wide acceptance in self-driving vehicles. The growing R&D spending towards improving image annotation for pushing developments in the field of self-driving vehicles is boosting the growth of the market. For instance, in January 2021, TCS announced the launch of an autoscape solution set for autonomous and connected vehicle ecosystem players. It is comprising automotive OEMs, suppliers, start-ups, and fleet owners. The solution addresses technology and business challenge and provides services such as petabyte data collection and analysis, validation, and deployment of algorithms, that offers proper guidance and control autonomous vehicles in the real world. It also provides a data annotation studio and Autonomous Vehicle (AV) validation services. The data annotation studio is a data categorization solution that enhances enterprise workflow by offering cost-effective data organization and model management.

Regional Insights

North America dominated the market and accounted for the largest revenue share of over 35.0% in 2020. This is due to the rapid product and geographical expansion strategy undertaken by market vendors in order to gain an edge in the market. The European market is expected to witness a steady growth pattern over the forecast period. Furthermore, the rising focus on image annotation is anticipated to enhance the operations of retail and automotive verticals in Europe.

In Asia Pacific, the market is anticipated to register the highest CAGR over the forecast period. Emerging economies in the Asia Pacific hold significant potential for the widespread adoption of data annotation tools, particularly in the healthcare and financial services verticals. The growth of the healthcare industry in the region is marked by the increasing adoption of technology and innovative healthcare access programs. These factors are anticipated to boost the demand for image data annotation tools in this region in the near future. For instance, in April 2021, Congenica Ltd, a provider of data analytics tools for annotating and clinically interpreting genomic sequence data, announced a partnership with CamtechDiagnostics, a U.K. based technology company with a specialization in microfluidics. This initiative is expected to expand Congenica’s presence in countries such as Singapore, Malaysia, Japan, and South Korea.

Key Companies & Market Share Insights

Vendors in the market are taking several strategic initiatives, such as collaborations, acquisitions and mergers, and partnerships with other key players in the market. Key vendors in the market are focusing on raising funds for product launches and geographical expansion. For instance, in November 2018, CloudFactoryLimited is a cloud-based platform that offers machine learning, data enrichment services, and data transcription solutions. The company raised its funding worth USD 65 million in its growth equity round, which has brought its total raised amount to USD 78 million. Some of the prominent players in the data annotation tools 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 GMbH

  • Mighty AI, Inc.

  • Trilldata Technologies Pvt Ltd

  • Scale AI, Inc.

  • Google LLC

  • Lionbridge Technologies, Inc

  • SuperAnnotate LLC

Data Annotation Tools Market Report Scope

Report Attribute


Market size value in 2021

USD 629.5 million

Revenue forecast in 2028

USD 3.4 billion

Growth Rate

CAGR of 27.1% from 2021 to 2028

Base year for estimation


Historical data

2017 - 2019

Forecast period

2021 - 2028

Quantitative units

Revenue in USD million and CAGR from 2021 to 2028

Report coverage

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

Segments covered

Type, annotation type, vertical,  region

Regional scope

North America; Europe; Asia Pacific; South America; MEA

Country scope

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

Key companies profiled

Annotate.com; Appen Limited; CloudApp; Cogito Tech LLC; Deep Systems; LabelboxInc; LightTag; Lotus Quality Assurance; PlaymentInc; 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; Google LLC; Lionbridge Technologies, Inc.; SuperAnnotate LLC

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Segments Covered in the Report

This report forecasts revenue growth at global, regional, and country levels and provides an analysis of the latest industry trends in each of the sub-segments from 2017 to 2028. For the purpose of this study, Grand View Research has segmented the global data annotation tools market report on the basis of type, annotation type, vertical, and region:

  • Type Outlook (Revenue, USD Million, 2017 - 2028)

    • Text

    • Image/Video

    • Audio

  • Annotation Type Outlook (Revenue, USD Million, 2017 - 2028)

    • Manual

    • Semi-supervised

    • Automatic

  • Vertical Outlook (Revenue, USD Million, 2017 - 2028)

    • IT

    • Automotive

    • Government

    • Healthcare

    • Financial Services

    • Retail

    • Others

  • Regional Outlook (Revenue, USD Million, 2017 - 2028)

    • North America

      • U.S.

      • Canada

      • Mexico

    • Europe

      • Germany

      • U.K.

      • France

    • Asia Pacific

      • China

      • Japan

      • India

    • South America

      • Brazil

    • Middle East and Africa (MEA)

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