The global data annotation tools market size was valued at USD 805.6 million in 2022 and is anticipated to expand at a compound annual growth rate (CAGR) of 26.5% from 2023 to 2030. 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 surge in the number of large datasets are likely to necessitate the use of artificial intelligence technologies in the field of data annotations. The data annotation industry is also expected to have benefited from the rising demands for improvements in machine learning as well as in the rising investment in advanced autonomous driving technology.
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 scans, 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 is expected to play a major role in enhancing the applications of AI in the healthcare sector. For instance, in March 2021, Innodata Inc., a U.S.-based company, announced its expansion of AI data annotation tools capabilities to include the medical reports of the patients. Innodata has established plans to synthesize its capabilities from the AI Data annotation tools platform and Synodex medical data extraction platform, to create a medical record data annotation platform. Via this, high-quality AI training data will be created that is likely to carry HIPAA compliance and follow all the security protocols.
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 industry. Owing to the rising scope of growth in data labeling, companies developing AI-enabled healthcare applications are collaborating with data annotation companies to provide 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 & 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 include multiple objects, making 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.
The text segment led the market in 2022, accounting for over 36% share of the global revenue. 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 Infervision, Zebra Medical Vision, and Arteries are some of the prominent startups within the healthcare sector in the data annotation market.
The text annotation 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. Text annotation will dominate the global market owing to the need to fine-tune the capacity of AI so that it can help recognize patterns in the text, voices, and semantic connections of the annotated data. The audio segment is expected to cater moderate share in the market. 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 annotations. Users can make use of a new pen feature named the vanishing pen feature to highlight text or objects.
The manual segment led the market in 2022, accounting for over 81% share of the global revenue. 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 a moderate share in the market.
The IT segment led the market in 2022, accounting for a 32% share of the global revenue. Based on verticals, 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.
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 market growth. For instance, in January 2021, TCS announced the launch of an autoscape solution set for autonomous and connected vehicle ecosystem players. It is composed of automotive OEMs, suppliers, start-ups, and fleet owners. The solution addresses technology & business challenges and provides services such as petabyte data collection & analysis, validation, and deployment of algorithms, that offer proper guidance and control of 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.
North America dominated the market in 2022, accounting for over 36% share of the global revenue. 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 the European region.
The Asia Pacific market is anticipated to register the highest CAGR over the forecast period. Emerging economies in the Asia Pacific region 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 Asia Pacific 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 Camtech Diagnostics, 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.
Vendors in the market are taking several strategic initiatives, such as collaborations, acquisitions & mergers, and partnerships with other key players in the market. Moreover, these players are focusing on raising funds to support geographical expansion and product launches. For instance, in November 2018, CloudFactory Limited- a cloud-based platform that offers machine learning, data enrichment services, and data transcription solutions raised funding worth USD 65 million in its growth equity round, thus equating its total raised the amount to USD 78 million. Some of the prominent players in the global 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
Report Attribute |
Details |
Market size value in 2023 |
USD 1,029.6 million |
Revenue forecast in 2030 |
USD 5,331 million |
Growth Rate |
CAGR of 26.5% from 2023 to 2030 |
Base year for estimation |
2022 |
Historical data |
2017 - 2021 |
Forecast period |
2023 - 2030 |
Quantitative units |
Revenue in USD million and CAGR from 2023 to 2030 |
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; 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; Google LLC. |
Customization scope |
Free report customization (equivalent up to 8 analysts working days) with purchase. Addition or alteration to country, regional & segment scope. |
Pricing and purchase options |
Avail customized purchase options to meet your exact research needs. Explore purchase options |
This report forecasts revenue growth at the global, regional, and country levels and provides an analysis of the latest industry trends in each of the sub-segments from 2017 to 2030. For 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, 2017 - 2030)
Text
Image/Video
Audio
Annotation Type Outlook (Revenue, USD Million, 2017 - 2030)
Manual
Semi-supervised
Automatic
Vertical Outlook (Revenue, USD Million, 2017 - 2030)
IT
Automotive
Government
Healthcare
Financial Services
Retail
Others
Regional Outlook (Revenue, USD Million, 2017 - 2030)
North America
U.S.
Canada
Mexico
Europe
Germany
U.K.
France
Asia Pacific
China
Japan
India
South America
Brazil
Middle East and Africa (MEA)
b. The global data annotation tools market size was estimated at USD 805.6 million in 2022 and is expected to reach USD 1,029.6 million in 2023.
b. The global data annotation tools market is expected to grow at a compound annual growth rate of 26.5% from 2023 to 2030 to reach USD 5,331.0 million by 2030.
b. North America dominated the data annotation tools market and accounted for the largest revenue share of over 36.8% in 2022.
b. Some key players operating in the data annotation tools market include Appen Limited; Cogito Tech LLC; Deep Systems; Labelbox, Inc.; LightTag; Playment Inc.; CloudFactory Limited; Clickworker GmbH; Alegion; Figure Eight Inc.; Amazon Mechanical Turk, Inc.; amongst others.
b. Key factors that are driving the data annotation tools market growth include the growing need to make text/image more interactive and engaging, rapid penetration of AI and machine learning, and growing R&D spending on the development of self-driving vehicles.
b. The text segment dominated the data annotation tools market and accounted for the largest revenue share of over 36.4% in 2022.
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