The global data labeling solution and services market size was valued at USD 6.65 billion in 2020 and is expected to expand at a compound annual growth rate (CAGR) of 23.5% from 2021 to 2028. Data labeling tools enable users to enhance data value by adding attribute tags. Data labeling is a practice of recognizing raw data (images, text, videos, etc.) and adding one or more relevant and informative labels to offer context. Machine learning is incorporated in various industries, including robots and drones, automated picture organization of visual websites, and facial recognition on social networking websites powered by data collection. Data labeling solutions and services are gaining traction in the automotive business, particularly for self-driving vehicles. A self-driving vehicle has a variety of sensors and networking devices that let the computer drive the vehicle.
The global data labeling market is expected to witness a surge in the adoption of the technology owing to benefits such as deriving business insights from socially shared photographs and auto-organizing untagged photo collections. Furthermore, data labeling technology is increasingly being used in autonomous vehicles, which is expected to contribute to the significant growth in the automobile industry. With the help of this technology, self-driving cars can detect obstacles and notify the driver about the vicinity of walkways and guardrails. The technology is also capable of reading stoplights and road signs.
Data efficiency is becoming increasingly important as technology evolves, allowing for new business innovations, infrastructure, and economics. These factors have contributed to the expansion of the market. In various data-driven applications, rising demand for machine learning in automated data analytics is predicted to boost demand for autonomous data labeling solutions and services tools. A growing emphasis on picture annotation is likely to improve the operations of the automotive, retail, and healthcare sectors, driving demand for data labeling technologies. The high expenses involved with the manual annotation of complicated photos may limit the market's growth.
The Asia Pacific region is expected to witness the fastest growth during the forecast period. E-commerce and online shopping and a significant reliance on digital platforms for healthcare, retail, and large businesses in developing nations are factors contributing to the growth of the market. China is expected to drive the expansion in the Asia Pacific data labeling market. The government of China has initiated the implementation of real-name registration laws that require residents to link their online accounts to their official government IDs. These policies have increased the usage of data collecting and labeling across the country.
The outsourced segment led the sourcing type segment of the data labeling solution and services market. In 2020, the segment held the largest revenue share of 83.7%. The outsourced segment is expected to account for the largest revenue share and provide solid growth opportunities. The segment is expected to witness the fastest CAGR over the forecast period. Short-term commitments and cost-effectiveness are priorities for outsourcing organizations. Outsourced companies assist organizations in achieving a flexible approach to developing annotative capacity, solid security protocols, and consulting practice for their labeling needs.
The in-house segment is estimated to witness moderate growth throughout the forecast period. Implementation of in-house data labeling solutions empowers businesses to develop reliable labeling processes and replicable systems for managing data. The companies can also set up custom practices according to the desires and requirements of the company. Moreover, positioning in-house data labeling teams provides a deeper understanding and improved control of operational procedures, which will profit the organizational viewpoint. These factors are expected to contribute to the growth of the segment.
The text segment led the market and accounted for the largest revenue share of over 37.0% in 2020. However, the image/ video segment will dominate the market over the forecast period. The high revenue share of the segment can be ascribed to the growing use of computer vision in various industries, including healthcare, automotive, media, and entertainment. For instance, medical imaging is one of the significant image labeling applications.
Increased use of advanced technology is anticipated to further fuel the growth of the image/video segment. The growing use of computer applications in the healthcare industry for x-ray, CT scans, MRI, and patient treatments will also propel the growth. The text segment accounted for a significant revenue share in 2020, owing to its rising applications in clinical research and e-commerce. Over the projected period, the audio segment is expected to witness the highest CAGR.
In 2020, the manual segment dominated the market, with over 82.0% revenue share. The market is divided into manual, semi-supervised, and automatic annotation types. The process of humans categorizing or annotating any data is known as manual data annotation. Compared to automatic annotation, the method is appealing because of benefits such as consistency, high integrity, and low data annotation efforts. However, because manual annotation is costly and time-consuming, labeled data collected through crowdsourcing activities are used for various purposes.
Over the projected period, the automatic annotation segment is expected to expand at a favorable CAGR. AI is becoming increasingly important in the data labeling sector as it enables the extraction of high-level and sophisticated abstractions from datasets through a hierarchical learning process. The demand is likely to increase as the necessity for mining and extracting meaningful patterns from large amounts of data grows. Semi-supervised systems can classify unlabeled data or identify specific labeled data. As a result of the restricted use of this annotation type, it will have a moderate market share.
In 2020, the IT segment dominated the market with a 33.7 % revenue share, due to the widespread use of AI applications in the sector. The healthcare business is expected to increase significantly during the projection period. Artificial intelligence is widely employed in the healthcare industry for various applications, including diagnostic automation, gene sequencing, treatment prediction, medication discovery, deep learning, and machine learning methods to train datasets. Since highly accurate data labeling is required for efficient AI-based applications, it directly impacts its growth.
Over the projected period, the automotive segment is expected to register the fastest CAGR of 25.2%. Data labeling technology is increasingly being used in autonomous vehicles, which is expected to contribute to the substantial growth in the automotive segment. With the help of data labeling technology, self-driving vehicles can detect barriers and notify the driver about the vicinity of pathways and guardrails. The technology is also capable of reading stoplights and road signs. All these factors are anticipated to contribute to the growth of the segment over the forecast period.
In 2020, North America led the market with a revenue share of over 35.0%. Increasing investments in North American companies for AI solutions and services have spurred the demand. Early adopters in the markets, such as the U.S. and Canada, are the frontiers of data labeling solutions and services. On the other hand, the Europe regional market is anticipated to witness steady growth during the forecast period. In addition, increasing developments in automotive obstacle detection technologies are expected to fuel the growth of Europe's automobile sector over the forecast period.
Asia Pacific is anticipated to expand at a CAGR of 25.2% over the forecast period, attributable to the rapidly increasing consumption of mobiles and tablets, swift technological advancements, and the increasing prominence of social networking in developing economies, such as India and China. For instance, the Chinese government has imposed real-name registering policies across the country, under which inhabitants should mandatorily link their official government ID with an online account. Such policies are augmenting the use of data labeling solutions across the country.
The competitive landscape of the market is fragmented and features the presence of several market players. The market has witnessed several mergers, acquisitions, and strategic partnerships in recent years. For instance, in March 2019, Appen Limited acquired Figure Eight Inc., a U.S.-based AI-focused company. This acquisition was anticipated to bring data annotation expertise to the company. In May 2020, Labelbox, Inc. partnered with Carahsoft Technology Corp., a U.S.-based company providing IT solutions to the government. The partnership speeds up the AI training data platform development for the intelligence community and federal agencies. Some of the prominent players operating in the global data labeling solution and services market are:
Alegion
Amazon Mechanical Turk, Inc.
Appen Limited
Clickworker GmbH
CloudApp
CloudFactory Limited
Cogito Tech LLC
Crowdworks, Inc.
Deep Systems, LLC
edgecase.ai
Explosion AI GmbH
Heex Technologies
Labelbox, Inc
Lotus Quality Assurance
Mighty AI, Inc.
Playment Inc.
Scale AI
Shaip
Steldia Services Ltd.
Tagtog Sp. z o.o.
Trilldata Technologies Pvt Ltd
Yandez LLC
Report Attribute |
Details |
Market size value in 2021 |
USD 8.68 billion |
Revenue forecast in 2028 |
USD 38.11 billion |
Growth Rate |
CAGR of 23.5% from 2021 to 2028 |
Base year for estimation |
2020 |
Historical data |
2018 - 2028 |
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 |
Segment Scope |
Sourcing type, type, annotation type,vertical, region |
Region 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 |
Alegion; Amazon Mechanical Turk, Inc.; Appen Limited; Clickworker GmbH; CloudApp; CloudFactory Limited; Cogito Tech LLC; Crowdworks, Inc.; Deep Systems, LLC; edgecase.ai; Explosion AI GmbH; Heex Technologies; Labelbox, Inc; Lotus Quality Assurance; Mighty AI, Inc.; Playment Inc.; Scale AI; Shaip; Steldia Services Ltd.; Tagtog Sp. z o.o.; Trilldata Technologies Pvt Ltd;Yandez 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 provides forecasts for revenue growth at the global, regional, and country levels and an analysis of the latest industry trends and opportunities in each of the sub-segments from 2018 to 2028. For this study, Grand View Research has segmented the global data labeling solution and services market report based on sourcing type, type, annotation type, vertical, and region:
Sourcing Type Outlook (Revenue, USD Million, 2018 - 2028)
In-House
Outsourced
Type Outlook (Revenue, USD Million, 2018 - 2028)
Text
Image/Video
Audio
Labeling Type Outlook (Revenue, USD Million, 2018 - 2028)
Manual
Semi-supervised
Automatic
Vertical Outlook (Revenue, USD Million, 2018 - 2028)
IT
Automotive
Government
Healthcare
Financial Services
Retails
Others
Regional Outlook (Revenue, USD Million, 2018 - 2028)
North America
U.S.
Canada
Mexico
Europe
U.K.
Germany
France
Asia Pacific
China
Japan
India
South America
Brazil
Middle East and Africa (MEA)
b. Some key players operating in the data labeling solution and services market include Alegion; Amazon Mechanical Turk, Inc.; Appen Limited; Clickworker GmbH; CloudApp; CloudFactory Limited; Cogito Tech LLC; Deep Systems, LLC; edgecase.ai; Explosion AI GmbH; Heex Technologies; Labelbox, Inc; Lotus Quality Assurance; Mighty AI, Inc.; Playment Inc.; Scale AI; Shaip; Steldia Services Ltd.; Tagtog Sp. z o.o.; Trilldata Technologies Pvt Ltd.;Yandez LLC.
b. Key factors that are driving the data labeling solution and services market growth include the emergence of data labeling tools and workflow trends, the increasing prominence of AI and machine learning, and accelerated medical data labeling for diagnostic AI.
b. The global data labeling solution and services market size was estimated at USD 6.65 billion in 2020 and is expected to reach USD 8.68 billion in 2021.
b. The global data labeling solution and services market is expected to grow at a compound annual growth rate of 23.5% from 2021 to 2028 to reach USD 38.11 billion by 2028.
b. North America dominated the data labeling solution and services market with a share of 36.1% in 2020. This is attributable to the mass adoption of digital devices, and increasing investments in North American companies for AI solutions and services.
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