Data Labeling Solution And Services Market Size Report, 2022-2030
The global Data Labeling Solution and Services market size was valued at USD 6.8 billion in 2021, and is predicted to be worth around USD 41.10 billion by 2030, registering a CAGR of 23.9% during the forecast period 2022 to 2030.
Growth Factors:
The rising popularity of data labeling solutions and services in the automotive industry, combined with autonomous vehicles that contain numerous sensors and networking systems that assist the computer driving the car, is propelling the growth of the market.
The market is driven by increased public awareness about digitalization, healthcare treatments, and technological advancements. The demand for data labeling is growing due to technology improvements in large enterprises from the industries such as automotive and healthcare. For example, Waymo LLC, Lyft, Inc., Zoox, and Toyota Research Institute have all used data labeling services provided by Scale AI, Inc., a digital start-up based in the United States.
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.
With the increasing execution of Electronic Health Record (EHR) systems-the collection of clinical data, particularly unstructured text documents-has become a valuable resource for clinical research. Statistical Natural Language Processing (NLP) standards have been designed to unlock data embedded in clinical text. With developments in sentiment analysis, text labeling is also widely utilized in social media monitoring to build recommendation systems.
Report Coverage
| Report Scope | Details |
| Market Size | USD 41.10 billion by 2030 |
| Growth Rate | CAGR of 23.9% From 2022 to 2030 |
| Base Year | 2021 |
| Forecast Period | 2022 to 2030 |
| Report coverage | Growth Factors, Revenue Status, Competitive Landscape, and Future Trends |
| Segments Covered | Sourcing Type, Type, Annotation Type,Vertical, Region |
| Regional Scope | North America, Europe, Asia Pacific, Latin America, Middle East & Africa (MEA) |
| Companies Mentioned | 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 |
By Sourcing type Analysis
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.
By Type Analysis
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.
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.
By Annotation Type Analysis
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.
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.
By Vertical Analysis
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.
By Regional Analysis
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.
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.
Competitive Rivalry
Foremost players in the market are attentive on adopting corporation strategies to enhance their market share. Some of the prominent tactics undertaken by leading market participants in order to sustain the fierce market completion include collaborations, acquisitions, substantial spending in R&D and the improvement of new-fangled products or reforms among others.
Major manufacturers & their revenues, percentage splits, market shares, growth rates and breakdowns of the product markets are determined through secondary sources and verified through the primary sources.
Some of the prominent players in the Data Labeling Solution And Services Market include:
Segments Covered in the Report
This research report offers market revenue, sales volume, production assessment and prognoses by classifying it on the basis of various aspects. Further, this research study investigates market size, production, consumption and its development trends at global, regional, and country level for the period of 2017 to 2030 and covers subsequent region in its scope:
Market Segmentation
By Geography
North America
Europe
Asia Pacific
Latin America
Middle East & Africa (MEA)
Research Methodology
In the study, a unique research methodology is utilized to conduct extensive research on the growth of the Data Labeling Solution And Services market, and reach conclusions on the future growth parameters of the market. This research methodology is a combination of primary and secondary research, which helps analysts ensure the accuracy and reliability of the conclusions.
Secondary resources referred to by analysts during the production of the Data Labeling Solution And Services market study are as follows - statistics from government organizations, trade journals, white papers, and internal and external proprietary databases. Analysts have also interviewed senior managers, product portfolio managers, CEOs, VPs, marketing/product managers, and market intelligence managers, all of whom have contributed to the development of this report as a primary resource.
Comprehensive information acquired from primary and secondary resources acts as a validation from companies in the market, and makes the projections on the growth prospects of the Data Labeling Solution And Services markets more accurate and reliable.
Secondary Research
It involves company databases such as Hoover's: This assists us recognize financial information, structure of the market participants and industry competitive landscape.
The secondary research sources referred in the process are as follows:
Primary Research
Primary research includes face-to face interviews, online surveys, and telephonic interviews.
Industry participants involved in this research study include:
Key Points Covered in Data Labeling Solution And Services Market Study:
Chapter 1. Introduction
1.1. Research Objective
1.2. Scope of the Study
1.3. Definition
Chapter 2. Research Methodology
2.1. Research Approach
2.2. Data Sources
2.3. Assumptions & Limitations
Chapter 3. Executive Summary
3.1. Market Snapshot
Chapter 4. Market Variables and Scope
4.1. Introduction
4.2. Market Classification and Scope
4.3. Industry Value Chain Analysis
4.3.1. Raw Material Procurement Analysis
4.3.2. Sales and Labeling Type Analysis
4.3.3. Downstream Buyer Analysis
Chapter 5. Market Dynamics Analysis and Trends
5.1. Market Dynamics
5.1.1. Market Drivers
5.1.2. Market Restraints
5.1.3. Market Opportunities
5.2. Porter’s Five Forces Analysis
5.2.1. Bargaining power of suppliers
5.2.2. Bargaining power of buyers
5.2.3. Threat of substitute
5.2.4. Threat of new entrants
5.2.5. Degree of competition
Chapter 6. Competitive Landscape
6.1.1. Company Market Share/Positioning Analysis
6.1.2. Key Strategies Adopted by Players
6.1.3. Vendor Landscape
6.1.3.1. List of Suppliers
6.1.3.2. List of Buyers
Chapter 7. Global Data Labeling Solution And Services Market, By Sourcing Type
7.1. Data Labeling Solution And Services Market, by Sourcing Type, 2021-2030
7.1.1. In-House
7.1.1.1. Market Revenue and Forecast (2019-2030)
7.1.2. Outsourced
7.1.2.1. Market Revenue and Forecast (2019-2030)
Chapter 8. Global Data Labeling Solution And Services Market, By Type
8.1. Data Labeling Solution And Services Market, by Type, 2021-2030
8.1.1. Text
8.1.1.1. Market Revenue and Forecast (2019-2030)
8.1.2. Image/Video
8.1.2.1. Market Revenue and Forecast (2019-2030)
8.1.3. Audio
8.1.3.1. Market Revenue and Forecast (2019-2030)
Chapter 9. Global Data Labeling Solution And Services Market, By Labeling Type
9.1. Data Labeling Solution And Services Market, by Labeling Type, 2021-2030
9.1.1. Manual
9.1.1.1. Market Revenue and Forecast (2019-2030)
9.1.2. Semi-supervised
9.1.2.1. Market Revenue and Forecast (2019-2030)
9.1.3. Automatic
9.1.3.1. Market Revenue and Forecast (2019-2030)
Chapter 10. Global Data Labeling Solution And Services Market, By Vertical
10.1. Data Labeling Solution And Services Market, by Vertical, 2021-2030
10.1.1. IT
10.1.1.1. Market Revenue and Forecast (2019-2030)
10.1.2. Automotive
10.1.2.1. Market Revenue and Forecast (2019-2030)
10.1.3. Government
10.1.3.1. Market Revenue and Forecast (2019-2030)
10.1.4. Healthcare
10.1.4.1. Market Revenue and Forecast (2019-2030)
10.1.5. Financial Services
10.1.5.1. Market Revenue and Forecast (2019-2030)
10.1.6. Retails
10.1.6.1. Market Revenue and Forecast (2019-2030)
Chapter 11. Global Data Labeling Solution And Services Market, Regional Estimates and Trend Forecast
11.1. North America
11.1.1. Market Revenue and Forecast, by Sourcing Type (2019-2030)
11.1.2. Market Revenue and Forecast, by Type (2019-2030)
11.1.3. Market Revenue and Forecast, by Labeling Type (2019-2030)
11.1.4. Market Revenue and Forecast, by Vertical (2019-2030)
11.1.5. U.S.
11.1.5.1. Market Revenue and Forecast, by Sourcing Type (2019-2030)
11.1.5.2. Market Revenue and Forecast, by Type (2019-2030)
11.1.5.3. Market Revenue and Forecast, by Labeling Type (2019-2030)
11.1.5.4. Market Revenue and Forecast, by Vertical (2019-2030)
11.1.6. Rest of North America
11.1.6.1. Market Revenue and Forecast, by Sourcing Type (2019-2030)
11.1.6.2. Market Revenue and Forecast, by Type (2019-2030)
11.1.6.3. Market Revenue and Forecast, by Labeling Type (2019-2030)
11.1.6.4. Market Revenue and Forecast, by Vertical (2019-2030)
11.2. Europe
11.2.1. Market Revenue and Forecast, by Sourcing Type (2019-2030)
11.2.2. Market Revenue and Forecast, by Type (2019-2030)
11.2.3. Market Revenue and Forecast, by Labeling Type (2019-2030)
11.2.4. Market Revenue and Forecast, by Vertical (2019-2030)
11.2.5. UK
11.2.5.1. Market Revenue and Forecast, by Sourcing Type (2019-2030)
11.2.5.2. Market Revenue and Forecast, by Type (2019-2030)
11.2.5.3. Market Revenue and Forecast, by Labeling Type (2019-2030)
11.2.5.4. Market Revenue and Forecast, by Vertical (2019-2030)
11.2.6. Germany
11.2.6.1. Market Revenue and Forecast, by Sourcing Type (2019-2030)
11.2.6.2. Market Revenue and Forecast, by Type (2019-2030)
11.2.6.3. Market Revenue and Forecast, by Labeling Type (2019-2030)
11.2.6.4. Market Revenue and Forecast, by Vertical (2019-2030)
11.2.7. France
11.2.7.1. Market Revenue and Forecast, by Sourcing Type (2019-2030)
11.2.7.2. Market Revenue and Forecast, by Type (2019-2030)
11.2.7.3. Market Revenue and Forecast, by Labeling Type (2019-2030)
11.2.7.4. Market Revenue and Forecast, by Vertical (2019-2030)
11.2.8. Rest of Europe
11.2.8.1. Market Revenue and Forecast, by Sourcing Type (2019-2030)
11.2.8.2. Market Revenue and Forecast, by Type (2019-2030)
11.2.8.3. Market Revenue and Forecast, by Labeling Type (2019-2030)
11.2.8.4. Market Revenue and Forecast, by Vertical (2019-2030)
11.3. APAC
11.3.1. Market Revenue and Forecast, by Sourcing Type (2019-2030)
11.3.2. Market Revenue and Forecast, by Type (2019-2030)
11.3.3. Market Revenue and Forecast, by Labeling Type (2019-2030)
11.3.4. Market Revenue and Forecast, by Vertical (2019-2030)
11.3.5. India
11.3.5.1. Market Revenue and Forecast, by Sourcing Type (2019-2030)
11.3.5.2. Market Revenue and Forecast, by Type (2019-2030)
11.3.5.3. Market Revenue and Forecast, by Labeling Type (2019-2030)
11.3.5.4. Market Revenue and Forecast, by Vertical (2019-2030)
11.3.6. China
11.3.6.1. Market Revenue and Forecast, by Sourcing Type (2019-2030)
11.3.6.2. Market Revenue and Forecast, by Type (2019-2030)
11.3.6.3. Market Revenue and Forecast, by Labeling Type (2019-2030)
11.3.6.4. Market Revenue and Forecast, by Vertical (2019-2030)
11.3.7. Japan
11.3.7.1. Market Revenue and Forecast, by Sourcing Type (2019-2030)
11.3.7.2. Market Revenue and Forecast, by Type (2019-2030)
11.3.7.3. Market Revenue and Forecast, by Labeling Type (2019-2030)
11.3.7.4. Market Revenue and Forecast, by Vertical (2019-2030)
11.3.8. Rest of APAC
11.3.8.1. Market Revenue and Forecast, by Sourcing Type (2019-2030)
11.3.8.2. Market Revenue and Forecast, by Type (2019-2030)
11.3.8.3. Market Revenue and Forecast, by Labeling Type (2019-2030)
11.3.8.4. Market Revenue and Forecast, by Vertical (2019-2030)
11.4. MEA
11.4.1. Market Revenue and Forecast, by Sourcing Type (2019-2030)
11.4.2. Market Revenue and Forecast, by Type (2019-2030)
11.4.3. Market Revenue and Forecast, by Labeling Type (2019-2030)
11.4.4. Market Revenue and Forecast, by Vertical (2019-2030)
11.4.5. GCC
11.4.5.1. Market Revenue and Forecast, by Sourcing Type (2019-2030)
11.4.5.2. Market Revenue and Forecast, by Type (2019-2030)
11.4.5.3. Market Revenue and Forecast, by Labeling Type (2019-2030)
11.4.5.4. Market Revenue and Forecast, by Vertical (2019-2030)
11.4.6. North Africa
11.4.6.1. Market Revenue and Forecast, by Sourcing Type (2019-2030)
11.4.6.2. Market Revenue and Forecast, by Type (2019-2030)
11.4.6.3. Market Revenue and Forecast, by Labeling Type (2019-2030)
11.4.6.4. Market Revenue and Forecast, by Vertical (2019-2030)
11.4.7. South Africa
11.4.7.1. Market Revenue and Forecast, by Sourcing Type (2019-2030)
11.4.7.2. Market Revenue and Forecast, by Type (2019-2030)
11.4.7.3. Market Revenue and Forecast, by Labeling Type (2019-2030)
11.4.7.4. Market Revenue and Forecast, by Vertical (2019-2030)
11.4.8. Rest of MEA
11.4.8.1. Market Revenue and Forecast, by Sourcing Type (2019-2030)
11.4.8.2. Market Revenue and Forecast, by Type (2019-2030)
11.4.8.3. Market Revenue and Forecast, by Labeling Type (2019-2030)
11.4.8.4. Market Revenue and Forecast, by Vertical (2019-2030)
11.5. Latin America
11.5.1. Market Revenue and Forecast, by Sourcing Type (2019-2030)
11.5.2. Market Revenue and Forecast, by Type (2019-2030)
11.5.3. Market Revenue and Forecast, by Labeling Type (2019-2030)
11.5.4. Market Revenue and Forecast, by Vertical (2019-2030)
11.5.5. Brazil
11.5.5.1. Market Revenue and Forecast, by Sourcing Type (2019-2030)
11.5.5.2. Market Revenue and Forecast, by Type (2019-2030)
11.5.5.3. Market Revenue and Forecast, by Labeling Type (2019-2030)
11.5.5.4. Market Revenue and Forecast, by Vertical (2019-2030)
11.5.6. Rest of LATAM
11.5.6.1. Market Revenue and Forecast, by Sourcing Type (2019-2030)
11.5.6.2. Market Revenue and Forecast, by Type (2019-2030)
11.5.6.3. Market Revenue and Forecast, by Labeling Type (2019-2030)
11.5.6.4. Market Revenue and Forecast, by Vertical (2019-2030)
Chapter 12. Company Profiles
12.1. Alegion
12.1.1. Company Overview
12.1.2. Sourcing Type Offerings
12.1.3. Financial Performance
12.1.4. Recent Initiatives
12.2. Amazon Mechanical Turk, Inc.
12.2.1. Company Overview
12.2.2. Sourcing Offerings
12.2.3. Financial Performance
12.2.4. Recent Initiatives
12.3. Appen Limited
12.3.1. Company Overview
12.3.2. Sourcing Offerings
12.3.3. Financial Performance
12.3.4. Recent Initiatives
12.4. Clickworker GmbH
12.4.1. Company Overview
12.4.2. Sourcing Offerings
12.4.3. Financial Performance
12.4.4. Recent Initiatives
12.5. CloudApp
12.5.1. Company Overview
12.5.2. Sourcing Offerings
12.5.3. Financial Performance
12.5.4. Recent Initiatives
12.6. CloudFactory Limited
12.6.1. Company Overview
12.6.2. Sourcing Offerings
12.6.3. Financial Performance
12.6.4. Recent Initiatives
12.7. Cogito Tech LLC
12.7.1. Company Overview
12.7.2. Sourcing Offerings
12.7.3. Financial Performance
12.7.4. Recent Initiatives
12.8. Crowdworks, Inc.
12.8.1. Company Overview
12.8.2. Sourcing Offerings
12.8.3. Financial Performance
12.8.4. Recent Initiatives
12.9. Deep Systems, LLC
12.9.1. Company Overview
12.9.2. Sourcing Offerings
12.9.3. Financial Performance
12.9.4. Recent Initiatives
12.10. edgecase.ai
12.10.1. Company Overview
12.10.2. Sourcing Offerings
12.10.3. Financial Performance
12.10.4. Recent Initiatives
Chapter 13. Research Methodology
13.1. Primary Research
13.2. Secondary Research
13.3. Assumptions
Chapter 14. Appendix
14.1. About Us
Glossary of Terms
Cross-segment Market Size and Analysis for
Mentioned Segments
Additional Company Profiles (Upto 5 With No Cost)
Additional Countries (Apart From Mentioned Countries)
Country/Region-specific Report
Go To Market Strategy
Region Specific Market DynamicsRegion Level Market Share Import Export AnalysisProduction AnalysisOthers