Data Annotation Tools Market - Historic Data (2019-2024), Global Trends 2025, Growth Forecasts 2037
Data Annotation Tools Market in 2025 is assessed at USD 1.91 billion. The global Market size was worth around USD 1.58 billion in 2024 and is set to register a CAGR of more than 26.2%, exceeding USD 32.54 billion revenue by 2037. North America is on pace to record USD 9.76 billion by 2037, fueled by rising IoT device adoption and AI integration in healthcare.
The growth of the market can be attributed to the rising production of data, such as videos and photos. In order to train ML models, more information/metadata is added to various data kinds, such as text, audio, image, and video, using a data annotation tool. More than 3 billion photographs and around 720,000 hours of video are shared every day on social media, worldwide.
In addition to these, factors that are believed to fuel the data annotation tools market growth include the rise in advanced technologies, such as AI, ML, robotics, and others. Advanced technologies such as industrial robots are mostly propelled by high-quality data annotation. It is common to practice using labeled data for tasks such as developing and testing computer vision (CV) models for robotic navigation systems. In companies all around the world, there are now a record-breaking 2.7 million industrial robots at work, up 12% from the previous year, according to the new World Robotics 2020 Industrial Robots research published by the International Federation of Robotics. Moreover, there was a worldwide shipment of 373,000 units in 2019. Furthermore, the rising use of data annotation in machine learning is also anticipated to augment the market growth. In machine learning projects all across the world , more than 80% of the engineering labor is devoted to data preparation and labeling. Additionally, by 2024, the market for third-party data annotation is expected to nearly triple.
Data Annotation Tools Sector: Growth Drivers and Challenges
Growth Drivers
- Growing Demand for Smart Autonomous Driving Technology– It takes a lot of annotated picture and video data to construct an autonomous vehicle and address all safety concerns. This allows the self-driving system to be trained to recognize objects. Almost 1.4 million vehicles sold globally in 2019 had at least Level 3 autonomy. Between 2019 and 2030, sales of autonomous vehicles are anticipated to increase. Moreover, the expected value of these cars' global sales in 2030 is around 58 million units.
- Rising Use of Artificial Intelligence– Data labeling enables the AI to handle all projects accurately and improves its capabilities. AI is used by about 37% of companies and organizations across the globe. In addition, nearly Investments in AI technologies are made by nine out of ten top companies.
- Massive Generation of Data –Data labeling enables the identification of objectives in raw data forms. The total amount of data in the globe was predicted to be over 40 zettabytes in 2020. According to the most recent estimates, more than 4 billion people use the internet daily, producing around 3 quintillion bytes of data.
- Rise in the Number of Devices Connected to IOT– With the rise in IoT-connected devices, production, and consumption have increased rapidly, and these data can be turned into a value with the use of a data annotation tool. IoT devices are predicted to number around 25 billion by 2030, all across the world. There are currently around 400 IoT platforms in use. Moreover, by 2025, there may be 27 billion connected IoT devices.
- Growing Popularity of Facial Recognition–The foundation for facial and emotional identification is high-quality facial annotation. For facial recognition algorithms to work properly, the accuracy and quality of video and image annotation are important. Globally around 96 million mobile devices had facial recognition hardware installed as of 2019. Yet, around 1 billion devices, worldwide are expected to have software-based facial recognition solutions by 2024.
Challenges
- Inaccuracy in data labeling owing to low-quality content - Doing a data annotation project was thought to present the biggest barrier in terms of data quality. High data quality must be maintained throughout the annotation process, which requires consistency. The quality of machine learning model's overall accuracy may be impacted by biased estimates caused by poor data quality. Inconsistency can also cause difficulties in the review process and in communication.
- Risk of data breaches
- Lack of enough skilled workers to train the huge amount of data
Data Annotation Tools Market: Key Insights
| Report Attribute | Details |
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Base Year |
2024 |
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Forecast Year |
2025-2037 |
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CAGR |
26.2% |
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Base Year Market Size (2024) |
USD 1.58 billion |
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Forecast Year Market Size (2037) |
USD 32.54 billion |
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Regional Scope |
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Data Annotation Tools Segmentation
End-user (Retail & E-Commerce, IT & Telecommunication, BFSI, Government, Automotive, Healthcare)
The retail & e-commerce segment is estimated to gain the largest data annotation tools market share in the year 2037. The growth of the segment can be attributed to the increasing prevalence of e-commerce and the rising integration of artificial intelligence in retail & e-commerce. According to a survey conducted in October 2020, around 70% of e-commerce decision-makers in North America and Europe said AI would aid personalization in their companies' operations in 2021. For both retailers and customers, AI & Data annotation services are greatly enhancing online shopping experiences. Companies witnessed a transformation in the e-commerce industry's adoption of AI and data annotation during the last few years. Therefore, for a better user experience and more effective solutions, several companies already utilize AI with data annotation services.
Type (Text, Pictures & Videos, Audio)
The text segment is expected to garner a significant share in the year 2037. Text is the most often used data type. In around 70% of businesses, the text is used. A wide variety of annotations, including sentiment, intent, and inquiry, are included in text annotations. The growth of the segment is primarily attributed to the rising use of annotation in data labeling. The labeling is used (Natural Language Processing) NLP technologies, automatic question-and-answer (Q&A) platforms, intelligent chatbots, sentiment analysis, and others. Therefore, the rising use of chatbots and text analytics based cloud NLP technologies is also expected to boost segment growth. Chatbot adoption as a brand communication channel has increased by around 92% globally since 2019. Almost 25% of customers interacted with businesses through chatbots in 2020, up from just under 13% in 2019.
Our in-depth analysis of the global market includes the following segments:
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By Type |
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By Component |
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By Annotation Type |
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By End User |
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Vishnu Nair
Head - Global Business DevelopmentCustomize this report to your requirements — connect with our consultant for personalized insights and options.
Data Annotation Tools Industry - Regional Synopsis
North American Market Forecast
The data annotation tools market in North America is projected to be the largest with a share of about 30% by the end of 2037. The growth of the market can be attributed majorly to the increasing number of devices connected to the Internet of Things (IoT). In 2022, there were nearly 3 billion connected IoT devices in North America, and this number is expected to rise to more than 6 billion devices by 2030. On the other hand, the rising adoption of AI in healthcare is also expected to boost market growth. In a poll of US healthcare executives, around 41% said that as of 2021, their use of AI had reached a fully functional level. Another nearly 26% claimed that their AI system is partially working.
APAC Market Statistics
The Asia Pacific data annotation tools market is estimated to be the second largest, registering a share of about 28% by the end of 2037. The growth of the market can be attributed majorly to the rising penetration of the internet, which in turn is expected to expand data generation. India adds up to 25 million new smartphone users every three months and has the highest mobile data usage rate in the world at around 12 gigabytes (GB) per user per month. In addition to this, China produced around 8 trillion gigabytes of data in 2018. That sum is anticipated to increase to around 49 trillion gigabytes by 2025. Furthermore, rising demand for autonomous cars in the region is also expected to augment the data annotation tools market growth. To promote modern mobility services, the Japanese government intends to utilize autonomous driving vehicles in more than 40 areas nationwide by 2025.
Europe Market Forecast
Europe region is expected to observe significant growth till 2037. The growth of the market can be attributed majorly to the rising adoption of facial recognition technologies. Furthermore, face recognition has quickly transformed from a cutting-edge curiosity to an essential component of daily life. Technologies for facial recognition are developing quickly, and algorithms are getting better every day. In 11 European nations, law enforcement agencies already use biometric identification systems in their investigations. Moreover, facial recognition technology is used by police for former identification during criminal investigations in France, Germany, Greece, Hungary, Italy, Austria, Finland, France, and other regions.
Companies Dominating the Data Annotation Tools Landscape
- Innodata, Inc.
- Company Overview
- Business Strategy
- Key Product Offerings
- Financial Performance
- Key Performance Indicators
- Risk Analysis
- Recent Development
- Regional Presence
- SWOT Analysis
- Telus Corporation
- Figure Eight Federal Inc.
- Google LLC
- Lighttag
- Lionbridge Technologies, LLC.
- Lotus Quality Assurance
- Scale AI, INC.
- SuperAnnotate AI, Inc.
- Tagtog Sp. Z.o.o
- Cogito Tech LLC
Recent Developments
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Innodata, Inc. announced the expansion of services to support the development of predictive models for the medical record by combining their Synodex medical data extraction platform with data annotation platform. This expansion demonstrates the efficacy of the method of Innodata for extracting high-quality AI training data from medical records.
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Telus Corporation announced the acquisition of Lionbridge AI, a market-leading global supplier of solutions for annotation platforms and crowd-based training data by their Telus International segment. Lionbridge AI will assist TELUS International expand its penetration of the quickly expanding new economy services market
- Report ID: 4763
- Published Date: May 08, 2025
- Report Format: PDF, PPT
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