Размер мирового рынка, прогноз и основные тенденции на 2025-2037 гг.
The data annotation tools market size exceeded US$ 1.58 billion in 2024 and is expected to reach US$ 32.36 billion by the end of 2037, registering a CAGR of about 25.9% during the forecast period, i.e., from 2025 to 2037. In 2025, the data annotation tools industry size is estimated to be US$ 1.91 billion.
The growth of the market can be attributed to the increase in the production of data such as videos and photos. To train machine learning models, additional information/metadata is added to various types of data such as text, audio, images, and videos using a data annotation tool. More than 3 billion photos and about 720,000 hours of video are shared on social media worldwide every day.
Apart from these factors, which are believed to be driving the growth of the data annotation tools market include the advancement of advanced technologies such as artificial intelligence, machine learning, robotics, and others. Advanced technologies such as industrial robots are mainly based on high-quality data annotations. It is common practice to use labeled data for tasks such as developing and testing computer vision (CV) models for robotic navigation systems. According to a new World Robotics 2020 Industrial Robots study published by the International Federation of Robotics, a record 2.7 million industrial robots are now in use in companies worldwide, up 12% from the previous year. Moreover, 373,000 units were shipped worldwide in 2019. Furthermore, the rise in the use of data annotation in machine learning is expected to fuel the market growth. In machine learning projects worldwide, more than 80% of the engineering work is dedicated to data preparation and labeling. Additionally, the third-party data annotation market is expected to nearly triple by 2024.
Сектор инструментов аннотации данных: факторы роста и проблемы
Growth Drivers
- Growing demand for intelligent autonomous driving technologies . To create an autonomous vehicle and solve all the safety issues, a lot of annotated images and video data is required. This allows the self-driving system to be trained to recognize objects. Almost 1.4 million cars sold worldwide in 2019 had at least Level 3 autonomy. Sales of self-driving vehicles are expected to grow between 2019 and 2030. Moreover, the expected global sales of these cars in 2030 will be around 58 million units.
- Growing use of artificial intelligence . Data labeling allows AI to accurately process all projects and expands its capabilities. Artificial intelligence is used by about 37% of companies and organizations worldwide. In addition, almost all investments in AI technologies are made by nine out of the ten largest companies.
- Massive data creation – Data labeling allows you to identify targets in the form of raw data. The total volume of data in the world is projected to exceed 40 zettabytes in 2020. According to recent estimates, more than 4 billion people use the Internet every day, creating about 3 quintillion bytes of data.
- Growing Number of Devices Connected to the Internet of Things . With the growing number of devices connected to the Internet of Things, production and consumption have increased rapidly, and this data can be turned into value using a data annotation tool. It is predicted that by 2030, the number of IoT devices worldwide will be around 25 billion. Currently, there are around 400 IoT platforms in use. Moreover, by 2025, 27 billion devices could be connected to the Internet of Things.
- Growing popularity of facial recognition . High-quality facial annotations are the basis of facial and emotion recognition. Accuracy and quality of video and image annotations are important for facial recognition algorithms to work properly. As of 2019, about 96 million mobile devices worldwide were equipped with facial recognition hardware. However, by 2024, about 1 billion devices worldwide are expected to have facial recognition software solutions.
Problems
- Inaccuracy in data labeling due to poor content quality – The execution of a data annotation project was considered to be the biggest hurdle in terms of data quality. High data quality must be maintained throughout the annotation process, which requires consistency. The overall accuracy of a machine learning model can be affected by biased estimates caused by poor data quality. Inconsistency can also cause difficulties in the review process and communication.
- Risk of data leakage
- Lack of skilled workers to process the huge volume of data.
Рынок инструментов аннотации данных: ключевые выводы
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Базовый год |
2024 год |
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Прогнозный год |
2025-2037 гг. |
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Среднегодовой темп роста |
25,9% |
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Размер рынка в базовом году (2024 г.) |
1,58 миллиарда долларов США |
|
Прогнозируемый год Размер рынка (2037 г.) |
32,36 млрд долларов США |
|
Региональный охват |
|
Сегментация инструментов аннотации данных
End User (Retail & E-Commerce, IT & Telecom, BFSI, Government, Automotive, Healthcare)
The global data annotation tools market is segmented and analyzed for demand and supply by the end users in the retail & e-commerce, IT & telecom, BFSI, government, automotive, healthcare, and others. Out of the six end users of data annotation tools, the retail & e-commerce segment is estimated to capture the largest market share in 2037. The growth of this segment can be attributed to the increasing prevalence of e-commerce and the rise in the integration of artificial intelligence in retail and e-commerce. According to a survey conducted in October 2020, around 70% of e-commerce decision makers in North America and Europe said that AI will help in personalizing their companies’ operations in 2021. enhancing the online shopping experience. Over the past few years, companies have witnessed a transformation in the adoption of artificial intelligence and data annotation in the e-commerce industry. Therefore, to improve user experience and make more effective decisions, several companies are already leveraging AI with data annotation services.
Type (text, images and video, audio)
The global data annotation tools market is also segmented and analyzed for supply and demand based on types: text, images, videos, and audio. Among these three segments, the text segment is expected to hold a significant share in 2037. Text is the most commonly used data type. Around 70% of companies use text. Text annotations include a wide variety of annotations including sentiments, intents, and queries. The growth of the segment is primarily attributed to the growing use of annotations in data labeling. NLP (Natural Language Processing) technologies, automated Q&A platforms, intelligent chatbots, sentiment analysis, and others are used for labeling. Thus, the growing use of chatbots and ="_blank"> cloud-based NLP technologies powered by text analytics are also expected to contribute to the growth of the segment. Since 2019, the use of chatbots as a brand communication channel has grown by around 92% globally. In 2020, nearly 25% of customers interacted with companies through chatbots, 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 components |
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By annotation type |
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End user |
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North American Market Forecast
By the end of 2037, the North America data annotation tools market is projected to be the largest with a share of about 30%. The market growth can be attributed mainly to the growing number of devices connected to the Internet of Things (IoT) . In 2022, there were about 3 billion connected IoT devices in North America, and this number is expected to grow to more than 6 billion devices by 2030. On the other hand, the growing adoption of artificial intelligence in healthcare is also expected to drive the market growth. According to a survey of US healthcare executives, about 41% said that their use of artificial intelligence will reach a fully functional level as of 2021. Another nearly 26% said that their AI system is partially functional.
Asia Pacific Market Statistics
The Asia Pacific data annotation tools market is estimated to be the second largest, accounting for around 28% of the market share by the end of 2037. The market growth can be attributed mainly to the increasing internet penetration, which is expected to increase data generation. India adds up to 25 million new smartphone users every three months and has the highest mobile data usage in the world at around 12 gigabytes (GB) per user per month. In addition to this, China generated around 8 trillion gigabytes of data in 2018. This amount is expected to increase to around 49 trillion gigabytes by 2025. Furthermore, the growing demand for autonomous vehicles in the region is also expected to fuel the data annotation tools market. To promote modern mobility services, the Japanese government aims to deploy self-driving vehicles in over 40 regions in the country by 2025.
Europe Market Forecast
In addition, the data annotation tool market in Europe is projected to account for a large share by the end of 2037. The market growth can be attributed mainly to the growing adoption of facial recognition technology. Moreover, facial recognition has quickly evolved from a recent curiosity to an important component of daily life. Facial recognition technology is rapidly evolving, and algorithms are getting better every day. In 11 European countries, law enforcement agencies are already using biometric identification systems in their investigations. In addition, facial recognition technology is used by police for preliminary identification in criminal investigations in France, Germany, Greece, Hungary, Italy, Austria, Finland, France and other regions.
Компании, доминирующие на рынке инструментов аннотации данных
- Innodata, Inc.
- Company overview
- Business strategy
- Main product offerings
- Financial indicators
- Key performance indicators
- Risk analysis
- Latest developments
- Regional presence
- SWOT analysis
- Telus Corporation
- Figure Eight Federal Inc.
- Google LLC
- Light tag
- Lionbridge Technologies, LLC.
- Lotus Quality Assurance
- Scale AI, INC.
- SuperAnnotate AI, Inc.
- Tagtog Sp. Z.o.o.
- OOO "Kogito Tech"
In the News
- Innodata, Inc. announced the expansion of its services to support the development of predictive models for medical records by combining its Synodex medical data extraction platform with its data annotation platform. This expansion demonstrates the effectiveness of Innodata's method for extracting high-quality AI training data from medical records.
- Telus Corporation announced the acquisition of Lionbridge AI, a leading global provider of annotation and mass learning data platform solutions, by its Telus International segment. Lionbridge AI will help TELUS International expand its presence in the fast-growing new economy services market
Авторы отчета: Abhishek Verma
- Report ID: 4763
- Published Date: Oct 14, 2024
- Report Format: PDF, PPT
