Data Collection And Labeling Market (By Data Type: Audio, Image/Video, Text; By Vertical: IT, Retail & E-commerce) - Global Industry Analysis, Size, Share, Growth, Trends, Revenue, Regional Outlook and Forecast 2022-2030

The global data collection and labeling market size was estimated at around USD 1.85 billion in 2021 and it is projected to hit around USD 13.45 billion by 2030, growing at a CAGR of 24.66% from 2022 to 2030.

Report Highlights

• The image/video segment led the market in 2021 with a revenue share of over 35.3%. 
• The IT segment led the market in 2021, accounting for over 30.2% share of the global revenue. 
• North America dominated the market in 2021, accounting for more than 35.3% share of global revenue. 

Data collection and labeling refer to collecting datasets from online sources and other sources and labeling them based on their nature, data type, and feature. Data gathering and its annotation, combined with AI technology, have created valuable growth opportunities in several verticals, such as gaming, social networking, and e-commerce. For instance, Twitter and Facebook, two major platforms in social networking, have benefited from image processing technology in audience engagement. Companies use data labeling platforms to identify raw data for the machine learning model. Text, movies, audio, and other items are the raw data. For instance, in May 2022, Heartex, Inc., an annotations tools and data labeling platform provider, announced a $25 million Series A fundraising round. The funds will go toward its AI-driven open-source data labeling platform. The platform aims to assist in labeling workflows for various AI use cases, and it includes capabilities for reporting, data quality control, and analytics.

The advent of digital capturing devices, particularly cameras built into smartphones, has led to an exponential growth in the volume of digital content in the form of images and videos. Much visual and digital information is being captured and shared through several applications, websites, social networks, and other digital channels. Several businesses have leveraged this available online content to deliver smarter and better services to their customers using data annotation. For instance, Scale AI, Inc., the U.S.-based tech start-up, has provided valuable data labeling services to its autonomous driving customers, including Waymo LLC; Lyft, Inc.; Zoox; and Toyota Research Institute.

However, data cleaning remains a significant challenge involved in data labeling. Also, considering the time, complexity, and cost associated with the development of machine learning models, many companies may not have the resources who can produce acceptable and accurate results. Therefore, several companies are taking strategic initiatives to expand their business in artificial intelligence-based data gathering. For instance, in July 2020, Microsoft acquired Orions Digital Systems, Inc., a U.S.-based data management solutions provider, to boost its Dynamics 365 Connected Store capabilities. This acquisition is anticipated to increase the use of computer vision and IoT sensors to help retailers better understand customer behavior and manage their physical spaces.

Scope of The Report

Data Type Insights

The image/video segment led the market in 2021 with a revenue share of over 35.3%. The large percentage can be due to the rising use of computer vision in various industries, including automotive, healthcare, media, and entertainment. For instance, in May 2022, Researchers at the Massachusetts Institute of Technology (MIT), a private land-grant research university, created a machine learning model that learns to describe data in a manner that incorporates concepts shared by video and aural modalities. Their model can identify and mark where particular actions occur in a video. The developers limit the technique to only 1,000 words to label vectors, and the model can choose which concepts or activities to put into a single vector.

The text segment accounted for a significant share in 2021 owing to its rising applications in clinical research and e-commerce. For instance, Taskmonk Technology Pvt Ltd., an e-commerce data labeling platform, offers a centralized procurement of labeled data to create better and faster AI retail. Further, it would help e-commerce enterprises get reliable data and save time with the help of AI data labeling. It would benefit enterprises by maximizing their labeling budget, boosting data accuracy, orchestrating labeling projects for any data type, and speeding up data labeling. With the growing implementation of EHR (Electronic Health Record) systems, the accumulation of clinical datasets, including unstructured text documents, has become a valuable resource for clinical research. Statistical NLP (natural language processing) models have been developed to unlock information embedded in clinical text.

For instance, in September 2021, Centaur Labs, a scalable and accurate medical data labeling service provider, announced USD 15 million in series A funding. The funds will be used to further the company's aim of labeling the world's clinical data. Centaur Labs' work and emphasis on healthcare data quality align with AI pioneer Andrew Ng's current drive to transform AI development from model-centric to data-centric. Also, with the advancement in sentiment analysis, text labeling is highly used in social media monitoring to build recommendation systems.

Vertical Insights

The IT segment led the market in 2021, accounting for over 30.2% share of the global revenue. The large share can be attributed to the wide adoption of AI applications. Besides, the healthcare industry is expected to grow over the forecast period. Since artificial intelligence is being used widely in the healthcare industry for several applications, such as diagnostic automation, treatment prediction, gene sequencing, and drug development, training data set with deep learning and machine learning algorithms is required. It directly influences the industry growth positively due to the requirement of highly accurate data labeling for efficient AI-based applications.

For instance, in May 2021, ByteBridge, a human-powered and machine-learning-powered data collecting and labeling SAAS platform, took a significant step ahead with the release of its automated data gathering and labeling platform. It provides researchers with high-quality labeled datasets relating to health care and public health, giving the machine learning industry high-quality training data.

The retail and e-commerce segment accounted for a significant market share in 2021. With the help of image labeling, online shoppers can search for clothing or accessories by taking a picture of the texture, print, or color of their choice. The photo captured by the smartphone is uploaded to an app that searches an inventory of products to find similar products using AI technology. Also, data annotation technology is being increasingly adopted in autonomous vehicles, which is anticipated to contribute to the noticeable growth of the automotive segment.

Self-driving cars can detect obstacles and warn the driver about the proximity to walkways and guardrails with the help of this technology. The technology is also capable of reading stoplights and road signs. For instance, in February 2022, Annotell, a company providing high-quality training data for supervised machine learning, raised USD 24 million to create data labeling tools for self-driving systems. The firm claims to provide a solution in the form of a platform that ostensibly allows for the safe perception of self-driving automobiles by integrating software with the knowledge to reduce the production timeline of driverless cars.

Regional Insights

North America dominated the market in 2021, accounting for more than 35.3% share of global revenue. This is due to the rise of cloud-based media services, one of the potential data sources for collecting. The expanding integration of mobile computing platforms and artificial intelligence in digital shopping and e-commerce is contributing to the regional growth. It generates a lot of data for annotation.

For instance, in May 2022, Sumake North America, the most dependable and complete source for automotive, electrical, and industrial applications, is introducing the EA-SC100 tool management system, its newest product. The system includes a touchscreen interface for real-time result visualization and a remote administration system for data collection and tool setup. The European regional market is predicted to grow significantly during the forecast period. Constant improvements in car obstacle detection technologies is likely to boost the growth of the European automobile industry throughout the forecast period.

Asia Pacific is expected to expand at the fastest CAGR during the projected period. This expansion can be ascribed to the increased usage of mobile phones and tablets, data processing technologies, and the popularity of social networking sites in emerging economies such as China and India. The expanding number of smart devices increases data collection and annotation demand. Face recognition applications in security and surveillance systems in China are expected to fuel market expansion in the Asia Pacific region.

For example, the Chinese government has implemented real-name registration laws in the country, requiring residents to link their internet accounts to their official government ID. For instance, in April 2022, a Reuters investigation of government records revealed that dozens of Chinese enterprises had developed software called "one person, one file." The software utilizes artificial intelligence to classify data set collected on citizens amid significant demand from authorities looking to expand their surveillance tools. The system improves on existing software, which takes data and then leaves it up to people to manage.

Key Players

• Reality AI
• Globalme Localization Inc.
• Global Technology Solutions
• Alegion
• Labelbox, Inc.
• Dobility, Inc.
• Scale AI, Inc.
• Trilldata Technologies Pvt. Ltd.
• Appen Limited
• Playment Inc.

Market Segmentation

• By Data Type Outlook

• Text
• Image/ Video
• Audio
• By Vertical Outlook
• IT
• Automotive
• Government
• Healthcare
• BFSI
• Retail & E-commerce
• Others
• By Regional Outlook
• North America

• U.S.
• Canada
• Mexico
• Europe
• Germany
• U.K.
• France
• Asia Pacific
• China
• Japan
• India
• South America
• Brazil
• Middle East and Africa (MEA)