Data Annotation Tools Market

The market size of Data Annotation Tools worldwide reached USD 805.6 million in 2022 and is projected to grow at a compound annual growth rate (CAGR) of 26.5% from 2023 to 2030. This growth is primarily fueled by the increasing adoption of image data annotation tools in sectors such as automotive, retail, and healthcare. These tools enable users to enhance the value of data by adding attribute tags or labels to it. The key advantage of using annotation tools is that they allow for centralized data management and eliminate the need to rewrite similar rules in multiple locations. As the volume of big data continues to rise and the number of large datasets increases, the use of artificial intelligence technologies in data annotation is becoming increasingly necessary. The data annotation industry is also benefiting from the growing demand for improvements in machine learning and increased investment in advanced autonomous driving technology.

Data annotation is expected to play a significant role in advancing the applications of artificial intelligence in the healthcare sector. AI-powered machines utilize machine vision or computer vision in medical imaging data technologies to detect patterns and identify potential injuries, assisting medical professionals in generating automated reports after examinations. AI can easily screen databases of CT scans, MRI, and X-Ray images to identify various injuries. Data annotation tools aid in training AI systems to differentiate between normal and injured medical images, facilitating the generation of final reports for examined individuals. As an example, in March 2021, U.S.-based company Innodata Inc. announced the expansion of its AI data annotation tool capabilities to include medical patient reports. Innodata plans to combine the capabilities of its AI data annotation tool platform with the Synodex medical data extraction platform to create a medical record data annotation platform. This initiative aims to generate high-quality AI training data that complies with HIPAA regulations and adheres to all security protocols.

Emerging technologies like the Internet of Things (IoT), Machine Learning (ML), robotics, advanced predictive analytics, and Artificial Intelligence (AI) generate vast amounts of data, driving the need for data efficiency in order to fuel new business innovations, infrastructure, and economic models. These factors have significantly contributed to the growth of the industry. As the demand for data labeling expands, companies developing AI-enabled healthcare applications are partnering with data annotation firms to obtain the necessary datasets that can enhance their machine learning and deep learning capabilities. For example, in November 2020, Telus International, a provider of digital customer experience and IT solutions, announced its acquisition of Lionbridge AI, a platform offering training data and annotation solutions for designing AI algorithms. This acquisition is expected to bolster Telus International's digital solution portfolio and expand its global presence.

However, the accuracy of data annotation tools poses a challenge to market growth. Some images may have low resolution or contain multiple objects, making labeling difficult. The primary obstacle faced by the market is the issue of inaccurate data labeling. Manually labeled data may sometimes contain errors, and detecting these errors can vary in terms of time, adding to the overall annotation costs. Nonetheless, the development of advanced algorithms is improving the accuracy of automated data annotation tools, reducing the reliance on manual annotation and potentially lowering costs in the future.

In terms of data type, the text segment held the largest market share in 2022, accounting for over 36% of global revenue. The market is segmented into text, image/video, and audio. The image/video annotation segment is expected to dominate the market during the forecast period. Image data annotation finds significant applications in the medical industry, particularly in medical imaging. For instance, investments in startups developing machine learning solutions using medical images reached $522 million in the first half of 2018. Prominent healthcare startups in the data annotation market include Infervision, Zebra Medical Vision, and Arteries.

The text annotation segment is poised to exhibit promising growth during the forecast period, driven by increasing applications in e-commerce and clinical research. Text annotation is expected to dominate the global market due to the necessity of refining AI capabilities to recognize patterns in text, voices, and semantic connections within annotated data. The audio segment is projected to capture a moderate share in the market. For example, in April 2021, Zoom, a video telephony software, introduced several updates to its platforms, including enhanced screen annotation, advanced hardware solutions for Zoom Rooms, expanded management abilities for Zoom Chat, and improved user experience based on customer feedback. These updates enable users to highlight text or objects without the need to erase previous annotations and utilize a new pen feature called the vanishing pen feature for text or object highlighting.

Annotation Type Insights
In 2022, the manual segment held the largest market share, accounting for over 81% of the global revenue. The market is segmented into manual, semi-supervised, and automatic annotation types. Manual data annotation involves the labeling or annotation of data by humans. This approach is popular due to its advantages, including accuracy, high integrity, minimal annotation efforts, and a higher likelihood of discovering insightful information within the data compared to automatic annotation. Labeled data collected through crowdsourcing activities is often used for various applications. However, manual annotation can be costly and time-consuming.

The automatic annotation segment is poised for significant growth during the forecast period. With the increasing importance of AI in the data annotation industry, this technology enables the extraction of complex abstractions from datasets through hierarchical learning processes. The demand for automatic data annotation tools is driven by the need to mine and extract meaningful patterns from large volumes of data. As a result, AI's growth is expected to fuel the demand for automatic annotation, while the limited use of semi-supervised systems will contribute a moderate share to the market.

Vertical Insights
In 2022, the IT segment emerged as the market leader, accounting for a 32% share of global revenue. The market is segmented into IT, automotive, government, healthcare, financial services, retail, and others. The healthcare segment is projected to grow at a favorable pace throughout the forecast period. AI is widely adopted in the healthcare sector for various applications, including treatment prediction, diagnostic automation, drug development, and gene sequencing. High-quality training data sets are crucial for the efficacy and accuracy of machine learning algorithms used in developing AI-based healthcare products. Data annotation tools play a vital role in providing training data sets for AI in the healthcare sector, thereby driving its development.

The automotive segment is anticipated to witness the highest growth rate over the forecast period, as data annotation tools find extensive application in self-driving vehicles. The increasing research and development spending on improving image annotation for advancements in autonomous driving technology is boosting market growth. For example, in January 2021, TCS (Tata Consultancy Services) launched the autoscape solution set for players in the autonomous and connected vehicle ecosystem. This solution addresses technology and business challenges and offers services such as petabyte data collection and analysis, algorithm validation, and deployment, providing guidance and control for autonomous vehicles in real-world scenarios. It also includes a data annotation studio and autonomous vehicle validation services, offering cost-effective data organization and model management to enhance enterprise workflows.

Regional Insights
In 2022, North America emerged as the dominant market, accounting for over 36% of the global revenue. This can be attributed to the rapid product and geographical expansion strategies implemented by market vendors to gain a competitive advantage. The European market is expected to witness a steady growth trajectory during the forecast period. The increasing focus on image annotation is anticipated to enhance operations in the retail and automotive sectors within the European region.

The Asia Pacific market is projected to register the highest compound annual growth rate (CAGR) over the forecast period. Emerging economies in the Asia Pacific region hold significant potential for the widespread adoption of data annotation tools, particularly in the healthcare and financial services sectors. The healthcare industry in the Asia Pacific region is experiencing growth due to the adoption of technology and innovative healthcare access programs. These factors are expected to drive the demand for image data annotation tools in the region. For example, in April 2021, Congenica Ltd, a provider of data analytics tools for annotating and clinically interpreting genomic sequence data, partnered with Camtech Diagnostics, a UK-based technology company specializing in microfluidics. This collaboration aims to expand Congenica's presence in countries such as Singapore, Malaysia, Japan, and South Korea.

Key Companies & Market Share Insights
Market vendors are undertaking various strategic initiatives such as collaborations, acquisitions, mergers, and partnerships with other key players. Additionally, these companies are focused on raising funds to support geographical expansion and product launches. For instance, in November 2018, CloudFactory Limited, a cloud-based platform offering machine learning, data enrichment services, and data transcription solutions, raised $65 million in a growth equity round, bringing its total funding to $78 million. Some of the prominent players in the global data annotation tools market include:
• Annotate.com
• Appen Limited
• CloudApp
• Cogito Tech LLC
• Deep Systems
• Labelbox, Inc
• LightTag
• Lotus Quality Assurance
• Playment Inc
• Tagtog Sp. z o.o
• CloudFactory Limited
• ClickWorker GmbH
• Alegion
• Figure Eight Inc.
• Amazon Mechanical Turk, Inc
• Explosion AI GMbH
• Mighty AI, Inc.
• Trilldata Technologies Pvt Ltd
• Scale AI, Inc.
• Google LLC
• Lionbridge Technologies, Inc
• SuperAnnotate LLC

Global Data Annotation Tools Market Segmentation

The report provides revenue growth forecasts for the global, regional, and country levels, along with an analysis of the latest industry trends within each sub-segment, covering the period from 2023 to 2030. Grand View Research has categorized the global data annotation tools market report based on type, annotation type, vertical, and region for this study.

Type Outlook (Revenue, USD Million, 2023 - 2030)
• Text
• Image/Video
• Audio

Annotation Type Outlook (Revenue, USD Million, 2023 - 2030)
• Manual
• Semi-supervised
• Automatic

Vertical Outlook (Revenue, USD Million, 2023 - 2030)
• IT
• Automotive
• Government
• Healthcare
• Financial Services
• Retail
• Others

Regional Outlook (Revenue, USD Million, 2023 - 2030)
• North America
o U.S.
o Canada
o Mexico
• Europe
o Germany
o U.K.
o France
• Asia Pacific
o China
o Japan
o India
• South America
o Brazil
• Middle East and Africa (MEA)