Data Annotation Tools Market (2024 - 2030) Size, Share & Trends Analysis Report By Type (Text, Image/Video, Audio), By Annotation Type, By Vertical, By Region, And Segment Forecasts

Data Annotation Tools Market Summary

The data annotation tools enable users to enhance the value of data by adding attribute tags to it or labeling it. The key benefit of using annotation tools is that the combination of data attributes enables users to manage the data definition at a single location and eliminates the need to rewrite similar rules in multiple places.

The rise of big data and a surge in the number of large datasets are likely to necessitate the use of artificial intelligence technologies in the field of data annotations. The data annotation industry is also expected to have benefited from the rising demands for improvements in machine learning as well as in the rising investment in advanced autonomous driving technology.

Technologies such as the Internet of Things (IoT), Machine Learning (ML), robotics, advanced predictive analytics, and Artificial Intelligence (AI) generate massive data. With changing technologies, data efficiency proves to be essential for creating new business innovations, infrastructure, and new economics. These factors have significantly contributed to the growth of the industry. Owing to the rising potential of growth in data annotation, companies developing AI-enabled healthcare applications are collaborating with data annotation companies to provide the required data sets that can assist them in enhancing their machine learning and deep learning capabilities.

For instance, in November 2022, Medcase, a developer of healthcare AI solutions, and NTT DATA, formalized a legally binding agreement. Under this partnership, the two companies announced their collaboration to offer data discovery and enrichment solutions for medical imaging. Through this partnership, customers of Medcase will gain access to NTT DATA's Advocate AI services. This access enables innovators to obtain patient studies, including medical imaging, for their projects.

However, the inaccuracy of data annotation tools acts as a restraint to the growth of the market. For instance, a given image may have low resolution and include multiple objects, making it difficult to label. The primary challenge faced by the market is issues related to inaccuracy in the quality of data labeled. In some cases, the data labeled manually may contain erroneous labeling and the time to detect such erroneous labels may vary, which further adds to the cost of the entire annotation process. However, with the development of sophisticated algorithms, the accuracy of automated data annotation tools is improving thus reducing the dependency on manual annotation and the cost of the tools.

Market Concentration & Characteristics

Significant innovations by prominent companies in the market are augmenting the degree of innovations in the data annotation tools market. Furthermore, the increasing utilization of AI by a number of businesses to develop novel products and revolutionize even the most established sectors is also projected to increase the need for novel innovations over the forecast period.

Strategic mergers and acquisitions from key companies are significantly fueling the market growth. In addition, the data annotation vendors are also poised for collaborations with leading tech giants in order to scale and expand their solution and service offerings to the diverse customer base. For instance, Amazon Web Services (AWS) has been chosen by Appen Limited, a source of high-quality data for the AI lifecycle, as its primary cloud for AI innovation and solutions. With a multi-year deal, the firms are deepening their collaboration as Appen creates new enterprise solutions for AI data source, model validation, and annotation.

The data annotation tools market is expected to be highly influenced by evolving regulations surrounding data privacy and security. Compliance with these regulations will be crucial, and annotation tools that effectively integrate industry-specific compliance measures will hold a competitive edge. However, stringent regulations could raise costs and introduce complexities for both tool developers and users.

The unique nature of data annotation involves translating data into a format understandable by machines and AI models, the threat of service substitution in this market is currently low. The increasing volume of AI and ML models further reinforces the demand for reliable data annotation. While AI-powered data annotation tools may automate primary tasks and potentially reduce costs in the future, human expertise in understanding and interpreting complex data will remain essential.

The market is characterized by a dynamic end-user landscape. Various industries are actively adopting data annotation tools. For instance, annotating data is going to play an important role in enhancing AI applications in the healthcare sector. Annotating medical imaging data allows AI-powered systems to analyze trends, identify potential abnormalities, and even assist medical professionals in generating automated reports. Exploring other promising end-user segments and their specific applications for data annotation tools will be crucial for understanding the market's future growth potential.

Type Insights

Based on type, the market is segmented into text, image/video, and audio. The text data annotation tools segment led the market in 2023, accounting for over 36.1% share of the global revenue. The image/video annotation segment is expected to dominate the market over the forecast period. Some of the major applications of image data annotation are in the medical industry in the field of medical imaging. The market is also witnessing substantial growth in the startup ecosystem in terms of innovations and investments. Startups such as Infervision, Zebra Medical Vision, and Arteries are some of the prominent startups within the healthcare sector in the data annotation market.

The text annotation segment is expected to grow at a promising pace over the forecast period, owing to the rising applications in e-commerce and clinical research applications. Text annotation will dominate the global market owing to the need to fine-tune the capacity of AI so that it can help recognize patterns in the text, voices, and semantic connections of the annotated data. Significant adoption of automated labeling solutions employing machine learning algorithms for text data annotation is notable. These solutions can offer speed and cost advantages over human-in-the-loop approaches subsequently propelling growth for the text annotation segment.

Annotation Type Insights 

Based on annotation type, the market is categorized into manual, semi-supervised, and automatic. The manual segment held a dominant revenue share in 2023. Manual data annotation is a process of labeling or annotating any data by humans. The approach is popular due to its benefits such as accuracy, high level of integrity, minimal data annotation efforts, and a higher chance of discovering intriguing insights pertaining to the data compared to automatic annotation, which can be later integrated into an algorithm. However, as manual annotation can be expensive and time-consuming, labeled data gathered through crowdsourcing activities is used for various applications.

The automatic annotation segment is expected to grow at a promising pace from 2024 to 2030. AI is becoming vital to the data annotation industry as the technology allows the extraction of high-level and complex abstractions from the datasets using a hierarchical learning process. The need for mining and extracting meaningful patterns from voluminous data is driving the growth of AI, which is expected to further drive the demand for automatic data annotation tools. The semi-supervised systems can be used to identify specific labeled data or can be used to classify the unlabeled data semi-supervised. Thus, limited use of this annotation type will contribute to a moderate share in the market.

Vertical Insights

The IT segment held the leading revenue share in 2023. The healthcare data annotation tools segment is expected to grow at a good pace from 2024 to 2030. AI is widely adopted in the healthcare sector for various applications such as treatment prediction, diagnostic automation, drug development, and gene sequencing. The data sets in healthcare are required to be trained with machine learning algorithms. The quality of the training significantly impacts the efficacy and accuracy of the algorithm used for developing AI-based applications. Access to accurate and high-quality data sets is the key step in developing a successful AI-enabled product in the healthcare sector. Thus, data annotation tools drive the development of the sector by providing training data sets to the AI.

The automotive segment is anticipated to grow at the highest CAGR over the forecast period as data annotation tools find wide acceptance in self-driving vehicles. The growing R&D spending towards improving image annotation for pushing developments in the field of self-driving vehicles is boosting the market growth. For instance, in November 2022, TechSee entered into a partnership with TELUS International to advance real-time computer vision in engagement centers. This collaboration involves integrating TechSee's array of AI-driven service automation and visual engagement technologies into TELUS International's customer offerings of self-driving models.

Regional Insights

North America dominated the global market in terms of revenue share in 2023. This is due to the rapid product and geographical expansion strategy undertaken by key companies in order to gain a competitive edge. The growth is attributable to the increasing integration of mobile computing platforms and artificial intelligence in digital shopping and e-commerce. The rising prominence of crowdsourcing, to generate labeled data with efficiency and in a cost-effective manner, is fostering the market growth.

U.S. Data Annotation Tools Market Trends

The data annotation tools market in the U.S. is witnessing substantial market growth expanding with a CAGR of 22.7% from 2024 to 2030. The growth is driven by the rapid development of technology, the rising use of smart gadgets, and the prevalence of social networking sites. Furthermore, the increasing implementation of facial recognition technologies in security and surveillance systems is anticipated to further foster the growth.

Europe Data Annotation Tools Market Trends

The data annotation tools market in Europe anticipates robust growth driven by the increasing adoption of AI technologies across various sectors, particularly automotive and retail. These sectors utilize image annotation heavily for applications like self-driving cars and product analysis. While commercially licensed tools dominate the market, there's a growing presence of open-source and freemium options, catering to individual developers and cost-conscious businesses.

The UK data annotation tools market is estimated to hold highest growth rate in the Europe region owing to the healthcare sector being a prominent user of data annotation techniques. The requirement for efficient and precise data labeling for various medical imaging, such as X-rays, ultrasounds, and MRIs, may be ascribed to the growing acceptance of data annotation tools in the healthcare sector.

Asia Pacific Data Annotation Tools Market Trends

The data annotation tools market in Asia Pacific is anticipated to register the highest CAGR over the forecast period. The growth is attributed to the rising usage of mobile devices and tablets, rapid technical breakthroughs, and the rising prominence of social networking in developing economies like India and China. Emerging economies in the region hold significant potential for the widespread adoption of data annotation tools, particularly in the healthcare and financial services verticals marked by the increasing adoption of technology and innovative access programs.

The China data annotation tools market accounted for the largest revenue share in Asia Pacific in 2023. This can be attributed to the presence of leading companies along with flourishing startup ecosystem in China is propelling the market growth. Substantial investments and strategic collaborations for business innovation and advancement for employing cutting-edge technologies are projected to augment the market growth in the coming years.

Key Data Annotation Tools Company Insights

Vendors are taking several strategic initiatives, such as collaborations, acquisitions & mergers, and partnerships with other key market players. These companies are focusing on raising funds to support geographical expansion and product launches. For instance, in January 2023, CloudFactory, a worldwide human-in-the-loop AI company, has introduced rapid annotation, a Vision AI product that combines CloudFactory's best-in-class workforce with industry-leading AI-assisted labeling technology to produce high-quality labeled data 5 times quicker than manual labeling. By combining an established managed workforce operation and an adaptive AI-assisted labeling model, Accelerated Annotation offers a balanced approach to annotation quality and speed.

Recent Developments

• In November 2023, Appen Limited, a high-quality data provider for the AI lifecycle, chose Amazon Web Services (AWS) as its primary cloud for AI solutions and innovation. As Appen utilizes additional enterprise solutions for AI data source, annotation, and model validation, the firms are expanding their collaboration with a multi-year deal. Appen is strengthening its AI data platform, which serves as the bridge between people and AI, by integrating cutting-edge AWS services.

• In September 2023, Labelbox launched Large Language Model (LLM) solution to assist organizations in innovating with generative AI and deepen the partnership with Google Cloud. With the introduction of large language models (LLMs), enterprises now have a plethora of chances to generate new competitive advantages and commercial value. LLM systems have the ability to revolutionize a wide range of intelligent applications; nevertheless, in many cases, organizations will need to adjust or finetune LLMs in order to align with human preferences. Labelbox, as part of an expanded cooperation, is leveraging Google Cloud's generative AI capabilities to assist organizations in developing LLM solutions with Vertex AI. Labelbox's AI platform will be integrated with Google Cloud's leading AI and Data Cloud tools, including Vertex AI and Google Cloud's Model Garden repository, allowing ML teams to access cutting-edge machine learning (ML) models for vision and natural language processing (NLP) and automate key workflows.

• In March 2023, has released the most recent version of Enlitic Curie, a platform aimed at improving radiology department workflow. This platform includes Curie|ENDEX, which uses natural language processing and computer vision to analyze and process medical images, and Curie|ENCOG, which uses artificial intelligence to detect and protect medical images in Health Information Security.

• In November 2022, Appen Limited, a global leader in data for the AI Lifecycle, announced its partnership with CLEAR Global, a nonprofit organization dedicated to ensuring access to essential information and amplifying voices across languages. This collaboration aims to develop a speech-based healthcare FAQ bot tailored for Sheng, a Nairobi slang language.

Data Annotation Tools Market Report Scope

Global Data Annotation Tools Market Report Segmentation

This report forecasts revenue growth at global, regional, and country levels and provides an analysis of the latest industry trends in each of the sub-segments from 2017 to 2030. For the purpose of this study, Grand View Research has segmented the global data annotation tools market report based on type, annotation type, vertical, and region:

• Type Outlook (Revenue, USD Million, 2017 - 2030)

  • Text

  • Image/Video

  • Audio

• Annotation Type Outlook (Revenue, USD Million, 2017 - 2030)

  • Manual

  • Semi-supervised

  • Automatic

• Vertical Outlook (Revenue, USD Million, 2017 - 2030)

  • IT

  • Automotive

  • Government

  • Healthcare

  • Financial Services

  • Retail

  • Others

• Regional Outlook (Revenue, USD Million, 2017 - 2030)

  • North America

    • U.S.

    • Canada

    • Mexico

  • Europe

    • Germany

    • U.K.

    • France

  • Asia Pacific

    • China

    • Japan

    • India

  • South America

    • Brazil

  • Middle East and Africa (MEA)