PUBLISHER: The Business Research Company | PRODUCT CODE: 1973074
PUBLISHER: The Business Research Company | PRODUCT CODE: 1973074
Data annotation, additionally referred to as data labeling, is the act of attributing, tagging, or labeling data using various metadata formats such as audio, text, pictures, and videos to train machine learning models. It is required to train AI (artificial intelligence) models so that they can properly understand varied kinds of data.
The main components of data annotation and labeling are solutions and services. A solution is a technique or procedure for resolving a problem or fulfilling a requirement. It includes various data types such as text, image, video, and audio, with several types of annotation are included, such as manual, automatic, and semi-supervises. It is used for several application, including dataset management, security and compliance, data quality control, workforce management, content management, catalog management, sentiment analysis, and others, and are used by various end-users, such as banking, financial services, and insurance (BFSI), information technology and information technology-enabled services (ITES), healthcare and life science, telecom, government defense, and public agencies, retail and consumer goods, automotive, and others.
Tariffs have influenced the data annotation and labeling market by increasing the cost of imported software platforms, automated annotation tools, and hardware required for processing large datasets. Regions such as North America, Europe, and Asia-Pacific, which rely on global vendors for annotation solutions, are most affected, particularly in BFSI, healthcare, ITES, and automotive sectors. Higher costs may delay deployment of manual, automatic, and semi-supervised annotation services. However, tariffs have also created opportunities for regional providers to innovate, develop local solutions, and offer cost-effective and scalable data annotation and labeling services.
The data annotation and labeling market research report is one of a series of new reports from The Business Research Company that provides data annotation and labeling market statistics, including data annotation and labeling industry global market size, regional shares, competitors with a data annotation and labeling market share, detailed data annotation and labeling market segments, market trends and opportunities, and any further data you may need to thrive in the data annotation and labeling industry. This data annotation and labeling market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenario of the industry.
The data annotation and labeling market size has grown exponentially in recent years. It will grow from $2.25 billion in 2025 to $2.98 billion in 2026 at a compound annual growth rate (CAGR) of 32.7%. The growth in the historic period can be attributed to rise in adoption of machine learning models, increasing volume of unstructured data, demand for high-quality labeled datasets, growth of AI applications in ites and bfs, adoption of manual annotation services.
The data annotation and labeling market size is expected to see exponential growth in the next few years. It will grow to $9.27 billion in 2030 at a compound annual growth rate (CAGR) of 32.8%. The growth in the forecast period can be attributed to integration of ai-powered annotation tools, growth in automated and semi-supervised annotation, increasing demand for multi-modal data labeling, expansion of annotation services in healthcare and automotive, development of domain-specific customized annotation solutions. Major trends in the forecast period include automated annotation solutions, crowd-sourced data labeling, quality assurance and validation, multi-modal data annotation, domain-specific annotation services.
The increasing usage of artificial intelligence (AI) and machine learning (ML) is expected to propel the growth of the data annotation and labeling market going forward. AI involves creating computer systems capable of performing tasks that typically require human intelligence, while ML focuses on algorithms that learn from data to predict, categorize, and automate processes without explicit programming. The growing use of AI and ML is driven by the explosion of data, as large and diverse datasets enable these technologies to improve accuracy, generate insights, and scale efficiently. Data annotation and labeling are essential for training AI and ML models, as labeled datasets allow algorithms to recognize patterns, anticipate outcomes, and perform tasks effectively. For instance, in October 2025, according to Netguru S.A., a Poland-based software development company, in 2024, the adoption of generative AI reached 71%, up sharply from 33% in 2023, reflecting rapid growth in business reliance on these advanced technologies. Therefore, the increasing adoption of AI and ML is driving the data annotation and labeling market.
Major companies operating in the data annotation and labeling market are focusing on products with technological upgrades such as structured data annotation tools to strengthen their position in the market. Structured data annotation tools are software applications that allow users to mark and tag structured data so that machine learning algorithms can identify and process it more easily. For instance, in March 2023, SciBite Limited, a UK-based company that offers a data annotation tool, launched Workbench. Workbench is a structured data annotation application that makes it easier to curate data using terminology and ontology standards. Workbench assists businesses with implementing a FAIR approach to data management, which ensures that data is findable, accessible, interrelated, and reusable. Data scientists and curators can correctly annotate data using Workbench's straightforward user interface, saving time and increasing replicability. Workbench also features a robust REST API that provides programmatic access to fundamental operations, allowing for integration into bespoke data curation workflows.
In August 2023, iMerit Inc., a US-based provider of AI data solutions, acquired Ango.AI for an undisclosed amount. The acquisition aims to combine iMerit's AI data expertise with Ango.ai's advanced data labeling technology, improving the development and efficiency of AI projects. This strategic move is designed to expand iMerit's technological capabilities, accelerate AI development, and strengthen its market position. Ango.AI is a Turkey-based platform that specializes in AI-supported data labeling.
Major companies operating in the data annotation and labeling market are Google LLC; Amazon Web Services Inc.; The International Business Machines Corporation; Oracle Corporation; Adobe Inc.; Allegion PLC; TELUS International; Appen Ltd; Scale AI Inc; CloudFactory Limited; Anolytics; CapeStart Inc.; Clickworker; DataPure Technologies; Amantya Technologies; Labelbox Inc.; LXT AI Inc.; Keylabs.AI LTD.; Dataloop AI; Precise BPO Solution; SuperAnnotate; Label Your Data; V7 Labs; Cogito Tech LLC; AI Data innovation; Sigma AI; LightTag; Datasur N.V.; Kili technology Corp.; Segment AI
North America was the largest region in the data annotation and labeling market in 2025. The regions covered in the data annotation and labeling market report are Asia-Pacific, South East Asia, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.
The countries covered in the data annotation and labeling market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Taiwan, Russia, South Korea, UK, USA, Canada, Italy, Spain
The data annotation and labeling market includes revenues earned by entities by providing services such as object detection, sentiment analysis, named entity recognition, and quality assurance for machine learning and AI model training datasets. The market value includes the value of related goods sold by the service provider or included within the service offering. Only goods and services traded between entities or sold to end consumers are included.
The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD unless otherwise specified).
The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.
Data Annotation and Labeling Market Global Report 2026 from The Business Research Company provides strategists, marketers and senior management with the critical information they need to assess the market.
This report focuses data annotation and labeling market which is experiencing strong growth. The report gives a guide to the trends which will be shaping the market over the next ten years and beyond.
Where is the largest and fastest growing market for data annotation and labeling ? How does the market relate to the overall economy, demography and other similar markets? What forces will shape the market going forward, including technological disruption, regulatory shifts, and changing consumer preferences? The data annotation and labeling market global report from the Business Research Company answers all these questions and many more.
The report covers market characteristics, size and growth, segmentation, regional and country breakdowns, total addressable market (TAM), market attractiveness score (MAS), competitive landscape, market shares, company scoring matrix, trends and strategies for this market. It traces the market's historic and forecast market growth by geography.
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