Data Annotation and Labeling Market Report 2025

This report covers market characteristics, size and growth, segmentation, regional and country breakdowns, competitive landscape, market shares, trends and strategies for this market. It traces the market’s historic and forecast market growth by geography.

The data annotation and labeling market size has grown exponentially in recent years. It will grow from $1.7 billion in 2024 to $2.26 billion in 2025 at a compound annual growth rate (CAGR) of 32.5%. The growth in the historic period can be attributed to increased accessibility of cloud-based data annotation services, emergence of crowdsourcing platforms.

The data annotation and labeling market size is expected to see exponential growth in the next few years. It will grow to $7.01 billion in 2029 at a compound annual growth rate (CAGR) of 32.8%. The growth in the forecast period can be attributed to increasing use of ML and AI, emergence of IoT, increasing cloud-based solutions. Major trends in the forecast period include product innovations, technological advancements, strategic partnerships.

The increasing usage of artificial intelligence and machine learning is expected to propel the growth of the data annotation and labeling market going forward. Artificial intelligence involves creating computer systems to perform tasks requiring human intellect, while machine learning focuses on algorithms learning from data to predict, categorize, and automate processes without explicit coding for each task. Data annotation and labeling in machine learning and artificial intelligence are critical for training algorithms because they provide labeled datasets that allow machine learning models to spot patterns, anticipate outcomes, and perform jobs effectively. For instance, in May 2022, according to the International Business Machines Corporation, a US-based technological company, approximately a third of organizations (35%) reported utilizing artificial intelligence in their operations, up four points from 2021. In 2022, there was a 13% rise in the chance of firms implementing AI relative to the previous year (2021). Similarly, in July 2023, according to Earthweb Inc., a US-based independent technology research blog, 48% of companies used deep learning, or machine learning, to make good use of massive amounts of data. Therefore, the increasing usage of artificial intelligence and machine learning 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 2024. The regions covered in the data annotation and labeling market report are Asia-Pacific, 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, 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).

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.

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.

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.

This product will be delivered within 3-5 business days.