Data Annotation and Labeling Global Market Report 2024

The data annotation and labeling market size has grown exponentially in recent years. It will grow from $1.28 billion in 2023 to $1.7 billion in 2024 at a compound annual growth rate (CAGR) of 32.9%. The expansion observed during the historical period can be attributed to several factors, including the increased accessibility of cloud-based data annotation services and the 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 $5.27 billion in 2028 at a compound annual growth rate (CAGR) of 32.6%. The projected growth in the forecast period can be attributed to several factors, including the increasing adoption of machine learning (ML) and artificial intelligence (AI), the emergence of the Internet of Things (IoT), and the rising utilization of cloud-based solutions. Major trends expected in this forecast period include product innovations, technological advancements, and strategic partnerships within the industry.

The upward trajectory of the data annotation and labeling market is strongly propelled by the escalating adoption of artificial intelligence (AI) and machine learning (ML). AI involves the development of computer systems capable of executing tasks that traditionally necessitate human intellect, while ML revolves around algorithms learning from data to forecast, categorize, and automate processes without explicit programming for each task. Data annotation and labeling play a pivotal role in ML and AI by furnishing labeled datasets, enabling ML models to discern patterns, forecast outcomes, and execute tasks proficiently. For instance, as of May 2022, reports from the International Business Machines Corporation revealed that approximately 35% of organizations incorporated AI into their operations, marking a four-point increase from 2021. Moreover, between 2021 and 2022, there was a notable 13% surge in the likelihood of firms adopting AI technology. Similarly, in July 2023, findings from Earthweb Inc. indicated that 48% of companies leveraged deep learning or ML to effectively harness vast volumes of data. Consequently, the burgeoning utilization of AI and ML is instrumental in propelling the growth of the data annotation and labeling market.

Prominent players within the data annotation and labeling market are strategically focusing on technologically enhanced products, particularly structured data annotation tools, to bolster their market stance. These tools, designed to facilitate the marking and tagging of structured data, streamline the process for ML algorithms to recognize and process information more efficiently. For instance, in March 2023, SciBite Limited, a UK-based entity specializing in data annotation solutions, unveiled "Workbench." This structured data annotation application simplifies data curation through the utilization of standardized terminologies and ontologies. Workbench empowers businesses to adopt a FAIR approach to data management, ensuring that data remains findable, accessible, interrelated, and reusable. Equipped with an intuitive user interface, data scientists and curators can accurately annotate data, thus optimizing time efficiency and enhancing replicability. Additionally, Workbench incorporates a robust REST API, furnishing programmatic access to essential operations and facilitating seamless integration into bespoke data curation workflows.

In July 2021, TELUS International, a Canadian technology firm specializing in innovative solutions for leading global brands, completed the acquisition of Playment for an undisclosed sum. This strategic move enables TELUS International to leverage the increasing need for data annotation services across diverse sectors such as healthcare, retail, and autonomous vehicle innovation. Playment, headquartered in India, provides cutting-edge data labeling infrastructure and solutions, facilitating organizations in expediting their machine learning initiatives.

Major companies operating in the data annotation and labeling market report 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 2023. 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.

Data annotation and labeling are essential procedures in machine learning and artificial intelligence, involving manually or automatically assigning tags or labels to data points for training models. Data annotation is the process of adding metadata or labels to raw data to make it understandable and usable by machine learning algorithms, whereas Labeling is a subset of data annotation in which categorical or numerical labels are assigned to data points to indicate their class, category, or value.

The primary components of data annotation and labeling consist of solutions and services. Solutions refer to techniques or procedures employed to address problems or meet requirements. They encompass various data types such as text, images, videos, and audio, along with different annotation methods including manual, automatic, and semi-supervised approaches. These solutions find application across a wide range of areas including dataset management, security and compliance, data quality control, workforce management, content management, catalog management, sentiment analysis, and more. They are utilized by diverse end-users including banking, financial services, and insurance (BFSI), information technology and information technology-enabled services (ITES), healthcare and life sciences, telecommunications, government defense and public agencies, retail and consumer goods, automotive, and others.

The data annotation and labeling market research report is one of a series of new reports that provides data annotation and labeling market statistics, including data annotation and labeling industry global market size, regional shares, competitors with 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 scenarios of the industry.

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.


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