Generative Artificial Intelligence (AI) in Data Labeling Solution and Services Market Report 2024

This Generative Artificial Intelligence (AI) in Data Labeling Solution and Services market 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 generative artificial intelligence (AI) in data labeling solution and services market size has grown exponentially in recent years. It will grow from $12.46 billion in 2023 to $15.5 billion in 2024 at a compound annual growth rate (CAGR) of 24.4%. The growth during the historic period can be attributed to the rising demand for cost-effectiveness, increased investment in AI startups, a growing need for real-time data processing, heightened focus on data security, and an increasing emphasis on AI ethics.

The generative artificial intelligence (AI) in data labeling solution and services market size is expected to see exponential growth in the next few years. It will grow to $37.31 billion in 2028 at a compound annual growth rate (CAGR) of 24.6%. The projected growth during the forecast period can be attributed to the expansion of AI applications, the growth of e-commerce and digital platforms, advancements in AI research and development, increased support for low-resource languages and dialects, and customization for industry-specific needs. Key trends expected in this period include advanced data augmentation techniques, crowdsourcing enhanced by AI assistance, integration with machine learning operations (MLOps), improved object recognition capabilities, and the development of advanced natural language processing (NLP) models.

The increasing volume of data is anticipated to significantly drive the growth of the generative artificial intelligence (AI) in data labeling solutions and services market. This surge in data volume results from the widespread adoption of digital technologies that generate and collect vast amounts of information from diverse sources, including social media, IoT devices, and online transactions. Generative AI data labeling solutions and services address this growing volume by automating the creation of high-quality, annotated datasets. This automation accelerates the training of machine learning models while reducing the time and costs typically associated with manual labeling. For example, the UK Business Data Survey 2022 reported that 85% of UK businesses managed digital data in 2022, an increase from 81% in 2021, highlighting the growing reliance on data management.

Major companies in the generative AI data labeling solutions and services market are focusing on developing advanced solutions to enhance their data labeling capabilities and meet the rising demand. One such innovation is the implementation of in-house generative AI services, which involve systems or platforms developed and maintained internally to create and utilize AI models for generating content and data. A notable instance occurred in October 2023 when Sumitomo Chemical Co., Ltd., a Japan-based chemical manufacturer, launched ChatSCC. This platform is designed to boost productivity and optimize the utilization of proprietary data among its approximately 6,500 employees. It features real-time sentiment analysis within conversations, allowing users to gauge emotional tones and respond effectively, thereby enhancing engagement and communication.

In June 2024, TDCX, a Singapore-based provider of digital customer experience solutions, partnered with SUPA to improve the accuracy and efficiency of data labeling processes. This collaboration aims to empower companies to effectively train their AI models and unlock greater business value by integrating advanced technology with human expertise. SUPA, a Malaysia-based developer of data labeling platforms, utilizes generative AI in its solutions and services.

Major companies operating in the generative artificial intelligence (AI) in data labeling solution and services market are Microsoft Corporation, CloudFactory Limited, iMerit Technology Services Pvt. Ltd., Quantiphi Inc., Samasource Inc., Appen Limited, DataRobot Inc., Scale AI Inc., Cogito Technologies Pvt. Ltd., Clarify Inc., Osiz Technologies Private Limited, Clickworker GmbH, Snorkel AI Inc., Labelbox Inc., V7 Lab Inc., SuperAnnotate Inc., Dataloop AI Ltd., Prolific Ltd., Superb AI Inc., Roboflow Inc., Anolytics Inc., Datasaur, LabelMe, Nanonets Inc.

North America was the largest region in the generative artificial intelligence (AI) in data labeling solution and services market in 2023. The regions covered in the generative artificial intelligence (AI) in data labeling solution and services market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.

The countries covered in the generative artificial intelligence (AI) in data labeling solution and services market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

Generative artificial intelligence (AI) in data labeling solutions and services refers to the application of advanced AI models to assist in or automate the data labeling process. This approach utilizes sophisticated machine learning algorithms to automatically assign accurate labels to large volumes of data, thereby accelerating the labeling process and enhancing the overall quality and consistency of labeled datasets.

The primary types of generative artificial intelligence (AI) in data labeling solutions and services include audio-based, image or video-based, and text-based labeling. Audio-based generative AI refers to the use of AI models to automatically generate, transcribe, and label audio data for training machine learning algorithms, which improves the efficiency and accuracy of the annotation processes. Labeling methods can be categorized into automatic, manual, and semi-supervised approaches, with sourcing options available as in-house or outsourced. These solutions are employed across various industries, including automotive, financial services, government, healthcare, information technology (IT), retail, and others.

The generative artificial intelligence (AI) in data labeling solution and services market research report is one of a series of new reports that provides generative artificial intelligence (AI) in data labeling solution and services market statistics, including the generative artificial intelligence (AI) in data labeling solution and services industry's global market size, regional shares, competitors with a generative artificial intelligence (AI) in data labeling solution and services market share, detailed generative artificial intelligence (AI) in data labeling solution and services market segments, market trends and opportunities, and any further data you may need to thrive in the generative artificial intelligence (AI) in data labeling solution and services industry. This generative artificial intelligence (AI) in data labeling solution and services 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 generative artificial intelligence (AI) in data labeling solution and services market consists of revenues earned by entities by providing services such as automated labeling, synthetic data generation, data augmentation, annotation assistance, and error detection and correction. 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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