Data Annotation and Labelling Market is expected to generate revenue of USD 29,584.2 Mn by 2033, at 34.4% CAGR: Dimension Market Research

New York, Sept. 04, 2024 (GLOBE NEWSWIRE) -- Overview

The Global Data Annotation and Labelling Market is expected to reach USD 2,072.2 million in 2024 which is further projected to grow up to USD 29,584.2 million by the end of 2033, growing at a CAGR of 34.4%.

The global data annotation and labelling market is rapidly expanding as industries adopt AI-powered models through supervised machine learning. Data annotation, crucial for training AI models in applications like NLP, image and video recognition, and sentiment analysis, is segmented by component, data type, deployment, organization size, annotation, vertical, and application.

Text annotation leads due to NLP applications. While cloud deployment grows, on-premise solutions remain vital for data privacy. Large enterprises dominate due to robust data management needs.

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The US Data Annotation and Labelling Market

The US data annotation and labelling market is projected to be valued at USD 838.2 million in 2024 and is further projected to reach USD 10,346.2 million by 2033, growing at a CAGR of 32.2%.

This growth is driven by the rapid adoption of AI and machine learning across sectors like healthcare, automotive, and finance. Trends include a preference for cloud-based solutions. Opportunities are prominent in healthcare for developing diagnostic tools. Recent developments include Appen's acquisition of Quadrant, Scale AI's partnership with Nvidia, and iMerit's new medical annotation tools.

Important Insights

• Market Size: The Global Data Annotation and Labelling Market is estimated to be valued at USD 2,072.2 million in 2024 and is projected to reach USD 29,584.2 million by 2033.
• The US Market Size: The US market, a significant contributor, is expected to grow from USD 838.2 million in 2024 to USD 10,346.2 million by 2033, at a CAGR of 32.2%.
• By Solution: Solutions are expected to dominate the component segment, holding 63.1% of the market share in 2024.
• By Data Type: Text data is anticipated to lead the market within the data type segment in this market with a 56.0% share in 2024.
• By Deployment: On-premise deployment is projected to dominate the deployment segment, holding the highest market share in 2024.
• By Organization Size: Large enterprises are expected to dominate the market, possessing the highest market share in 2024.
• Regional Analysis: North America is expected to have the largest market share of the global annotation and labelling market, about 48.1% of the market share in 2024.
• Growth Rate: The global market is growing at a CAGR of 34.4% over the forecast period.

Latest Trends

• AI Integration: One of the most significant changes in the field of data annotation is that AI-powered annotation tools are entering the market to enhance the standard annotation process with the help of sophisticated algorithms. Such trends are emerging as more organizations look forward to managing and processing more data in a real-time manner, especially for labelling that is critical for use in applications such as self-driving cars and real-time video analysis.
• Cloud Adoption: Remote centralized data annotation services are becoming popular day by day mainly because they are easily accessible, flexible and also considerably cheaper. These platforms accommodate remote work and simple data processing and storage demands as they can support practically infinite processing power and data storage.

Data Annotation and Labelling Market: Competitive Landscape

• The global data annotation and labelling market is highly fragmented, featuring major players like Appen, Lionbridge, and Scale AI, which offer comprehensive services across text, image, video, and audio data. These leaders invest heavily in R&D to enhance their AI and machine learning capabilities and frequently engage in mergers and acquisitions, such as Appen’s acquisition of Figure Eight Inc., to strengthen their market position.
• The market also includes numerous smaller, specialized firms that provide niche annotation services tailored to specific industry needs, intensifying competition and diversifying service offerings.

Some of the prominent market players:

• Google
• IBM
• Oracle
• TELUS International
• Adobe
• AWS
• Cogito Tech
• Anolytics
• AI Data Innovation
• Clickworker
• Sigma
• Segment.ai
• Defined.ai
• Dataloop
• Understand.ai
• Other Key Players

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Data Annotation and Labelling Market Scope

Growth Drivers

• Big Data Proliferation: Microtasks involved in data labelling, primarily required for big data originating from social media and IoT devices, create demand for accurate data annotation for AI and a variety of applications of machine learning. It underlines the necessity of effective annotation approaches as the amount of data and its variety grows.
• AI and ML Advancements: AI and machine learning development increases the necessity for better quality of annotated data. However, as models such as deep learning emerge, there is a prerequisite of having quality annotated data to enhance the outlook of increasing accuracy and performance.

Restraints

• Data Privacy Concerns: The higher level of risk in the protection of individual data and information may hamper market growth, particularly by the use of cloud service. Some of these solutions may not be readily implemented in organizations especially in the health and or financial sector because of challenges of compliance and data privacy.
• High Costs: The use of big data in decision-making is hindered by the high cost of data annotation, especially by manual means. Manual annotations are tiresome and can be very expensive when working on large projects since they have to be done by professional annotators, although in recent years, technology has lowered the costs, the actual investment in the best technologies, however, is capital intensive and may act as a limiting factor to the market penetration.

Growth Opportunities

• Healthcare Sector: It is evidenced that the healthcare area has a high potential, as the annotated data is necessary for using artificial intelligence methods to diagnose ailments and select an individual therapy approach. This growing need can be particularly served by specialized organizations dealing with annotation services.
• Automotive Industry: The automotive industry as a whole, especially with self-driven cars, has benefited greatly from annotated data especially when it comes to object recognition, analyzing traffic patterns, and making decisions. Further advancements in data annotation used in autonomous driving result in improving the safety and performance of the vehicle.

Market Analysis

Solutions are set to dominate the component segment with a 63.1% market share in 2024. Software platforms and toolkits play a crucial role by automating and streamlining data annotation tasks. These solutions, including AI-driven annotation tools and automated algorithms, enhance efficiency and reduce manual intervention in large-scale data projects.

Toolkits offer scalable modules tailored to diverse industry needs, while software platforms facilitate end-to-end data management. The growing need for high-quality data to train machine learning models and the shift toward AI in industries like healthcare and automotive drive the robust demand for these solutions.

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Data Annotation and Labelling Market Segmentation

By Component

• Solution
  • Software Platforms
  • Toolkits
• Services
  • Managed Services
  • Professional Services
    • Consulting
    • Training & Support
    • Implementation & Integration

 By Data Type

• Text
  • Natural Language Processing (NLP)
  • Named Entity Recognition (NER)
  • Sentiment Analysis
  • Document Classification
• Image
  • Object Detection
  • Image Classification
  • Image Segmentation
  • Facial Recognition
• Video
  • Video Classification
  • Activity Recognition
  • Object Tracking
  • Scene Detection
• Audio
  • Speech Recognition
  • Sound Classification
  • Speaker Identification
  • Audio Transcription

By Deployment Type

• On-Premise
• Cloud

By Organization Size

• Large Enterprise
• SMEs

By Annotation Type

• Manual
  • Human-in-the-Loop (HITL)
  • Crowdsourcing Platforms
• Automatic
  • AI-Driven Annotation Tools
  • Automated Labeling Algorithms
• Semi-Supervised
  • Hybrid Methods
  • Active Learning
  • Weak Supervision

By Application

• Dataset Management
• Security and Compliance
• Data Quality Control
• Workforce Management
• Content Management
• Catalogue Management
• Sentiment Analysis
• Other Applications

By Vertical

• BFSI
• IT and ITES
• Healthcare & Life science
• Telecom
• Government, Defense and Public Agencies
• Retail and Consumer Goods
• Automotive
• Other Verticals

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Regional Analysis

North America is projected to lead the global data annotation and labelling market with a 48.1% share in 2024. Key factors include the region's concentration of major technology firms and startups utilizing AI and ML, robust IT infrastructure, and significant investment in AI advancements.

Additionally, North America's strong data protection policies and high demand for annotated data in sectors like healthcare, automotive, finance, and retail drive market growth. Strategic collaborations, mergers, and acquisitions further bolster North America's dominance.

By Region

North America

• The U.S.
• Canada

Europe

• Germany
• The U.K.
• France
• Italy
• Russia
• Spain
• Benelux
• Nordic
• Rest of Europe

Asia-Pacific

• China
• Japan
• South Korea
• India
• ANZ
• ASEAN
• Rest of Asia-Pacific

Latin America

• Brazil
• Mexico
• Argentina
• Colombia
• Rest of Latin America

Middle East & Africa

• Saudi Arabia
• UAE
• South Africa
• Israel
• Egypt
• Rest of MEA

Recent Developments in the Data Annotation and Labelling Market

• July 2024: Appen acquired Quadrant, boosting its location-based data annotation capabilities for applications like mapping and navigation.
• June 2024: Scale AI partnered with Nvidia to enhance the annotation of large-scale video datasets for autonomous vehicles using advanced GPU technology.
• May 2024: Lionbridge upgraded its AI training data platform with new automation tools to improve data quality and streamline the annotation process.
• April 2024: iMerit launched advanced annotation tools for medical images, using AI to assist in accurate labelling for diagnostics and treatment.
• March 2024: AWS introduced a new data annotation service within its SageMaker platform, offering tools for NLP and computer vision tasks.

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