Market Definition
Data annotation tools are software programs that allow users to label and categorize data for machine learning algorithms. The most common types of data annotation tools are image annotation tools and video annotation tools. Image annotation tools allow users to label images for object detection, classification, and segmentation tasks. Video annotation tools allow users to label video data for tasks such as action detection and recognition.
Market Outlook
The growing importance of high-quality and well-labeled input data for augmenting the accuracy of machine learning algorithms is likely to drive the industry growth. Data annotation tools are highly suited for situations where unlabeled data is available in large volumes and will create new opportunities for the market expansion. Moreover, increasing need for data annotation tools to support the increasing volume of data coupled with the increasing number of data annotation tool providers.
One of the key restraints in the data annotation tools market is the need for high initial investment. Data annotation tools require significant investment in terms of hardware, software, and trained personnel. In addition, data annotation is a time-consuming process, which can further increase the overall cost. Another key challenge in the data annotation tools market is the lack of skilled personnel. Data annotation is a highly technical process that requires trained personnel to achieve desired results. The lack of skilled personnel can hamper the adoption of data annotation tools, especially in small and medium enterprises.
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Research Objectives
- Estimates and forecast the overall market size for the total market, across product, service type, type, end-user, and region
- Detailed information and key takeaways on qualitative and quantitative trends, dynamics, business framework, competitive landscape, and company profiling
- Identify factors influencing market growth and challenges, opportunities, drivers and restraints
- Identify factors that could limit company participation in identified international markets to help properly calibrate market share expectations and growth rates
- Trace and evaluate key development strategies like acquisitions, product launches, mergers, collaborations, business expansions, agreements, partnerships, and R&D activities
- Thoroughly analyze smaller market segments strategically, focusing on their potential, individual patterns of growth, and impact on the overall market
- To thoroughly outline the competitive landscape within the market, including an assessment of business and corporate strategies, aimed at monitoring and dissecting competitive advancements.
- Identify the primary market participants, based on their business objectives, regional footprint, product offerings, and strategic initiatives
Market Segmentation
The report analyses the global Data Annotation Tools market based on Data Type, Annotation Approach, Application and Region.
Global Data Annotation Tools Market by Data Type
By data type, the market is segmented into image/video, text, and audio. The image/video segment accounted for significant market share in 2021 and is expected to register lucrative CAGR over the forecast period. This is attributed to the increasing uptake of data annotation tools for labeling image/video to improve entity recognition. With the continuously evolving machine learning landscape in the region, data annotation tool vendors are developing new technologies for improving the accuracy of annotated images/videos and delivering high precision datasets for AI-based applications.
Global Data Annotation Tools Market by Annotation Approach
By annotation approach, the data annotation tools market is classified into manual annotation, and automated annotation. The manual annotation segment accounted for significant revenue in 2022. This is due to surging adoption to ensure high-quality input data. Manually labeled data is less prone to errors due to the involvement of highly trained domain experts, who can handle complex data labeling scenarios, where machine-based algorithms would perform poorly. Medical image labeling requires the expertise of specialist medical professionals in cases where the machine learning systems cannot accurately label the data. Data annotation service providers in the China are offering innovative data labeling services & annotated healthcare training data validated by medical experts to strengthen their market presence and add value to their offerings. As enterprises focus strongly on developing new & innovative solutions to cater to the growing demand, the market will witness a sharp expansion.
Global Data Annotation Tools Market by End-use
The end-use segment of the market is bifurcated into IT & telecom, BFSI, healthcare, retail, automotive, agriculture, and others. The automotive are expected to register highest CAGR between 2023 and 2032. the automotive manufacturers are transitioning toward leveraging AI for developing self-driving vehicles and connected cars. A gradual shift of the U.S. automotive industry toward full autonomy has been fueled with the development in AI and ML technologies, which make heavy use of labeled data to deploy self-driving mechanisms. The accurately labeled data assists on-board AI to make instantaneous decisions during complex road situations, avoiding major accidents and object collision. For instance, in December 2021, Tesla launched a new auto labeling tool for its self-driving vehicles. The auto labeling tool is able to use an extensive data set to improve its neural nets powering suite of autopilot feature. As automotive enterprises gradually acknowledge the benefits of high-quality labeled data to develop reliable onboard AI, the market will undergo a rapid growth.
Geographical Analysis of Global Data Annotation Tools MarketRegion-wise, it is studied across North America, Europe, Asia Pacific, and the Rest of the World. Asia Pacific data annotation tools market revenue is poised to grow significant CAGR during the forthcoming years. Rapid growth of IT infrastructure, increasing number of data labeling start-ups, and wide-scale adoption of AI technologies have accentuated the regional market growth. With improvement in ICT landscape, abundance of skilled workforce, and increasing awareness regarding reliable training data among AI-related SMEs, the region is projected to become a major potential market. For instance, in June 2021, ByteBridge launched the world’s first mobile 3D cloud point data labeling service, which is the collaboration of various dots spread around 3D space. It is widely used for product development & analysis in aerospace, traffic, and others.
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Major Players
The key players in the Data Annotation Tools market Annotate.com, Appen Limited, CloudApp, Cogito Tech LLC, Deep Systems, Labelbox, Inc., LightTag, Lotus Quality Assurance, Playment Inc., and Tagtog Sp. z o.o. among others.
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Research Scope
- Scope – Highlights, Trends, Insights. Attractiveness, Forecast
- Market Sizing – Product Type, End User, Offering Type, Technology, Region, Country, Others
- Market Dynamics – Market Segmentation, Demand and Supply, Bargaining Power of Buyers and Sellers, Drivers, Restraints, Opportunities, Threat Analysis, Impact Analysis, Porters 5 Forces, Ansoff Analysis, Supply Chain
- Business Framework – Case Studies, Regulatory Landscape, Pricing, Policies and Regulations, New Product Launches. M&As, Recent Developments
- Competitive Landscape – Market Share Analysis, Market Leaders, Emerging Players, Vendor Benchmarking, Developmental Strategy Benchmarking, PESTLE Analysis, Value Chain Analysis
- Company Profiles – Overview, Business Segments, Business Performance, Product Offering, Key Developmental Strategies, SWOT Analysis
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