The market value of the data annotation tool is expected to reach the US dollar

LOS ANGELES, Aug. 02, 2021 (GLOBE NEWSWIRE) — The Global Data Annotation Tools Market is expected to grow at a CAGR of approximately 34.5% from 2021 to 2028 and reach approximately US$8.0 billion by 2028.

North America dominates the market for data annotation tools; Asia Pacific to Record Fastest Growing CAGR

North America has held the lion’s share of the data annotation tools market in the past and is expected to do so again during the forecast period. The rapid product expansion based on geography is attributed to the growth, which is widely adopted by major players residing in this region to grow and gain a competitive advantage in the regional market. This is one of the most significant factors driving the growth of the data annotation tools market.


Asia-Pacific, on the other hand, is expected to have the fastest growing CAGR in the data annotation tools market. The market for data annotation tools in the Asia-Pacific region is growing rapidly due to the widespread adoption of advanced technologies, especially in the healthcare and financial services industries. As the healthcare industry gains popularity in APAC, the demand for data annotation tools will also increase, which will rise at a record CAGR in the coming years.

Impact of COVID-19 on the Global Data Annotation Tools Market

The COVID-19 pandemic has affected all aspects of society globally. Strict government regulations imposed globally to combat the spread of the corona virus have led to supply chain disruption. In addition, the nationwide lockdown and temporary shutdown of production units related to the pandemic has led to a decrease in labor on the supply side and a decrease in demand for several products and services around the world. These strict restrictions are having a negative impact on the data annotation tools market. It is estimated that as the economy gets back on track, the data annotation tools market will register significant demand globally.


Sector outlook

The global data annotation tools market is segmented into type, annotation type, and vertical. Based on type, the market is segmented into text, image/video, and audio. By annotation type, the market is segregated into manual, semi-supervised, and automatic. Based on the vertical, the market is segmented into IT, automotive, government, healthcare, financial services, retail, and others.

By type of annotation, manual segment dominates the global data annotation tools market. Additionally, based on the vertical, IT segment is dominating the global data annotation tools market with major revenue share. The text segment will dominate the global data annotation tools market in terms of type.

Competitive landscape

Major players of data annotation tool are, CloudApp, Appen Limited, Deep Systems, Cogito Tech LLC, Labelbox, Inc., Playment, etc.

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Some of the key observations about the data annotation tool include:

  • In February 2021, Appen Limited announced enhanced capabilities that ensure autonomous vehicle manufacturers have access to high-quality training data and can get the most out of training data investment.
  • In July 2021, TELUS International announced the acquisition of Playment, a leader in data annotation and computer vision tools and services specializing in 2D and 3D image, video and LiDAR technologies. With this acquisition, the TELUS International team will harness the full potential of computer vision technology and advance the shared mission of accelerating the age of AI through numerous partnerships with brands present at the global scale.
  • In February 2021, NextBillion AI announced a partnership with Google Cloud for the deployment of data pipelines. As NextBillion AI is an industry-leading startup involved in deploying a platform used for mapping that offers software as a service (SaaS) for businesses.
  • In November 2017, Appen Limited announced that it had entered into a definitive agreement to acquire Leapforce Inc. to enhance its expertise in artificial intelligence and machine learning with high quality human annotated data.



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