Data Annotation Tools Market Analysis 2020-2026 by Top Players -Alegion, Appen Limited, Amazon Web Services, Clickworker, CloudApp, CloudFactory, Cogito, Google, Hive, IBM, iMerit, Labelbox, LionBridge AI, Mighty AI, MonkeyLearn, Neurala, Playment, Samaso

Global data annotation tools market derives much of its growth from the rising penetration of machine learning and artificial intelligence technologies in various industry verticals. These tools are witnessing extensive adoption in healthcare, telecom, agriculture industries.

Artificial intelligence has witnessed massive deployment in agricultural applications for semantic segmentation of videos & images using data labeling tools. These tools help farming robots in executing many real-time actions, including herbicide spraying, weed controlling, and automated monitoring of huge acreage farmlands.

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For example, in 2018, Cropin, an AgTech solutions provider collaborated with ITC Ltd., an Indian multinational conglomerate company, to digitally plan and annotate the imagery of farmlands expanded in around 24,000 acres across four states of India. This solution enabled the company to develop advanced solutions to deal with crop diseases and pest infestations. Data annotation tools market from the agriculture segment is projected to grow at a 30% CAGR over 2020-2026.

Company profiled in this report based on Business overview, Financial data, Product landscape, Strategic outlook & SWOT analysis:
1. Alegion Inc.
2. Appen Limited
3. Amazon Web Services
4. Clickworker
5. CloudApp Inc.
6. CloudFactory Limited
7. Cogito
8. Google
9. Hive
10. IBM
11. iMerit
12. Labelbox Inc.
13. LionBridge AI
14. Mighty AI
15. MonkeyLearn Inc.
16. Neurala Inc.
17. Playment Inc.
18. Samasource Inc.
19. Scale Inc.
20. Trilldata Technologies Pvt. Ltd.
21. Webtunix AI

The manual data annotation tools segment in data annotation tools market held a share of over 75% in 2019 owing to the improved quality of labeled data in comparison to automated data labeling. Typically, only skilled experts with strong expertise on the content and nature of data perform manual data labeling as human annotators could easily handle and detect even the smallest amounts of disparity in input data, that are likely to be missed by automated data labeling tools.

Additionally, manually labeled data is gaining traction due to developing AI algorithms that are applied in critical applications because of its accuracy and quality.

The data annotation tools market in text annotation tools segment is likely to observe an immense growth rate with a CAGR of nearly 35% between 2020 and 2026 since textual data labeling has become important for conducting sentiment analysis and for developing algorithms for document classification.

Furthermore, textual data annotation is also attaining importance for social media text mining since national security authorities and federal agencies examine the behavior of citizens for possible terrorist threats.

By using deep learning neural networks combined with solutions for text annotation, security agencies could also monitor threat topics as well as objectional material posted on social media handles.

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Speaking about the regional landscape, Europe data annotation tools market is likely to experience growth spurts across the Netherlands, Germany, and Nordic countries. These countries being the frontrunners in the implementation of AI and machine learning technologies provide lucrative opportunities for data annotation tools industry growth. Moreover, in Europe, business corporations have been amplifying focus on adoption of AI technologies. The European Commission has earmarked around $775 million for the development of AI-related projects under Horizon 2020 digital strategy. Europe data annotation tools market is likely to observe a CAGR of more than 30% over 2020-2026.

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