The Latin America, Middle East and Africa Data Annotation Tools Market is expected to witness market growth of 27.1% CAGR during the forecast period (2021-2027).
Organizations generate a huge amount of data by using advanced technologies like loT, ML, AI, robotics, and advanced predictive analytics. The emerging technologies increase the importance of data efficiency for making the latest business innovations, new economics, and infrastructure, which is expected to further surge the market growth. Due to the rising possibility of growth in data labeling, some companies which develop AI-enabled healthcare applications are teaming up with data annotation providers offering the needed data sets, which can help the companies to improve their machine learning & deep learning capabilities.
The lack of precision of data annotation tools is estimated to hamper the market growth. For example, a certain image can have low resolution and consists of various objects that create difficulty in labeling it. The major challenge possessed in the data annotation market is the inaccuracy in the quality of data labeled. There are certain cases in which the manually labeled data contains wrong labeling and the time to identify these faulty labels may vary that further increase the cost of the complete annotation process. Though, with the emerging sophisticated algorithms, the precision of automated data annotation tools is increasing and hence, decreasing the reliance on manual annotation & the cost of the tools in the coming years.
The increasing adoption rate of various new technologies in this region is driving the growth of the data annotation tools market. There are many companies in the Middle East, Africa, and Latin America, which are highly adopting emerging and advanced technologies that will significantly impact the growth of the data annotation tools market. Furthermore, the limited capital of several companies in this region is estimated to hamper the growth of the regional market.
However, companies are getting more aware of the importance of data annotation in a firm along with the wide range of benefits offered by data annotation tools. This is expected to further support the key market players to enter the market and acquire a significant share in it. Thus, all such factors are estimated to bolster the growth of the data annotation market in the LAMEA region.
The Text market dominated the South Africa Data Annotation Tools Market by Type 2020, and is expected to continue to be a dominant market till 2027; thereby, achieving a market value of $7.2 million by 2027. The Image/Video market is expected to witness a CAGR of 28.5% during (2021 - 2027).
Based on Type, the market is segmented into Text, Image/Video and Audio. Based on Annotation Type, the market is segmented into Manual, Semi-supervised and Automatic. Based on Industry, the market is segmented into IT, Automotive, Retail, Healthcare, Financial Services, Government and Others. Based on countries, the market is segmented into Brazil, Argentina, UAE, Saudi Arabia, South Africa, Nigeria, and Rest of LAMEA.
The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include Google, Inc., Amazon.com, Inc., Uber Technologies, Inc. (Mighty AI, Inc.), Appen Limited, Scale AI, Inc., Labelbox, Inc., Annotate Software, Cogito Tech LLC, Deep Systems, and Playment, Inc.
Scope of the Study
Market Segments covered in the Report:
By Type
By Annotation Type
By Industry
By Country
Companies Profiled
Unique Offerings from the Publisher
Organizations generate a huge amount of data by using advanced technologies like loT, ML, AI, robotics, and advanced predictive analytics. The emerging technologies increase the importance of data efficiency for making the latest business innovations, new economics, and infrastructure, which is expected to further surge the market growth. Due to the rising possibility of growth in data labeling, some companies which develop AI-enabled healthcare applications are teaming up with data annotation providers offering the needed data sets, which can help the companies to improve their machine learning & deep learning capabilities.
The lack of precision of data annotation tools is estimated to hamper the market growth. For example, a certain image can have low resolution and consists of various objects that create difficulty in labeling it. The major challenge possessed in the data annotation market is the inaccuracy in the quality of data labeled. There are certain cases in which the manually labeled data contains wrong labeling and the time to identify these faulty labels may vary that further increase the cost of the complete annotation process. Though, with the emerging sophisticated algorithms, the precision of automated data annotation tools is increasing and hence, decreasing the reliance on manual annotation & the cost of the tools in the coming years.
The increasing adoption rate of various new technologies in this region is driving the growth of the data annotation tools market. There are many companies in the Middle East, Africa, and Latin America, which are highly adopting emerging and advanced technologies that will significantly impact the growth of the data annotation tools market. Furthermore, the limited capital of several companies in this region is estimated to hamper the growth of the regional market.
However, companies are getting more aware of the importance of data annotation in a firm along with the wide range of benefits offered by data annotation tools. This is expected to further support the key market players to enter the market and acquire a significant share in it. Thus, all such factors are estimated to bolster the growth of the data annotation market in the LAMEA region.
The Text market dominated the South Africa Data Annotation Tools Market by Type 2020, and is expected to continue to be a dominant market till 2027; thereby, achieving a market value of $7.2 million by 2027. The Image/Video market is expected to witness a CAGR of 28.5% during (2021 - 2027).
Based on Type, the market is segmented into Text, Image/Video and Audio. Based on Annotation Type, the market is segmented into Manual, Semi-supervised and Automatic. Based on Industry, the market is segmented into IT, Automotive, Retail, Healthcare, Financial Services, Government and Others. Based on countries, the market is segmented into Brazil, Argentina, UAE, Saudi Arabia, South Africa, Nigeria, and Rest of LAMEA.
The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include Google, Inc., Amazon.com, Inc., Uber Technologies, Inc. (Mighty AI, Inc.), Appen Limited, Scale AI, Inc., Labelbox, Inc., Annotate Software, Cogito Tech LLC, Deep Systems, and Playment, Inc.
Scope of the Study
Market Segments covered in the Report:
By Type
- Text
- Image/Video
- Audio
By Annotation Type
- Manual
- Semi-supervised
- Automatic
By Industry
- IT
- Automotive
- Retail
- Healthcare
- Financial Services
- Government
- Others
By Country
- Brazil
- Argentina
- UAE
- Saudi Arabia
- South Africa
- Nigeria
- Rest of LAMEA
Companies Profiled
- Google, Inc.
- Amazon.com, Inc.
- Uber Technologies, Inc. (Mighty AI, Inc.)
- Appen Limited
- Scale AI, Inc.
- Labelbox, Inc.
- Annotate Software
- Cogito Tech LLC
- Deep Systems
- Playment, Inc.
Unique Offerings from the Publisher
- Exhaustive coverage
- Highest number of market tables and figures
- Subscription based model available
- Guaranteed best price
- Assured post sales research support with 10% customization free
Table of Contents
Chapter 1. Market Scope & Methodology
Chapter 2. Market Overview
Chapter 3. LAMEA Data Annotation Tools Market by Industry
Chapter 4. LAMEA Data Annotation Tools Market by Type
Chapter 5. LAMEA Data Annotation Tools Market by Annotation Type
Chapter 6. LAMEA Data Annotation Tools Market by Country
Chapter 7. Company Profiles
Companies Mentioned
- Google, Inc.
- Amazon.com, Inc.
- Uber Technologies, Inc. (Mighty AI, Inc.)
- Appen Limited
- Scale AI, Inc.
- Labelbox, Inc.
- Annotate Software
- Cogito Tech LLC
- Deep Systems
- Playment, Inc.
Methodology
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