The global data collection and labeling market size is expected to reach USD 30.49 billion by 2032, according to a new study by Polaris Market Research. The report “Data Collection and Labeling Market Size, By Data Type (Audio, Image/ Video, Text); By Vertical (IT, Automotive, Government, Healthcare, BFSI, Retail & E-commerce, Others); By Region; Segment Forecast, 2023 - 2032” gives a detailed insight into current market dynamics and provides analysis on future market growth.
Data collection and labeling are being increasingly adopted due to the increasing adoption of artificial intelligence (AI) and machine learning (ML) technology in various industries. The demand for highly accurate and well-labeled datasets for training AI and ML models is driving the growth of the market. For example, the healthcare industry relies heavily on image and voice data to develop and train machine-learning models for diagnostic automation, gene sequencing, and treatment prediction. Companies like DefinedCrowd provide data labeling services that help create highly accurate training data for voice recognition models.
Additionally, the increasing focus on the development of cloud-based platforms for data collection and labeling allows for remote data collection and labeling, providing flexibility and scalability to companies. For instance, Appen, a provider of data collection and labeling services, offers a cloud-based platform that enables remote data labeling, improving efficiency and reducing costs. Moreover, the rise of e-commerce and digital shopping has led to a surge in data collection for annotation, driving the growth of the market.
COVID-19 pandemic has both positively and negatively impacted the market. The surge in online activities has increased demand for data labeling services, especially in the healthcare industry. Remote work and cloud-based technologies have also accelerated, leading to increased demand for remote data collection and labeling services. However, budget cuts in industries such as retail and automotive have reduced demand for data collection and labeling services in those areas. Overall, the pandemic has emphasized the importance of accurate and efficient data collection and labeling services for AI models.
Do you have any questions? Would you like to request a sample or make an inquiry before purchasing this report? Simply click the link below: https://www.polarismarketresearch.com/industry-analysis/data-collection-and-labeling-market/request-for-sample
In March 2023, Appen, a leading provider of high-quality data for AI, announced the launch of three new products in March 2023, including Reinforcement Learning with Human Feedback, Document Intelligence, & Automated NLP Labeling. In January 2023, Amazon Web Services (AWS) launched Amazon SageMaker, a new data labeling service that uses machine learning to automate data labeling tasks. It reduces the time and effort required to label large datasets, allowing businesses to train their AI models more efficiently and effectively.
Data Collection and Labeling market Report Highlights
Polaris Market Research has segmented the Data Collection and Labeling market report based on data type, vertical and region:
Data Collection and Labeling, Data type Outlook (Revenue, USD Billion, 2019 - 2032)
Data Collection and Labeling, Vertical Outlook (Revenue, USD Billion, 2019 - 2032)
Data Collection and Labeling, Regional Outlook (Revenue - USD Billion, 2019 - 2032)
Data Collection and Labeling Market Report Scope
Report Attributes |
Details |
Market size value in 2023 |
USD 3.17 billion |
Revenue forecast in 2032 |
USD 30.49 billion |
CAGR |
28.6% from 2023- 2032 |
Base year |
2022 |
Historical data |
2019 - 2021 |
Forecast period |
2023- 2032 |
Quantitative units |
Revenue in USD billion and CAGR from 2023 to 2032 |
Segments covered |
By Data Type, By Vertical, By Region |
Regional scope |
North America, Europe, Asia Pacific, Latin America; Middle East & Africa |
Key companies |
Lionbridge, Appen, Amazon Mechanical Turk, Labelbox, Scale AI, CloudFactory, Cognizant, HCL Technologies, Infosys, Tech Mahindra, Wipro, iMerit, Playment, SuperAnnotate, Samasource. |
For Specific Research Requirements |