The Global Data Labeling Market is growing at a rate of 28.4% CAGR and is expected to reach 3.5 billion USD by 2026. Hence, most of the brands are outsourcing data labeling services to create robust machine-learning models.

Data labeling is the manual solution for machine learning and artificial intelligence application data with the help of humans. Labeling data is crucial because computers have multiple shortcomings and some of them cannot be overcome without human assistance. A machine can be trained potentially for performing complex calculations and manage tasks that would be strenuous for humans to handle manually, but the same cannot spot the difference between a dog’s or a car’s picture without proper training.

Machines utilize a dataset-based algorithm for understanding what normally involves someone to supervise. This phenomenon is known as supervised machine learning. On the basis of data type, the market is segmented into text, image, video, or Audio and also based on End-user, Retail & Ecommerce, Healthcare, Government, Automotive, and others.

The Rise of Data Labeling & Annotation Tools

Data Annotation tools assist in the crucial improvement of the training data used by smart AI models which allow them to address complex data challenges. Therefore, the market for data annotation tools is witnessing thriving growth as the organizations are deploying these data labeling & annotation technologies.

For example, data labeling tools have enabled automotive manufacturers in the field of smart applications for vehicle to vehicle communication (V2X) and connected car technologies like speech recognition & Natural Language Processing (NLP). Therefore Data annotation tool providers are focusing on developing specialized techniques for facilitating the automation of 2D and 3D annotation for LiDar data and sensors.

The Growing Demand for Data Labeling in Various Sectors

Data labeling will play a significant role in multiple industries and various sectors. For instance, in healthcare, medical imaging makes use of computer vision technology to predict the patterns and detect disease and injury. Data annotation tools help training AI systems in differentiating data among medical images which includes magnetic resonance imaging (MRI), X-ray, or CT scan Images. Also, studies have found out that after the entry of AI into the healthcare sector, error rates have decreased by 15%.

Another area is the cloud advent services and a surge in mobile devices where multiple data processing technologies have emerged. Some of them are data annotation, multilingual speech transcription, and data classification. Several technologies are being introduced to reduce the dependency on manual processing or human efforts.

Regional Insights of the Global Data Labeling Market

Back in 2020, North America dominated the market accounting for more than 38% of the global share. This remained to be one of the most rapid growth of cloud-based services and one of the potential sources of data collection.

The growth of the North American segment is attributed to the rising hub of AI & mobile computing platforms in the sector of e-commerce. Europe is also expected to grow beautifully in this forecast period and advance in the automobile sector.

At the same time, Asia Pacific is expected to reach the peak of highest CAGR in this period. A growing number of smart devices will ultimately boost the need for data labeling as well as annotations. Due to the rapid technological developments and increasing use of mobiles and social networks, data labeling market will be in a boom.

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