Global Data Labeling Software Market Growth (Status and Outlook) 2024-2030

Global Data Labeling Software Market Growth (Status and Outlook) 2024-2030

Data labeling software provides a tool set for businesses to turn unlabeled data into labeled data and build corresponding artificial intelligence algorithms. Within these tools, the user inputs a given dataset and the software provides a label through machine learning-assisted labeling, a human taskforce, or the user themselves.

The global Data Labeling Software market size is projected to grow from US$ 50 million in 2023 to US$ 160.3 million in 2030; it is expected to grow at a CAGR of 17.9% from 2024 to 2030.

LPI (LP Information)' newest research report, the “Data Labeling Software Industry Forecast” looks at past sales and reviews total world Data Labeling Software sales in 2023, providing a comprehensive analysis by region and market sector of projected Data Labeling Software sales for 2024 through 2030. With Data Labeling Software sales broken down by region, market sector and sub-sector, this report provides a detailed analysis in US$ millions of the world Data Labeling Software industry.

This Insight Report provides a comprehensive analysis of the global Data Labeling Software landscape and highlights key trends related to product segmentation, company formation, revenue, and market share, latest development, and M&A activity. This report also analyzes the strategies of leading global companies with a focus on Data Labeling Software portfolios and capabilities, market entry strategies, market positions, and geographic footprints, to better understand these firms’ unique position in an accelerating global Data Labeling Software market.

This Insight Report evaluates the key market trends, drivers, and affecting factors shaping the global outlook for Data Labeling Software and breaks down the forecast by Type, by Application, geography, and market size to highlight emerging pockets of opportunity. With a transparent methodology based on hundreds of bottom-up qualitative and quantitative market inputs, this study forecast offers a highly nuanced view of the current state and future trajectory in the global Data Labeling Software.

The future market trends of data labeling software are driven by the increasing demand for high-quality and reliable training data for various machine learning and artificial intelligence applications across different industries. Some of the key trends are:

The adoption of higher-speed and cloud-based data labeling software, which can handle large volumes of data and provide faster and more scalable solutions. These software can also leverage advanced technologies such as computer vision, natural language processing, and deep learning to automate and improve the accuracy and efficiency of data labeling tasks.

The growth of multi-modal and multi-task data labeling software, which can support different types of data (such as audio, image/video, text) and different types of labels (such as classification, segmentation, detection) in a single platform. These software can also enable cross-modal and cross-task learning, which can enhance the performance and generalization of machine learning models.

The emergence of human-in-the-loop and active learning approaches, which can combine the strengths of human intelligence and machine intelligence to optimize the data labeling process. These approaches can involve human feedback, verification, correction, or annotation to improve the quality and consistency of the labeled data. They can also use machine learning techniques to select the most informative and relevant data samples for labeling, reducing the time and cost of data collection and annotation.

The integration of artificial intelligence ethics and privacy principles into data labeling software, which can ensure the fairness, accountability, transparency, and security of the data labeling process. These principles can help users to avoid bias, discrimination, or harm in their data labeling tasks. They can also help users to protect the privacy and confidentiality of their data sources and subjects.

This report presents a comprehensive overview, market shares, and growth opportunities of Data Labeling Software market by product type, application, key players and key regions and countries.

Segmentation by type
Cloud-Based
On-Premises

Segmentation by application
Government
Retail and eCommerce
Healthcare and Life Sciences
BFSI
Transportation and Logistics
Telecom and IT
Manufacturing
Others

This report also splits the market by region:
Americas
United States
Canada
Mexico
Brazil
APAC
China
Japan
Korea
Southeast Asia
India
Australia
Europe
Germany
France
UK
Italy
Russia
Middle East & Africa
Egypt
South Africa
Israel
Turkey
GCC Countries

The below companies that are profiled have been selected based on inputs gathered from primary experts and analyzing the company's coverage, product portfolio, its market penetration.
AWS
Figure Eight
Hive
Playment
V7
Clarifai
CloudFactory
Labelbox
Alegion
BasicAI
Dataloop AI
Datasaur
DefinedCrowd
Diffgram
edgecase.ai
Heartex
LinkedAi
Lionbridge
Sixgill
super.AI
SuperAnnotate
Deep Systems
TaQadam
TrainingData.io

Please note: The report will take approximately 2 business days to prepare and deliver.