全球资料收集和标籤市场规模（按类型、应用、区域范围）预测至 2025 年

资料收集和标籤市场规模及预测

2024 年资料收集和标籤市场规模价值 181.8 亿美元，预计到 2032 年将达到 933.7 亿美元，在 2026-2032 年预测期内的复合年增长率为 25.03%。

资料收集和标记涉及获取原始资料并对其进行註释，以用于机器学习和人工智慧应用。这项技术可确保资料集的结构化和准确性，从而使电脑能够有效率地学习。图像、文字和音讯是各行各业智慧系统开发中常用的资料类型。

在实践中，收集和标记资料对于医疗保健、银行和自动驾驶汽车等行业的模型训练至关重要。提供高品质的学习输入可以提高人工智慧应用程式的效能。工具和系统正在逐步实现这一过程的自动化，在提高数据品质的同时节省时间和精力。

随着人工智慧和机器学习应用的日益普及，对资料收集和标记的需求也将日益增长。自动註释和合成资料合成是简化此流程的两项创新。这项发展将使企业能够更有效地利用数据，增强决策能力，并推动各领域的创新。

数据收集和标籤的全球市场动态

影响全球数据收集和标籤市场的关键市场动态是：

关键市场驱动因素

对人工智慧和机器学习的依赖日益增加：随着人工智慧和机器学习在众多行业中的普及，对可靠数据收集和分类的需求也日益增长。到2025年，人工智慧产业规模预计将达到1,260亿美元，凸显了高品质资料集对于有效建模的重要性。

更重视资料隐私和合规性：GDPR 和 CCPA 等更高要求要求企业优先考虑确保隐私和合规性的资料收集方法。预计到 2023 年，全球资料隐私产业规模将成长至 67 亿美元，凸显了在标籤流程中采取负责任的资料处理实务的必要性。

高阶资料註解工具的兴起：高阶资料註解工具的兴起源自于技术进步，这些进步能够提高效率并降低成本。全球数据註释工具市场预计将显着增长，因为它能够促进更快、更准确的数据标记，这对于满足日益增长的人工智慧应用需求至关重要。

主要问题

确保数据品质和准确性：保持高准确性是数据收集和标记过程中最艰鉅的挑战之一。标记不良的数据可能会损害人工智慧模型的效能。确保大型资料集（尤其是照片和音讯等复杂资料类型）的质量，需要大量的人工监控和严格的通讯协定。

资料标註的可扩展性：AI 模型需要大量标註数据，这使得标註流程难以扩展。手动标註耗时耗力，在保持高效能的同时满足日益增长的数据需求是一项挑战，尤其对于需要特定领域知识的复杂数据集。

资料隐私问题：随着《一般资料保护规范》(GDPR) 和《加州消费者隐私法案》(CCPA) 等资料隐私法规的不断增多，在保护敏感资讯的同时收集和分类资料已成为一项重大挑战。企业必须兼顾法律要求，并确保匿名化、知情同意和合规性，这增加了资料收集和标记流程的复杂性和成本。

主要趋势

资料标註自动化应用日益普及：资料标註自动化正日益普及，从而节省了时间和人事费用成本。人工智慧系统如今能够以更高的精度处理大规模标註任务。预计2020-2027年全球数据标註工具市场将以27.1%的复合年增长率成长，加速当前趋势。

对高品质训练资料的需求日益增长：随着人工智慧系统日益复杂，对标记资料的需求也日益增长。准确的数据收集和标记对于开发可靠的机器学习模型至关重要。受此需求推动，预计到 2030 年，全球数据收集和标记市场将大幅成长。

合成资料的标记应用日益增多：为了解决资料稀缺和隐私问题，合成资料的使用日益增多，这使得企业即使没有真实资料也能产生标记资料集。到2027年，合成资料的使用预计将对自动驾驶汽车和医疗保健等领域产生重大影响，从而增强模型训练。

目录

第一章：全球资料收集与标籤市场简介

• 市场概览
• 研究范围
• 先决条件

第二章执行摘要

第三章：已验证的市场研究调查方法

• 资料探勘
• 验证
• 第一手资料
• 资料来源列表

第四章 资料收集与标记的全球市场展望

• 概述
• 市场动态
  • 驱动程式
  • 限制因素
  • 机会

第五章全球资料收集和标籤市场（按类型）

• 概述
• 文字
• 图片/影片
• 声音的

第六章全球资料收集与标籤市场（按应用）

• 概述
• 车
• 卫生保健
• BFSI
• 零售与电子商务
• 资讯科技/通讯
• 政府

7. 全球资料收集和标籤市场（按地区）

• 概述
• 北美洲
  • 美国
  • 加拿大
  • 墨西哥
• 欧洲
  • 德国
  • 英国
  • 法国
  • 其他欧洲国家
• 亚太地区
  • 中国
  • 日本
  • 印度
  • 其他亚太地区
• 其他的
  • 中东和非洲
  • 拉丁美洲

8. 全球资料收集和标籤市场的竞争格局

• 概述
• 各公司市场排名
• 重点发展策略

第九章 公司简介

• Reality AI
• Globalme Localization
• Global Technology Solutions
• Alegion
• Labelbox
• Dobility
• Scale AI
• Trilldata Technologies Pvt Ltd
• Appen Limited
• Playment

第十章 附录

• 相关调查

Data Collection And Labeling Market Size And Forecast

Data Collection And Labeling Market size was valued at USD 18.18 Billion in 2024 and is projected to reach USD 93.37 Billion by 2032 growing at a CAGR of 25.03% from 2026 to 2032.

Data collecting and labeling entails acquiring raw data and annotating it for machine learning and AI applications. This technique guarantees that datasets are structured and accurate, allowing computers to learn efficiently. Images, text, and audio are common data types used in the development of intelligent systems in a variety of industries.

In practice, data collection and labeling are critical for training models in industries like as healthcare, banking, and autonomous cars. They help AI applications perform better by supplying high-quality learning inputs. Tools and systems are progressively automating this process, saving time and effort while enhancing data quality.

As AI and machine learning applications become more prevalent, the requirement for data collecting and labeling will increase. Automated annotation and synthetic data synthesis are two innovations that will streamline the process. This evolution will empower businesses to leverage data more efficiently, enhancing decision-making and driving innovation in various fields.

Global Data Collection And Labeling Market Dynamics

The key market dynamics that are shaping the global Data Collection And Labeling Market include:

Key Market Drivers:

Increasing Reliance on Artificial Intelligence and Machine Learning: As AI and machine learning become more prevalent in numerous industries, the necessity for reliable data gathering and categorization grows. By 2025, the AI business is estimated to be worth $126 billion, emphasizing the significance of high-quality datasets for effective modeling.

Increasing Emphasis on Data Privacy and Compliance: With stronger requirements such as GDPR and CCPA, enterprises must prioritize data collection methods that assure privacy and compliance. The global data privacy industry is expected to grow to USD 6.7 Billion by 2023, highlighting the need for responsible data handling methods in labeling processes.

Emergence Of Advanced Data Annotation Tools: The emergence of enhanced data annotation tools is being driven by technological improvements, which are improving efficiency and lowering costs. Global Data Annotation tools market is expected to grow significantly, facilitating faster and more accurate labeling of data, essential for meeting the increasing demands of AI applications.

Key Challenges:

Ensuring Data Quality and Accuracy: Maintaining high accuracy is one of the most difficult challenges in data gathering and labeling. Poorly labeled data can impair AI model performance. Ensuring quality across huge datasets, particularly for complex data types such as photos and audio, necessitates extensive human monitoring and rigorous protocols.

Scalability Of Data Labeling: As AI models require massive amounts of labeled data, scaling the labeling process becomes difficult. Manual labeling is time-consuming and resource-intensive, making it challenging for businesses to fulfil increasing data needs while remaining efficient, particularly for complex datasets requiring domain-specific knowledge.

Data Privacy Concerns: With more data privacy rules, such as GDPR and CCPA, collecting and categorizing data while protecting sensitive information is a significant difficulty. Organizations must navigate legal requirements and ensure anonymization, consent, and compliance, adding complexity and cost to the data collection and labeling processes.

Key Trends:

Rising Adoption of Automation in Data Labeling: Automation in data labeling is becoming more popular, saving time and personnel expenses. AI-powered systems now handle large-scale annotating tasks with greater accuracy. The global data annotation tools market is expected to develop at a CAGR of 27.1% between 2020 and 2027, accelerating the current trend.

Growing Demand for High-Quality Training Data: As AI systems get more complicated, there is a greater requirement for labeled data. Accurate data collection and labeling are critical for developing dependable machine learning models. The global Data Collection And Labeling Market is predicted to develop significantly by 2030 as a result of this demand.

Increasing the Use of Synthetic Data for Labeling: To address data shortages and privacy problems, the usage of synthetic data is increasing. It allows companies to generate labeled datasets without real-world data. By 2027, synthetic data usage is expected to significantly impact sectors like autonomous vehicles and healthcare, enhancing model training.

Global Data Collection And Labeling Market Regional Analysis

Here is a more detailed regional analysis of the global Data Collection And Labeling Market:

North America:

According to Verified Market Research, North America is expected to dominate the global Data Collection And Labeling Market.

The increasing growth of the AI and machine learning businesses in North America, particularly in the United States, is driving high demand for labeled data. The National Science Foundation reports that between 2011 and 2020, AI-related papers in North America increased by 198%.

The US Bureau of Labor Statistics predicts a 21% increase in AI-related employment by 2032. North American businesses are also aggressively investing in big data and analytics, which drives up demand for data collecting and labeling. The US big data market is projected at USD 200.5 Billion in 2020 and is anticipated to reach USD 292.1 Billion by 2025.

Asia Pacific:

According to Verified Market Research, Asia Pacific is fastest growing region in global Data Collection And Labeling Market.

Rapid digital transformation in Asia Pacific is driving up demand for data collecting and labeling services. Digital transformation spending in the region (excluding Japan) is expected to reach USD 1.2 Trillion by 2024, with a CAGR of 17.4%. This spike reflects the growing demand for labeled data to assist AI and machine learning.

The growing e-commerce sector and mobile internet usage are also driving data labeling need. Southeast Asia, for example, added 40 million internet users in 2020, bringing the total to 400 million. By 2025, the region's digital economy is estimated to be worth USD 360 Billion, necessitating considerable data labeling for improved user experience and customization.

Global Data Collection And Labeling Market: Segmentation Analysis

The Global Data Collection And Labeling Market is segmented based on Type, Application, and Geography.

Data Collection And Labeling Market, By Type

• Text
• Image/Video
• Audio

Based on Type, the Global Data Collection And Labeling Market is separated into Text, Image/Video, and Audio. Image/Video leads the global Data Collection And Labeling Market due to its broad use in industries such as autonomous driving, healthcare diagnostics and facial recognition. The requirement for labeled visual data is critical for training AI and machine learning models, which is increasing its market share.

Data Collection And Labeling Market, By Application

• Automotive
• Healthcare
• Banking, Financial Services and Insurance (BFSI)
• Retail and E-commerce
• IT and Telecom
• Government

Based on Application, the Global Data Collection And Labeling Market is divided into Automotive, Healthcare, BFSI, Retail and E-commerce, IT and Telecom, Government. The automotive industry currently dominates the global Data Collection And Labeling Market, owing to the increasing demand for labeled data for autonomous driving systems, improved driver support systems and vehicle recognition technologies. The demand for accurate and comprehensive data in these applications necessitates major investment in data labeling systems.

Data Collection And Labeling Market, By Geography

• North America
• Europe
• Asia Pacific
• Rest of the World

Based on Geography, the Global Data Collection And Labeling Market divided into North America, Europe, Asia Pacific and Rest of the World. North America dominates the Data Collection And Labeling Market due to the high concentration of AI and IT businesses, which drives demand for labeled data. The Asia-Pacific area is the fastest growing, driven by rapid digital transformation, rising AI usage and emerging industries including as manufacturing and e-commerce that require tagged data.

Key Players

• The Global Data Collection And Labeling Market study report will provide valuable insight with an emphasis on the global market. The major players in the market are Reality AI, Globalme Localization, Inc., Global Technology Solutions, Alegion, Labelbox, Inc., Dobility, Inc., Scale AI, Inc., Trilldata Technologies Pvt Ltd, Appen Limited, Playment, Inc.

Our market analysis also entails a section solely dedicated to such major players wherein our analysts provide an insight into the financial statements of all the major players, along with product benchmarking and SWOT analysis. The competitive landscape section also includes key development strategies, market share and market ranking analysis of the above-mentioned players globally.

• Global Data Collection And Labeling Market Recent Developments
• In November 2022, Scale AI bought Labelbox, a data labeling tool provider to enhance its data annotation capabilities and speed the development of its artificial intelligence platform.
• In November 2022, Google introduced Cloud Annotations, a new data tagging platform. The platform employs machine learning to detect and classify things in photos and videos, saving time and effort over manual labeling. The software also allows users to collaborate on labeling activities, which makes large-scale labeling projects more manageable.

TABLE OF CONTENTS

1 INTRODUCTION OF GLOBAL DATA COLLECTION AND LABELING MARKET

• 1.1 Overview of the Market
• 1.2 Scope of Report
• 1.3 Assumptions

2 EXECUTIVE SUMMARY

3 RESEARCH METHODOLOGY OF VERIFIED MARKET RESEARCH

• 3.1 Data Mining
• 3.2 Validation
• 3.3 Primary Interviews
• 3.4 List of Data Sources

4 GLOBAL DATA COLLECTION AND LABELING MARKET OUTLOOK

• 4.1 Overview
• 4.2 Market Dynamics
  • 4.2.1 Drivers
  • 4.2.2 Restraints
  • 4.2.3 Opportunities

5 GLOBAL DATA COLLECTION AND LABELING MARKET, BY TYPE

• 5.1 Overview
• 5.2 Text
• 5.3 Image/Video
• 5.4 Audio

6 GLOBAL DATA COLLECTION AND LABELING MARKET, BY APPLICATION

• 6.1 Overview
• 6.2 Automotive
• 6.3 Healthcare
• 6.4 BFSI
• 6.5 Retail and E-commerce
• 6.6 IT and Telecom
• 6.7 Government

7 GLOBAL DATA COLLECTION AND LABELING MARKET, BY GEOGRAPHY

• 7.1 Overview
• 7.2 North America
  • 7.2.1 U.S.
  • 7.2.2 Canada
  • 7.2.3 Mexico
• 7.3 Europe
  • 7.3.1 Germany
  • 7.3.2 U.K.
  • 7.3.3 France
  • 7.3.4 Rest of Europe
• 7.4 Asia Pacific
  • 7.4.1 China
  • 7.4.2 Japan
  • 7.4.3 India
  • 7.4.4 Rest of Asia Pacific
• 7.5 Rest of the World
  • 7.5.1 Middle East & Africa
  • 7.5.2 Latin America

8 GLOBAL DATA COLLECTION AND LABELING MARKET COMPETITIVE LANDSCAPE

• 8.1 Overview
• 8.2 Company Market ranking
• 8.3 Key Development Strategies

9 COMPANY PROFILES

Reality AI

Globalme Localization

Global Technology Solutions

Alegion

Labelbox

Dobility

Scale AI

Trilldata Technologies Pvt Ltd

Appen Limited

Playment

10 APPENDIX

• 10.1 Related Research