Summary

Data Collection and Labelling Market Research Report By Data Type (Text, Image/ Video and Audio), by Vertical (IT, Automotive, Government, Healthcare, BFSI, Retail & E-commerce, and Others), and By Region (North America, Europe, Asia-Pacific, Middle East and Africa, South America) Market Forecast Till 2032
Overview of the Market
In 2023, the data collection and labeling market was estimated to be worth USD 2,701.8 million. With a compound annual growth rate (CAGR) of 29.4% from 2024 to 2032, the data collecting and labeling market is expected to increase from USD 2,984.1 million in 2024 to USD 23,476.8 million by 2032. For both well-established companies and up-and-coming entrepreneurs, the data collection and labeling sector has enormous prospects.
The quality of data annotations is a key factor in training autonomous cars. The reliability and safety of autonomous vehicles depend on the highest quality annotations. The success of autonomous driving depends on accurate data annotation since it enables vehicles to navigate safely by classifying roadside objects and features. The stages of development and manufacture can be adversely affected by inadequate data labeling procedures, which can result in delays and jeopardize the security and operation of self-driving automobiles. Data validation is a crucial step in the data annotation process for self-driving automobiles since it ensures reliable and accurate algorithm training. It attests to the accuracy, completeness, and relevance of the annotated data to the algorithms under training. The future of data annotation quality in self-driving cars aims to improve safety and accuracy through advanced annotation techniques and automation. The creation of new market segment insights will improve the overall safety and dependability of autonomous driving systems

Market Segmentation
The data collection and labeling market has been divided into three segments based on the type of data: text, image/video, and audio.
IT, Automotive, Government, Healthcare, BFSI, Retail & E-commerce, and Others are the segments of the Data Collection and Labeling Market based on Vertical.

Regional Perspectives
The United States, Canada, and Mexico make up North America. The necessity for data collection and labeling has grown across North America. Data annotation and labeling have rapidly taken root in this sector, which is home to numerous significant enterprises that have adopted cutting-edge technology rapidly. Businesses must outsource these services to meet their data processing needs due to the growing complexity of the AI and machine learning models being built.
Artificial Intelligence (AI) and Machine Learning (ML) have been increasingly prevalent in several industries in the Asia-Pacific area in recent years, particularly in nations like China, Japan, India, and others. The requirement for data collection and annotation is increasing at an exponential rate in tandem with the real-world applications of these technologies.
The study's Europe region includes the UK, Germany, France, and the rest of Europe. The primary drivers are thought to be the growing use of AI and ML technologies in Europe as well as the strong demand for data collection and labeling services. Since generative AI has advanced and made the technologies more deployable, the region's sectors are progressively implementing AI and ML solutions.
Key Players
Appen Limited, Telcus International, Global Technology Solutions, Alegion, Labelbox, Inc., Reality AI, Globalme Localization, Inc., Dobility Inc., Scale AI, and Trilldata Technologies PVT LTD are the leading suppliers in the market.

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Table of Contents

TABLE OF CONTENTS
1 EXECUTIVE SUMMARY 18
2 MARKET INTRODUCTION 21
2.1 DEFINITION 21
2.2 SCOPE OF THE STUDY 21
2.3 RESEARCH OBJECTIVE 21
2.4 MARKET STRUCTURE 22
3 RESEARCH METHODOLOGY 23
3.1 OVERVIEW 23
3.2 DATA FLOW 25
3.2.1 DATA MINING PROCESS 25
3.3 PURCHASED DATABASE: 26
3.4 SECONDARY SOURCES: 27
3.4.1 SECONDARY RESEARCH DATA FLOW: 28
3.5 PRIMARY RESEARCH: 29
3.5.1 PRIMARY RESEARCH DATA FLOW: 30
3.5.2 PRIMARY RESEARCH: NUMBER OF INTERVIEWS CONDUCTED 31
3.6 APPROACHES FOR MARKET SIZE ESTIMATION: 32
3.6.1 CONSUMPTION & NET TRADE APPROACH 32
3.6.2 REVENUE ANALYSIS APPROACH 32
3.7 DATA FORECASTING 33
3.7.1 DATA FORECASTING TYPE 33
3.8 DATA MODELING 34
3.8.1 MICROECONOMIC FACTOR ANALYSIS: 34
3.8.2 DATA MODELING: 35
4 MARKET DYNAMICS 38
4.1 INTRODUCTION 38
4.2 DRIVERS 38
4.2.1 RISE IN HEALTHCARE AI APPLICATION 38
4.2.2 RAPIDLY INCREASING IN E COMMERCE 39
4.3 RESTRAINTS 40
4.3.1 DATA PRIVACY AND SECURITY CONCERNS 40
4.3.2 PROBLEMS RELATED TO INADEQUATE TRAINING DATA QUALITY 40
4.4 OPPORTUNITY 41
4.4.1 GROWTH OF AUTONOMOUS TECHNOLOGY 41
4.4.2 GROWING POPULARITY OF LABELLING CROWDSOURCED DATA 42
5 MARKET FACTOR ANALYSIS 43
5.1 VALUE CHAIN ANALYSIS 43
5.1.1 DATA COLLECTION 43
5.1.2 DATA PREPROCESSING 43
5.1.3 SELECT THE RIGHT VENDOR OR TOOL 43
5.1.4 ANNOTATION GUIDELINES 43
5.1.5 ANNOTATION 43
5.1.6 QUALITY ASSURANCE (QA) 44
5.1.7 DATA EXPORT 44
5.2 PORTER'S FIVE FORCES MODEL 45
5.2.1 THREAT OF NEW ENTRANTS 45
5.2.2 BARGAINING POWER OF SUPPLIERS 46
5.2.3 THREAT OF SUBSTITUTES 46
5.2.4 BARGAINING POWER OF BUYERS 46
5.2.5 INTENSITY OF RIVALRY 46
5.3 COVID-19 IMPACT ANALYSIS 47
5.3.1 MARKET IMPACT ANALYSIS 47
5.3.2 REGIONAL IMPACT 47
5.3.3 OPPORTUNITY AND THREAT ANALYSIS 47
6 GLOBAL DATA COLLECTION AND LABELLING MARKET, BY DATA TYPE 49
6.1 OVERVIEW 49
6.2 TEXT 51
6.3 IMAGE/ VIDEO 51
6.4 AUDIO 51
7 GLOBAL DATA COLLECTION AND LABELLING MARKET, BY VERTICAL 53
7.1 INTRODUCTION 53
7.2 IT 55
7.3 AUTOMOTIVE 55
7.4 GOVERNMENT 56
7.5 HEALTHCARE 56
7.6 BFSI 56
7.7 RETAIL & E-COMMERCE 57
7.8 OTHERS 57
8 GLOBAL DATA COLLECTION AND LABELLING MARKET, BY REGION 59
8.1 OVERVIEW 59
GLOBAL DATA COLLECTION AND LABELLING MARKET, BY REGION, 2023 VS 2032 (USD MILLION) 59
8.2 NORTH AMERICA 60
8.2.1 US 63
8.2.2 CANADA 64
8.3 EUROPE 65
8.3.1 UK 69
8.3.2 GERMANY 70
8.3.3 FRANCE 71
8.3.4 ITALY 72
8.3.5 SPAIN 73
8.3.6 REST OF EUROPE 74
8.4 ASIA-PACIFIC 75
8.4.1 CHINA 78
8.4.2 JAPAN 79
8.4.3 INDIA 80
8.4.4 SOUTH KOREA 81
8.4.5 AUSTRALIA 82
8.4.6 REST OF ASIA-PACIFIC 83
8.5 REST OF THE WORLD 85
8.5.1 MIDDLE EAST 88
8.5.2 AFRICA 89
8.5.3 LATIN AMERICA 90
9 COMPETITIVE LANDSCAPE 91
9.1 INTRODUCTION 91
9.2 MARKET SHARE ANALYSIS, 2023 91
9.3 COMPETITOR DASHBOARD 92
SUMMA LINGUAE TECHNOLOGIES 92
5 92
APPEN 92
4 92
IBM 92
5 92
LABELBOX 92
4 92
TELUS INTERNATIONAL 92
4 92
9.4 MAJOR PLAYERS FINANCIAL MATRIX 93
9.5 KEY DEVELOPMENTS & GROWTH STRATEGIES 93
9.5.1 PRODUCT DEVELOPMENT 93
9.5.2 PARTNERSHIPS/AGREEMENTS/CONTRACTS/COLLABORATIONS 95
10 COMPANY PROFILE 97
10.1 APPEN LIMITED 97
10.1.1 COMPANY OVERVIEW 97
10.1.2 FINANCIAL OVERVIEW 98
10.1.3 PRODUCTS OFFERED 98
10.1.4 KEY DEVELOPMENTS 99
10.1.5 SWOT ANALYSIS 100
10.1.6 KEY STRATEGIES 100
10.2 TELUS INTERNATIONAL 101
10.2.1 COMPANY OVERVIEW 101
10.2.2 FINANCIAL OVERVIEW 102
10.2.3 PRODUCTS OFFERED 102
10.2.4 KEY DEVELOPMENTS 103
10.2.5 SWOT ANALYSIS 103
10.2.6 KEY STRATEGIES 104
10.3 GLOBAL TECHNOLOGY SOLUTIONS 105
10.3.1 COMPANY OVERVIEW 105
10.3.2 FINANCIAL OVERVIEW 105
10.3.3 PRODUCTS OFFERED 106
10.4 ALEGION 107
10.4.1 COMPANY OVERVIEW 107
10.4.2 FINANCIAL OVERVIEW 108
10.4.3 PRODUCTS OFFERED 108
10.4.4 KEY DEVELOPMENTS 109
10.4.5 SWOT ANALYSIS 109
10.4.6 KEY STRATEGIES 109
10.5 LABELBOX, INC 110
10.5.1 COMPANY OVERVIEW 110
10.5.2 FINANCIAL OVERVIEW 110
10.5.3 PRODUCTS OFFERED 110
10.5.4 KEY DEVELOPMENTS 111
10.5.5 SWOT ANALYSIS 112
10.5.6 KEY STRATEGIES 112
10.6 RENESAS ELECTRONICS CORPORATION 113
10.6.1 COMPANY OVERVIEW 113
10.6.2 FINANCIAL OVERVIEW 113
10.6.3 PRODUCTS OFFERED 114
10.6.4 KEY DEVELOPMENTS 115
10.6.5 SWOT ANALYSIS 116
10.6.6 KEY STRATEGIES 117
10.7 SUMMA LINGUAE TECHNOLOGIES 118
10.7.1 COMPANY OVERVIEW 118
10.7.2 FINANCIAL OVERVIEW 118
10.7.3 PRODUCTS OFFERED 119
10.7.4 KEY DEVELOPMENTS 119
10.7.5 SWOT ANALYSIS 120
10.7.6 KEY STRATEGIES 120
10.8 DOBILITY INC. 121
10.8.1 COMPANY OVERVIEW 121
10.8.2 FINANCIAL OVERVIEW 121
10.8.3 PRODUCTS OFFERED 122
10.8.4 KEY DEVELOPMENTS 122
10.8.5 SWOT ANALYSIS 122
10.8.6 KEY STRATEGIES 123
10.9 SCALE AI INC. 124
10.9.1 COMPANY OVERVIEW 124
10.9.2 FINANCIAL OVERVIEW 124
10.9.3 PRODUCTS OFFERED 124
10.9.4 KEY DEVELOPMENTS 125
10.9.5 SWOT ANALYSIS 126
10.9.6 KEY STRATEGIES 126
10.10 IBM CORPORATION 127
10.10.1 COMPANY OVERVIEW 127
10.10.2 FINANCIAL OVERVIEW 127
10.10.3 PRODUCTS OFFERED 128
10.10.4 KEY DEVELOPMENTS 129
10.10.5 SWOT ANALYSIS 130
10.10.6 KEY STRATEGIES 130