AI Data Service Market Insights: Industry Opportunities, Drivers, Outlook and Trends Research Report
公開 2026/01/05 12:17
最終更新
-
On Jan 5, Global Info Research released "Global AI Data Service Market 2026 by Manufacturers, Regions, Type and Application, Forecast to 2032". This report includes an overview of the development of the AI Data Service industry chain, the market status of AI Data Service Market, and key enterprises in developed and developing market, and analysed the cutting-edge technology, patent, hot applications and market trends of AI Data Service.
According to our (Global Info Research) latest study, the global AI Data Service market size was valued at US$ 5032 million in 2025 and is forecast to a readjusted size of US$ 31214 million by 2032 with a CAGR of 29.7% during review period.
The global gross margin for AI data services is projected to be around 49% in 2025. AI data services refer to a collection of products and services surrounding the collection, processing, and labeling of data required for training, alignment, and evaluation of artificial intelligence models; quality control; data governance and version management; and the generation and delivery of synthetic data. Its core deliverables are structured data assets that can be directly used for training or evaluation (such as finished datasets, industry data packages, instruction and preference data, and evaluation sets), or the ability to continuously produce this data (such as data labeling platforms and data operation pipelines). Statistically, AI data services are typically defined by the "commercial delivery of training data-related capabilities," emphasizing the transformation of data from its raw form to a trainable form. Data labeling, as a key step, is generally defined as adding labels and metadata to raw data such as images, text, audio, and video, making it usable for machine learning training and validation.
The core applications of AI data services cover three main battlegrounds: First, the data closed loop for autonomous driving and advanced driver assistance systems (long-tail road scene acquisition, spatiotemporally consistent multi-sensor annotation, playback evaluation, and simulation synthesis completion); second, robotics and embodied intelligence (operation teaching and teleoperation data, multimodal interaction data such as visual-language-action or visual-language-tactile-action, and large-scale synthetic trajectories in simulation environments); and third, large models and generative artificial intelligence (instruction fine-tuning data, preference comparison and scoring data, red team and safety evaluation data, and continuous benchmark evaluation data). Among these, "alignment and human feedback data" has become an important part of the commercial training chain for large models. The market is moving from the traditional "low-complexity annotation outsourcing" stage to the "high-value data engineering" stage. As model capabilities improve, customers' requirements for data are shifting from quantity to quality and verifiability, especially in safety-critical and high-reliability scenarios. Data providers no longer just deliver samples, but need to deliver traceable data lineage, reproducible evaluation protocols, and sustainable data production mechanisms. Synthetic data and simulation are becoming key tools for expanding coverage of long-tail and extreme scenarios, driving the evolution of data services from labor-intensive to platform-based and automated models. The competitive landscape is also being reshaped: leading clients tend to purchase both "service delivery capabilities" and "platform capabilities" to reduce the unit cost of data production and increase iteration speed; while data service companies are increasing unit price and customer stickiness by introducing expert participation, human feedback workflows, and more stringent quality control systems. Recent capital and cooperation trends surrounding data service companies also reflect the continued upward trend in long-term market demand for high-quality training data.
This report is a detailed and comprehensive analysis for global AI Data Service market. Both quantitative and qualitative analyses are presented by company, by region & country, by Type and by Application. As the market is constantly changing, this report explores the competition, supply and demand trends, as well as key factors that contribute to its changing demands across many markets. Company profiles and product examples of selected competitors, along with market share estimates of some of the selected leaders for the year 2025, are provided.
Sample Report Request AI Data Service
https://www.globalinforesearch.com/reports/3406063/ai--data-service
Market segment by Type: Dataset、 Data Collection、 Data Labeling、 Other
Market segment by Application: Smart Security、 Smart Home、 Smart Finance、 Smart Healthcare、 New Retail、 Embodied Intelligence、 Intelligent Driving
Major players covered: TransPerfect、 Scale AI、 Shaip、 TELUS Digital、 iMerit、 CloudFactory、 Samasource、 Alegion、 Innodata、 TaskUs、 Centific、 Cogito Tech、 LXT、 Defined.ai、 Toloka AI、 OneForma、 Hive AI、 Surge AI、 Invisible Technologies、 Snorkel Al、 Labelbox、 SuperAnnotate、 Encord、 V7、 Dataloop（Dell)、 Gretel、 Mostly AI、 Speechocean、 Datatang、 DataBaker、 Data100、 Appen、 Kingline、 Baidu Crowdsourcing、 Longmao Data、 Fellisen、 MindFlow、 NavInfo、 iFLYTEK、 Lionbridge
Market segment by region, regional analysis covers:
North America (United States, Canada and Mexico),
Europe (Germany, France, United Kingdom, Russia, Italy, and Rest of Europe),
Asia-Pacific (China, Japan, Korea, India, Southeast Asia, and Australia),
South America (Brazil, Argentina, Colombia, and Rest of South America),
Middle East & Africa (Saudi Arabia, UAE, Egypt, South Africa, and Rest of Middle East & Africa).
The content of the study subjects, includes a total of 15 chapters:
Chapter 1, to describe AI Data Service product scope, market overview, market estimation caveats and base year.
Chapter 2, to profile the top manufacturers of AI Data Service, with price, sales, revenue and global market share of AI Data Service from 2021 to 2025.
Chapter 3, the AI Data Service competitive situation, sales quantity, revenue and global market share of top manufacturers are analyzed emphatically by landscape contrast.
Chapter 4, the AI Data Service breakdown data are shown at the regional level, to show the sales quantity, consumption value and growth by regions, from 2021 to 2032.
Chapter 5 and 6, to segment the sales by Type and application, with sales market share and growth rate by type, application, from 2021 to 2032.
Chapter 7, 8, 9, 10 and 11, to break the sales data at the country level, with sales quantity, consumption value and market share for key countries in the world, from 2021 to 2025.and AI Data Service market forecast, by regions, type and application, with sales and revenue, from 2026 to 2032.
Chapter 12, market dynamics, drivers, restraints, trends and Porters Five Forces analysis.
Chapter 13, the key raw materials and key suppliers, and industry chain of AI Data Service.
Chapter 14 and 15, to describe AI Data Service sales channel, distributors, customers, research findings and conclusion.
Data Sources:
Via authorized organizations:customs statistics, industrial associations, relevant international societies, and academic publications etc.
Via trusted Internet sources.Such as industry news, publications on this industry, annual reports of public companies, Bloomberg Business, Wind Info, Hoovers, Factiva (Dow Jones & Company), Trading Economics, News Network, Statista, Federal Reserve Economic Data, BIS Statistics, ICIS, Companies House Documentsm, investor presentations, SEC filings of companies, etc.
Via interviews. Our interviewees includes manufacturers, related companies, industry experts, distributors, business (sales) staff, directors, CEO, marketing executives, executives from related industries/organizations, customers and raw material suppliers to obtain the latest information on the primary market;
Via data exchange. We have been consulting in this industry for 16 years and have collaborations with the players in this field. Thus, we get access to (part of) their unpublished data, by exchanging with them the data we have.
From our partners.We have information agencies as partners and they are located worldwide, thus we get (or purchase) the latest data from them.
Via our long-term tracking and gathering of data from this industry.We have a database that contains history data regarding the market.
About Us:
Global Info Research
Web: https://www.globalinforesearch.com
Email: report@globalinforesearch.com
Global Info Research is a company that digs deep into global industry information to support enterprises with market strategies and in-depth market development analysis reports. We provides market information consulting services in the global region to support enterprise strategic planning and official information reporting, and focuses on customized research, management consulting, IPO consulting, industry chain research, database and top industry services. At the same time, Global Info Research is also a report publisher, a customer and an interest-based suppliers, and is trusted by more than 30,000 companies around the world. We will always carry out all aspects of our business with excellent expertise and experience.
According to our (Global Info Research) latest study, the global AI Data Service market size was valued at US$ 5032 million in 2025 and is forecast to a readjusted size of US$ 31214 million by 2032 with a CAGR of 29.7% during review period.
The global gross margin for AI data services is projected to be around 49% in 2025. AI data services refer to a collection of products and services surrounding the collection, processing, and labeling of data required for training, alignment, and evaluation of artificial intelligence models; quality control; data governance and version management; and the generation and delivery of synthetic data. Its core deliverables are structured data assets that can be directly used for training or evaluation (such as finished datasets, industry data packages, instruction and preference data, and evaluation sets), or the ability to continuously produce this data (such as data labeling platforms and data operation pipelines). Statistically, AI data services are typically defined by the "commercial delivery of training data-related capabilities," emphasizing the transformation of data from its raw form to a trainable form. Data labeling, as a key step, is generally defined as adding labels and metadata to raw data such as images, text, audio, and video, making it usable for machine learning training and validation.
The core applications of AI data services cover three main battlegrounds: First, the data closed loop for autonomous driving and advanced driver assistance systems (long-tail road scene acquisition, spatiotemporally consistent multi-sensor annotation, playback evaluation, and simulation synthesis completion); second, robotics and embodied intelligence (operation teaching and teleoperation data, multimodal interaction data such as visual-language-action or visual-language-tactile-action, and large-scale synthetic trajectories in simulation environments); and third, large models and generative artificial intelligence (instruction fine-tuning data, preference comparison and scoring data, red team and safety evaluation data, and continuous benchmark evaluation data). Among these, "alignment and human feedback data" has become an important part of the commercial training chain for large models. The market is moving from the traditional "low-complexity annotation outsourcing" stage to the "high-value data engineering" stage. As model capabilities improve, customers' requirements for data are shifting from quantity to quality and verifiability, especially in safety-critical and high-reliability scenarios. Data providers no longer just deliver samples, but need to deliver traceable data lineage, reproducible evaluation protocols, and sustainable data production mechanisms. Synthetic data and simulation are becoming key tools for expanding coverage of long-tail and extreme scenarios, driving the evolution of data services from labor-intensive to platform-based and automated models. The competitive landscape is also being reshaped: leading clients tend to purchase both "service delivery capabilities" and "platform capabilities" to reduce the unit cost of data production and increase iteration speed; while data service companies are increasing unit price and customer stickiness by introducing expert participation, human feedback workflows, and more stringent quality control systems. Recent capital and cooperation trends surrounding data service companies also reflect the continued upward trend in long-term market demand for high-quality training data.
This report is a detailed and comprehensive analysis for global AI Data Service market. Both quantitative and qualitative analyses are presented by company, by region & country, by Type and by Application. As the market is constantly changing, this report explores the competition, supply and demand trends, as well as key factors that contribute to its changing demands across many markets. Company profiles and product examples of selected competitors, along with market share estimates of some of the selected leaders for the year 2025, are provided.
Sample Report Request AI Data Service
https://www.globalinforesearch.com/reports/3406063/ai--data-service
Market segment by Type: Dataset、 Data Collection、 Data Labeling、 Other
Market segment by Application: Smart Security、 Smart Home、 Smart Finance、 Smart Healthcare、 New Retail、 Embodied Intelligence、 Intelligent Driving
Major players covered: TransPerfect、 Scale AI、 Shaip、 TELUS Digital、 iMerit、 CloudFactory、 Samasource、 Alegion、 Innodata、 TaskUs、 Centific、 Cogito Tech、 LXT、 Defined.ai、 Toloka AI、 OneForma、 Hive AI、 Surge AI、 Invisible Technologies、 Snorkel Al、 Labelbox、 SuperAnnotate、 Encord、 V7、 Dataloop（Dell)、 Gretel、 Mostly AI、 Speechocean、 Datatang、 DataBaker、 Data100、 Appen、 Kingline、 Baidu Crowdsourcing、 Longmao Data、 Fellisen、 MindFlow、 NavInfo、 iFLYTEK、 Lionbridge
Market segment by region, regional analysis covers:
North America (United States, Canada and Mexico),
Europe (Germany, France, United Kingdom, Russia, Italy, and Rest of Europe),
Asia-Pacific (China, Japan, Korea, India, Southeast Asia, and Australia),
South America (Brazil, Argentina, Colombia, and Rest of South America),
Middle East & Africa (Saudi Arabia, UAE, Egypt, South Africa, and Rest of Middle East & Africa).
The content of the study subjects, includes a total of 15 chapters:
Chapter 1, to describe AI Data Service product scope, market overview, market estimation caveats and base year.
Chapter 2, to profile the top manufacturers of AI Data Service, with price, sales, revenue and global market share of AI Data Service from 2021 to 2025.
Chapter 3, the AI Data Service competitive situation, sales quantity, revenue and global market share of top manufacturers are analyzed emphatically by landscape contrast.
Chapter 4, the AI Data Service breakdown data are shown at the regional level, to show the sales quantity, consumption value and growth by regions, from 2021 to 2032.
Chapter 5 and 6, to segment the sales by Type and application, with sales market share and growth rate by type, application, from 2021 to 2032.
Chapter 7, 8, 9, 10 and 11, to break the sales data at the country level, with sales quantity, consumption value and market share for key countries in the world, from 2021 to 2025.and AI Data Service market forecast, by regions, type and application, with sales and revenue, from 2026 to 2032.
Chapter 12, market dynamics, drivers, restraints, trends and Porters Five Forces analysis.
Chapter 13, the key raw materials and key suppliers, and industry chain of AI Data Service.
Chapter 14 and 15, to describe AI Data Service sales channel, distributors, customers, research findings and conclusion.
Data Sources:
Via authorized organizations:customs statistics, industrial associations, relevant international societies, and academic publications etc.
Via trusted Internet sources.Such as industry news, publications on this industry, annual reports of public companies, Bloomberg Business, Wind Info, Hoovers, Factiva (Dow Jones & Company), Trading Economics, News Network, Statista, Federal Reserve Economic Data, BIS Statistics, ICIS, Companies House Documentsm, investor presentations, SEC filings of companies, etc.
Via interviews. Our interviewees includes manufacturers, related companies, industry experts, distributors, business (sales) staff, directors, CEO, marketing executives, executives from related industries/organizations, customers and raw material suppliers to obtain the latest information on the primary market;
Via data exchange. We have been consulting in this industry for 16 years and have collaborations with the players in this field. Thus, we get access to (part of) their unpublished data, by exchanging with them the data we have.
From our partners.We have information agencies as partners and they are located worldwide, thus we get (or purchase) the latest data from them.
Via our long-term tracking and gathering of data from this industry.We have a database that contains history data regarding the market.
About Us:
Global Info Research
Web: https://www.globalinforesearch.com
Email: report@globalinforesearch.com
Global Info Research is a company that digs deep into global industry information to support enterprises with market strategies and in-depth market development analysis reports. We provides market information consulting services in the global region to support enterprise strategic planning and official information reporting, and focuses on customized research, management consulting, IPO consulting, industry chain research, database and top industry services. At the same time, Global Info Research is also a report publisher, a customer and an interest-based suppliers, and is trusted by more than 30,000 companies around the world. We will always carry out all aspects of our business with excellent expertise and experience.
