For the first time, the International Data Corporation (IDC) has positioned AI foundation data services as a standalone sector for systematic quantitative analysis, unveiling its latest research report on China's AI foundation data services market this year.
According to the findings, the sector reached a valuation of 6.26 billion yuan in 2025, marking a 27.8% year-on-year expansion that surpassed market expectations. Projections indicate the market will climb to 7.83 billion yuan by 2026, with a compound annual growth rate (CAGR) of 19.6% anticipated between 2025 and 2030.
Despite headwinds in the broader economic landscape, the AI foundation data services market has demonstrated remarkable resilience, propelled by the rapid advancement of artificial intelligence. The customer base has diversified well beyond traditional AI enterprises to encompass government agencies, autonomous driving developers, and embodied intelligence pioneers, with data requirements now being steered by practical AI deployment needs that shift focus from consumer entertainment toward tangible productivity enhancements.
Market Landscape: Fragmented Competition with Newcomers Capturing Over Half the Share
Examining the competitive dynamics of 2025, the leading players in China's AI foundation data services arena include Appen, Baidu, China Telecom, Speechocean, Datatang, Jinglianwen, and Yunce Technology. Appen commands the top position with an 11.5% market share, closely followed by Baidu at 10.6%.
Notably, the overall market remains highly fragmented, with the "others" category accounting for a substantial 56.3% share, indicating relatively low entry barriers and a continuous influx of new participants. While top-tier vendors have achieved growth rates exceeding projections, their product offerings have yet to show meaningful differentiation. Instead, these firms are competing primarily through automated annotation tools designed to reduce labeling complexity and costs, thereby capturing additional market share. When selecting data service partners, clients increasingly prioritize historical service expertise, labor expenses, responsiveness to requirements, and data acquisition capabilities.
Shifting Paradigm: From Knowledge-Centric to Task-Oriented Data
The IDC report highlights a profound transformation underway in the AI foundation data services market, characterized by three pivotal trends. First, data demand is migrating from large-scale collection efforts toward task-specific data, encompassing agent execution traces, multi-step task planning, tool invocation sequences, and enterprise workflow data. Second, annotation methodologies are evolving from purely manual processes to human-machine collaboration, establishing a closed loop that integrates model generation, AI-driven automated evaluation, expert validation, and reinforcement learning optimization. Third, data types are narrowing from generalized multimodal inputs to production-related behavioral information that directly enhances productivity.
Furthermore, demand is surging for specialized domain data spanning physician-level diagnostics, legal expertise, and financial analysis, while inference and evaluation datasets are attracting growing attention. The customer landscape continues to broaden, incorporating industry-specific vendors and software enterprises across sectors. Investment interest in world models and Physical AI infrastructure is expected to intensify in 2026, while advancements in agent technologies are poised to boost client AI procurement budgets by approximately 20%.
Strategic Recommendations: Balancing Technological Advancement with Business Model Evolution
The IDC advises data service providers to intensify research and development investments, fully embracing the "Human-in-the-loop" framework while proactively positioning synthetic data as a second growth engine. Firms should also restructure their talent pipelines, transitioning from conventional annotation staff toward highly educated specialists and industry experts, establishing flexible talent pools that encompass postgraduate researchers, programmers, physicians, lawyers, and other professionals.
On the business model front, the IDC suggests shifting from volume-based pricing toward outcome-oriented or solution-based fee structures, delivering end-to-end closed-loop services that span scenario definition, data collection, precision annotation, model evaluation, and fine-tuning optimization. Data compliance capabilities should be elevated to core competitive advantages and treated as a non-negotiable prerequisite, requiring providers to implement comprehensive frameworks for data anonymization, copyright verification, and privacy-preserving computation across the entire workflow.
IDC analysts contend that enterprises must fundamentally rethink how AI data is priced and valued. For sustainable, long-term queryable datasets, service providers are entitled to charge premiums, as data value is no longer tied to individual users but rather directly correlated with enhancements in model performance.