Impact of Data Element Market Development on AI Industry Investment and Investment Analysis of Embodied Intelligence Data Transactions

According to the latest market research, the rapid development of the data element market is reshaping the investment logic of the AI industry [1]. As a new type of production factor, the assetization process of data provides a clearer valuation framework for AI investment.

• The AI infrastructure SaaS market is expected to grow from $69.2 billion in 2025 to $155.6 billion in 2030, with a CAGR of 17.6% [1]
• The foundation model market will surge from $25.3 billion in 2025 to $136.2 billion in 2030, an increase of nearly 5.4 times [1]
• The AI customer service and support market will grow from $27.9 billion to $56.2 billion, mainly due to clear ROI from autonomous ticket processing and workflow automation [1]

Through legal and compliant transaction mechanisms, the data element market has significantly reduced the cost and threshold for AI enterprises to obtain high-quality training data. The first embodied intelligence dataset transaction completed by the Jiangsu Data Exchange marks a major breakthrough in the data element market in the vertical AI field [2].

• Reduce repeated investment in data collection, allowing enterprises to focus on core algorithm development
• Standardized data products shorten R&D cycles
• Multi-source data fusion improves model performance

• Multimodal Data Integration:
  Combined collection of structured data such as video data, joint angles, and torque parameters
• Scenario-based Datasets:
  Professional datasets for specific application scenarios (e.g., industrial manufacturing, home services)
• Standardized Products:
  Preprocessed data packages that can be directly used for model training

• Address the pain point of shortage of high-quality real-world data in the embodied intelligence industry
• Provide “plug-and-play” training data for robot developers
• Reduce industry entry barriers through data standardization

As the platform for the first embodied intelligence dataset transaction in China, its model innovations are reflected in:

• Compliance Assurance:
  Provide data property rights confirmation and transaction compliance review
• Pricing Mechanism:
  Establish a data quality evaluation system and market-oriented pricing mechanism
• Ecosystem Construction:
  Connect data suppliers (e.g., Jiangsu Zhujing Intelligence) with demanders (AI enterprises, robot companies)

• Data annotation and cleaning services
• Scenario-customized data collection
• Data quality evaluation and certification
• Continuous data update subscription services

• Investment Logic: Embodied intelligence requires massive real-scenario data, and professional data collection companies have first-mover advantages
• Key Metrics: Data collection scale, data quality, and breadth of scenario coverage

• Market Driver: Real data costs are high, and simulation data can effectively supplement training needs
• Technical Barriers: Physical simulation accuracy and multi-scenario simulation capability

• Key Areas: Industrial robots, service robots, autonomous driving
• Investment Value: Data accumulation forms industry barriers

According to industry forecasts, the size of China’s intelligent robot market is expected to reach $77 billion by 2030, with policy support, increased capital investment, and industrial chain collaboration as the main drivers [3].

With the popularization of AI agent applications, the relevant data market is experiencing explosive growth. AI agent investment will reach $6.4 billion in 2025, involving 451 transactions, compared to $4.6 billion in 2024 [4].

• Ununified data collection standards affect reusability
• Uneven data quality affects model training results
• Lack of unified industry evaluation standards

• Increasingly strict data privacy protection requirements
• Restrictions on cross-border data transmission
• Intellectual property protection challenges

• Rapid evolution of model architectures may reduce data value
• Development of few-shot learning technology may reduce reliance on large-scale data
• Advances in simulation data technology may replace part of the demand for real data

• Data Infrastructure Service Providers: Data exchanges, data quality management platforms
• Scenario-specific Data Collection Enterprises: Industrial robots, service robots fields
• Data Compliance and Security Assurance Providers

Meta acquired the AI agent company Manus for $2 billion; the latter sells AI agents to enterprises through subscription services, with annual revenue reaching $125 million [5], verifying the commercial value of data-driven AI applications.

• Full-stack embodied intelligence solution providers (data + algorithm + hardware)
• Data generation and simulation platforms
• Cross-scenario data service platforms
• Data assetization financial innovation services

• Industrial Internet data transactions
• Humanoid robot training data market
• Multimodal data fusion technology
• Data value evaluation and pricing system

Dimension	Evaluation Indicators	Weight
Data Assets	Data scale, quality, scarcity	30%
Technical Barriers	Collection technology, processing capability, standardization level	25%
Business Model	Revenue sources, customer stickiness, scalability	25%
Compliance Capability	Data compliance system, security assurance	20%

The maturity of the data element market provides a new value anchor for AI industry investment, especially in the field of embodied intelligence, where innovations in data transaction models are accelerating the industrial commercialization process.

1. Data Asset Value Highlights:
   High-quality scenario data becomes core competitiveness; the speed and quality of data accumulation determine the enterprise’s moat
2. Infrastructure First:
   Infrastructure builders such as data transaction platforms and quality evaluation systems will benefit first
3. Application Scenario Orientation:
   Investment should focus on vertical application scenarios with clear willingness and ability to pay
4. Ecosystem Synergy Value:
   Enterprises with data collection, algorithm development, and hardware integration capabilities have the highest investment value

With the advancement of the construction of a unified national data element market and the implementation of policies such as “data assets entering the balance sheet”, the data element market will usher in dual opportunities of institutional innovation and market expansion; embodied intelligence data transactions are expected to become a new blue ocean for AI industry investment.

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[1] Jinling API Data - Based on PitchBook report data, market size forecasts for AI infrastructure SaaS, foundation models, and customer service markets
[2] Reports on embodied intelligence dataset transactions of Jiangsu Data Exchange (Source: Web search)
[3] Forecast of China’s intelligent robot market size by 2030 (Source: Web search)
[4] PitchBook Data - AI agent investment reaches $6.4 billion in 2025 (Source: Web search)
[5] Meta’s acquisition of Manus case - Commercial verification of AI agents (Source: Web search)

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This analysis is based on public information and professional research; investment decisions need to be combined with due diligence and risk assessment of specific projects. If you need to enable deep research mode for more detailed target screening and financial modeling analysis, please provide specific investment direction preferences.