Two Ministries Jointly Launch 'Model-Data Resonance' Initiative to Create New AI-Empowered Industry Models

Two Ministries Issue Major Policy as 'Model-Data Resonance' Initiative Officially Launches

The General Office of the Ministry of Industry and Information Technology (MIIT) and the General Department of the National Data Administration recently jointly issued a notice on implementing the 2026 'Model-Data Resonance' initiative. The notice explicitly proposes guiding computing power enterprises, model enterprises, data enterprises, and application development enterprises to form 'Model-Data Resonance' innovation consortia around key industries, driving deep integration and coordinated development of artificial intelligence and data elements on the industrial side.

The release of this policy signal marks a critical step in China's AI industrialization — shifting from single-point technological breakthroughs to full-chain collaborative innovation.

Core Measures: Four Types of Enterprises to Form Innovation Consortia

According to the notice, the core of the 'Model-Data Resonance' initiative lies in connecting the four major segments of computing power, models, data, and applications to create a closed-loop collaboration mechanism. Specifically, the policy includes several key points:

First, forming innovation consortia. Centered on selected key industries, computing power enterprises, model enterprises, data enterprises, and application development enterprises are guided to form 'Model-Data Resonance' innovation consortia, with no fewer than one consortium per key industry to ensure substantive progress across all sectors.

Second, a collaborative linkage mechanism. The initiative supports innovation consortia in coordinating with 'Model-Data Resonance' spaces to jointly conduct model development, hardware-software adaptation, data processing, and application solution design and development across the full workflow, achieving seamless connection from R&D to real-world deployment.

Third, creating industry 'showrooms.' Consortia are organized to strengthen the development and application of industry-level, full-stack solutions, using the 'showroom' model to set industry benchmarks and form replicable, scalable AI-empowered industry pathways.

Underlying Logic: Why 'Model-Data Resonance'?

The concept of 'Model-Data Resonance' essentially aims to create a positive feedback loop where AI models and data elements drive and reinforce each other. Currently, China's AI industry faces several prominent challenges:

Insufficient supply chain coordination. Computing power providers, large model developers, data service providers, and industry application enterprises often operate in silos, lacking effective collaboration mechanisms, resulting in a clear gap between technology supply and scenario demand.

High industry data barriers. Acquiring, cleaning, and labeling quality industry data remains a core bottleneck for AI deployment. Model enterprises alone cannot break through data barriers and urgently need deep participation from data enterprises.

Fragmented deployment scenarios. Many AI solutions remain at the demonstration stage, lacking systematic capabilities from hardware-software adaptation to full-stack deployment, making it difficult to achieve large-scale application.

The 'Model-Data Resonance' initiative targets these pain points precisely, using policy guidance and institutional design to drive upstream and downstream enterprises to join forces and accelerate AI's journey from 'usable' to 'effective.'

Industry Impact: An Ecosystem Benefiting Multiple Stakeholders

From an industrial ecosystem perspective, this policy will have far-reaching effects on multiple types of enterprises:

• Computing power enterprises will gain clearer industry demand signals, helping optimize computing resource allocation and improve utilization efficiency.
• Model enterprises can leverage industry data and application scenarios to accelerate model iteration and strengthen competitiveness in vertical domains.
• Data enterprises will see further unlocking of their industry data asset value, with data governance and data service capabilities becoming core competitive advantages.
• Application development enterprises can rely on consortia for more comprehensive technology infrastructure support, lowering AI application development thresholds and integration costs.

Notably, the introduction of the 'showroom' model indicates that the policy pursues not only technological innovation but also the formation of replicable, standardized solutions. This will powerfully drive AI adoption from leading enterprises to SMEs, and from first-tier cities to broader regions.

Outlook: AI Industrialization Enters Deep Waters

The launch of the 'Model-Data Resonance' initiative reflects China's AI industrial policy transitioning from 'encouraging R&D' to 'driving deployment.' As the 2026 action plan is gradually implemented, benchmark AI application cases are expected to emerge first in key industries such as manufacturing, energy, healthcare, and transportation.

Looking ahead, as more innovation consortia are formed and industry 'showrooms' are established, the resonance effect between 'models' and 'data' is expected to accelerate, propelling China's AI industry from a technology-driven phase to a new value-driven stage. For participants across the industrial chain, finding the right positioning and leveraging strengths within the consortium mechanism will be key to winning the next round of competition.