On February 7, China’s National Data Administration together with the Ministry of Industry and Information Technology, the Ministry of Public Security and the China Securities Regulatory Commission issued a joint policy paper to cultivate the domestic data circulation industry and speed the marketisation and monetisation of data as an economic factor. For the first time Beijing formally identifies three categories of data intermediaries—data exchanges (or centres), data-circulation platform companies, and so-called "data merchants"—and sets out distinct roles for each.
Under the new guidance, data exchanges are to provide comprehensive services across governance, trading and quality assurance; platform companies are expected to pursue specialised, vertical offerings; and data merchants will be tasked with developing packaged data products and downstream services. The document also encourages experimentation with a broader range of trading mechanisms beyond cash-for-data, including swaps of data for orders, services, models and application scenarios, a move designed to loosen legacy transactional patterns and stimulate more dynamic exchanges of datasets.
A particular emphasis of the policy is on supporting China’s “AI+” strategy. The authors argue that market-facing institutions should work with artificial-intelligence firms to assemble high‑quality datasets, broaden the ways such datasets can be traded, and provide services such as data aggregation, governance and model training. Officials frame these measures as necessary to accelerate model development while improving dataset quality for commercial and research uses.
The involvement of the Ministry of Public Security and the securities regulator in the joint paper signals Beijing’s intent to marry market cultivation with security and financial oversight. That dual mandate reflects ongoing efforts since the Data Security Law and Personal Information Protection Law to reconcile data-driven innovation with tighter rules on data protection, cross-border transfer and national-security risk management.
For domestic firms, the guidance promises clearer institutional roles and potentially easier access to curated datasets—especially valuable to start‑ups and applied‑AI teams that struggle with fragmented data silos. For the broader ecosystem, the policy aims to professionalise intermediaries that can vet, package and monetise data, creating pathways for public-sector and private datasets to be reused in lawful and standardised ways.
Yet the initiative also raises complex questions. Expanding data markets will require robust mechanisms to certify dataset provenance, protect personal information and prevent illicit use. The presence of security and financial regulators on the steering document suggests that fast‑tracked marketisation will be accompanied by stricter compliance and vetting processes, which may slow some transactions even as new exchange models proliferate.
Taken together, the move is a pragmatic next step in China’s long‑running push to treat data as an economic input. Policymakers are signalling that the state will not only regulate data flows but actively shape the intermediaries that enable datasets to be traded and used by industry—especially by AI firms—while retaining levers to limit systemic and national‑security risks.