Six Government Departments Jointly Issue Guidelines to Promote Large-Scale Application of AI Technology in Advertising
Miles Bennett
China's market regulator and five other agencies jointly issued guidelines mandating accelerated AI adoption in advertising and fostering 'data-intelligent' ad formats, elevating the industry's AI transformation to national policy — signaling a new phase where tech access and regulatory compliance advance in parallel.
What does this policy actually push?
Six agencies jointly released the *Opinions on Vigorously Promoting High-Quality Development of the Advertising Industry in the New Era*, demanding faster deployment of big data, AI, blockchain, and IoT in advertising.
This means → AI adoption in advertising is no longer a voluntary corporate initiative. It is now written into national-level industrial policy, upgrading the signal from "encouraged" to "mandated."
Three specific tracks: R&D in ad-design software and hardware, performance-monitoring tools, and an end-to-end service chain from data collection to real-time analysis to AI-generated content.
How are smaller firms supposed to keep up?
The guidelines explicitly require platform companies, supply-chain leaders, and AI research institutions to offer SME ad firms open-source technology, computing-power support, and hardware sharing.
In plain terms = big tech opens up its AI tools and computing capacity so smaller players can afford to use them. The policy goal is tech access for all, not a windfall for incumbents alone.
Digital ad platforms and third-party providers are also encouraged to leverage computing infrastructure to guarantee processing power for ad production and delivery.
What does 'data-intelligent advertising' look like?
The guidelines back a new big data + AI-driven ad model, oriented around data-driven decisions and real-world scenario deployment.
The key resource: high-quality datasets covering user behavior, consumption preferences, and media touchpoints, applied to innovative ad services for emerging consumption scenarios.
This means → the future competitive edge in advertising is not just creative talent — it is who can chain together data, computing power, and AI generation into a single pipeline.
What is the regulatory hand doing?
Alongside the innovation push, the guidelines explicitly call for tougher enforcement against illegal AI-generated advertising.
They simultaneously require stronger data security and personal-information protection in advertising, enforce tiered data-classification safeguards, and direct firms to collect and use data in compliance.
In plain terms = the policy hits the accelerator and installs the brakes at the same time — AI-powered ads are welcome, but illegal generated content and non-compliant data harvesting will be policed. Where exactly the regulatory boundary falls for AI-generated ads will be the most contested implementation challenge.
What about going global — and where does the money come from?
On the opening-up front, the guidelines support ad firms embedding in global supply chains via service trade and outbound investment, going overseas alongside China's competitive industries.
Firms are encouraged to develop multilingual ad services tailored to cultural differences across markets and to expand into international media platforms.
On fiscal and financial support, qualifying ad firms will receive earmarked government funds, and financial institutions are urged to improve receivables and IP-backed pledge financing. This reflects a policy that goes beyond rhetoric — the funding channels are opening in parallel.
Content is for reference only, not financial advice.