Chongqing’s municipal authorities have unveiled a targeted incentive package to accelerate the integration of artificial intelligence into manufacturing, offering cash awards for projects that build industrial data assets, trusted data spaces, vertical large models and intelligent agents. The city’s economic and information commission and finance bureau published a set of measures that include up to RMB5 million (roughly $700,000) for single projects and specific caps of RMB3 million ($420,000) for industrial datasets and trusted data spaces and RMB2 million ($280,000) for developing and promoting vertical models and intelligent agents.
The package bundles 20 measures across six areas, signalling a comprehensive municipal effort to seed an AI-for-manufacturing ecosystem. Local authorities will also reward firms whose projects are selected as Ministry of Industry and Information Technology (MIIT) AI exemplar cases (RMB500,000, about $70,000) and will offer RMB2 million for building innovation platforms and carriers. The measures are explicitly aimed at enterprises and third-party professional bodies that can generate high-quality industrial data and practical AI applications rather than generic consumer models.
This municipal push mirrors a broader, nationwide pivot: Beijing has emphasised breakthroughs in compute chips, industrial models and application ecosystems as the next phase of China’s AI strategy. Chongqing’s incentives are pragmatic — focused on the costly but high-value building blocks of industrial AI (data, trustworthy data sharing frameworks, and domain-specific models) rather than general-purpose foundational models alone. For a city with heavy manufacturing, automotive supply chains and capital-intensive industry clusters, the policy is an attempt to translate central priorities into local competitive advantage.
For companies, the subsidies are sizeable but typically insufficient to fund large-scale pretraining of foundation models; they are, however, well matched to the economics of constructing curated industrial datasets, running domain-specific fine-tuning, building pilot intelligent agents and scaling demonstrators across factory floors. The design encourages collaboration between manufacturers, cloud and systems providers, and specialist data firms, and will likely spur third-party firms that offer data-labeling, secure data-sharing platforms and verticalized model development.
There are risks and trade-offs. Municipal subsidies can accelerate useful deployments, but they can also create distortions: overlap among cities chasing the same AI winners, capital flowing to subsidy-savvy firms over technically superior ones, and a patchwork of local standards for data sharing that could impede interoperability. Trusted industrial data spaces, if implemented well, can reduce data silos and enable safer model training, but they raise governance questions about ownership, cross-border transfer and industrial cybersecurity.
Ultimately Chongqing’s policy is notable less for the headline sums than for its focus. By prioritising industrial datasets, trusted data spaces and vertical models, the city is betting that applied AI — not only glitzy general-purpose models — will deliver productivity gains to manufacturing. If other industrial centres follow suit, China’s next wave of AI development may be defined by many smaller, domain-specific models and integrated on-prem/cloud intelligent agents tailored to factory needs rather than a single dominant foundation model.