Multiple regions roll out a new round of artificial intelligence industry support policies

In recent times, multiple regions across the country have introduced a new round of artificial intelligence (AI) industry support policies. For example, Beijing’s Economic and Information Technology Bureau has officially kicked off the public solicitation to identify the organizations responsible for building high-quality data sets that enable AI-enabled new industrialization in the third batch of 2026. Meanwhile, the Zhangjiang Science City Administration Committee in Shanghai has opened the application channel for the second-quarter special-coupon policy for the Zhangjiang AI Innovation Town.

According to a review, since the beginning of this year, local AI industry support policies have generally shown three major characteristics. First, the driver has shifted from technology R&D to scenario implementation. Second, support has moved from broad-based assistance to targeted guidance. Third, relevant policies have continued to strengthen the market orientation of support.

Experts interviewed by Securities Daily said that the evolution of domestic AI industry support policies reflects not only China’s stage-based characteristics in the AI industry’s shift from tackling technological bottlenecks to value transformation, but also provides clear guidance for enterprises to plan their strategies across different regions and different fields.

Market orientation continues to be strengthened

Since the beginning of this year, around the full life cycle of AI industry development, many places have rolled out a series of subsidy measures, gradually building an industry support “toolbox” that includes computing power support to reduce costs, R&D subsidies to solve tough problems, scenario awards to promote implementation, and tax incentives to stabilize expectations. With these tools working in coordination, China’s AI commercialization achievements are accelerating in delivery.

Reporters, after reviewing the detailed subsidy rules across regions, found that scenario application awards and subsidies are the fastest-growing category. At the national level, the funding support amount for a single project under these subsidies typically ranges from 1 million to 20 million. The subsidy disbursement ratio remains at 15% to 30%, covering a variety of vertical application fields such as industrial manufacturing, government services, finance, and healthcare.

It is worth noting that the application scenarios covered by local awards and subsidies are continuously expanding. Taking the 《Several Measures of Beijing Municipality on Supporting Industrial Enterprises to Improve Quality and Efficiency》 issued in June as an example, the policy clearly supports enterprises in purchasing and consuming tokens (Token) to carry out AI applications. For enterprises that meet the requirements, funding support is provided based on their actual use of Tokens.

In addition, another notable feature of AI industry support policies in the course of this year is that policy support is shifting from “broad-spectrum” general technology support to “precision irrigation” targeting specific vertical sectors. Taking the AI micro-short drama sector as an example, the core of relevant policies lies in incentivizing large-scale applications of AI technologies in content production, virtual human creation, and overseas distribution. For example, in May, Shanghai issued the 《Several Measures of Shanghai Municipality on Accelerating High-Quality Development of AI-Enabled Micro-Short Dramas》, which proposes to award top micro-short drama projects (including AI micro-short dramas) that give equal emphasis to value, content, and quality, with the highest reward of 3 million.

Song Xiangqing, Vice Chairman of the China Society of Business Economics, told Securities Daily reporters that the logic behind this shift is that, as AI foundational technologies (especially large-model capabilities) continue to mature, the core of industrial development has moved from “whether it can be done” to “where to use it and how to use it well.” Therefore, policy resources have started to tilt toward vertical tracks that have high industrial value, strong social externalities, and high compatibility with AI technologies.

It is also worth noting that, this year, AI industry support policies issued across regions generally strengthen market orientation, with support methods accelerating the shift from upfront direct disbursement of funds to “award-in-lieu-of-subsidy” and “post-subsidy” models that are deeply tied to enterprises’ actual market results. For example, the 《Notice on Issuing the 2026 Implementation Guide for Beijing’s High-Precision and Advanced Industry Development Project Funds and Funds for Supporting the Development of Small and Medium-Sized Enterprises (First Batch)》 shows that, for high-quality solutions that apply vertical large models in the industry for the first time to address the demand for typical application scenarios in key industries and that are actually implemented, support will be provided at 15% of the actual remittance amount for the non-hardware portion in the solution. The amount supported for a single enterprise will not exceed 30 million.

Fu Yifu, a special research fellow at CMB Suzhou? Bank (Sushang?), told Securities Daily reporters that the evolution of AI industry support policies is an important indicator of the industry moving toward maturity. Market-oriented, post-implementation award-and-subsidy mechanisms eliminate the drawbacks of traditional subsidies—“placing emphasis on project approval, while neglecting implementation; and focusing on weak results.” Using market remittance, scenario implementation, and industrial enablement as the core evaluation criteria will make enterprises focus more on genuine needs and refine high-quality solutions. At the same time, targeted support for precise vertical tracks and diversified, factor-based subsidy approaches can precisely match the end-to-end needs of the AI industry—from technology R&D to commercialization implementation—effectively activating a positive virtuous cycle of large-model development, scenario application, and industry enablement.

Enterprises apply relevant policies well

At present, China’s AI industry support policies exhibit distinct characteristics of being scenario-based, more finely targeted, and market-oriented. This is an effective way to comprehensively move the AI industry from the stage of technological breakthroughs to the stage of value transformation.

According to the latest invoice data from the State Taxation Administration, from January to May, the year-on-year growth rates of sales revenue for robot and intelligent vehicle-mounted equipment manufacturing were 27.7% and 46.3%, respectively. The level of industrial intelligentization enabled by AI has continued to improve.

Based on the context and logic of policy evolution, experts interviewed by Securities Daily generally believe that the subsequent evolution of AI industry support policies will show three clear directions. First, the focus of subsidies will accelerate the shift from “subsidizing technology R&D” to “supporting implemented scenarios.” Second, policy tools will be upgraded from single funding subsidies to multiple combined empowerment measures. Third, cross-regional industrial coordination and supporting mechanisms will be continuously improved and advanced in depth.

Against the backdrop of changes in industrial policy, for AI industry-chain enterprises to secure advantages in the next round of industry competition, the key lies in fully understanding the underlying logic of policy evolution, precisely aligning enterprises’ development strategies with national and local policy directions, and building a multi-dimensional portfolio of policy tools tailored to their own development.

When asked how to make good use of the relevant subsidy policies, Fu Yifu said that AI enterprises at different development stages have significant differences in resource endowments, technological maturity, and commercialization capabilities. Therefore, it is necessary to adopt differentiated application pathways to maximize the marginal utility of the policies. For example, for start-up micro teams, cash-flow relief and reducing computing power costs are the core priorities. They should prioritize applying for low-threshold inclusive small vouchers for computing power, venues, and tax-related support offered across different places, while avoiding high-threshold, long-cycle major projects. For growth-stage enterprises that already have mature products and market foundations, applications can shift toward performance-based scenario rewards and R&D breakthrough special projects linked to sales revenue and collections.

【Author: Tian Peng】 (Editor: Wen Jing)

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                                                            Artificial Intelligence