Increased Confidence Among Sci-Tech Enterprises Spurs Bolder Investments: New STAR Market Policy Channels Capital into AI Super Track

Shanghai Securities News   Liu Yihe, Sun Xiaocheng

For AI enterprises still in the throes of technological breakthroughs, the threshold for listing on the STAR Market is being significantly lowered. Recently, China Securities Regulatory Commission (CSRC) released the Opinions on Establishing a Sci-Tech Growth Tier on the STAR Market to Enhance Institutional Inclusiveness and Adaptability, which reinstates and expands the application of the fifth set of listing standards for unprofitable companies. This move is directly aimed at cutting-edge sectors like AI, which typically feature "value realization ahead of profits". This reform is expected not only to reshape the development trajectory of such enterprises but also to drive a deep resonance between the capital market and the AI industry.

"Value Realization Ahead of Profits" in the AI Industry

Centered around data, algorithms, and computing power, the AI industry spans a wide range of application scenarios from large models and embodied intelligence to autonomous driving. While widely regarded as a "golden track", it also faces a capital-intensive "cash burn" dilemma due to heavy R&D investments. Embodied intelligence companies must engage in interdisciplinary R&D across hardware, algorithms, and software, while managing complex supply chains. Meanwhile, leading large model firms—such as OpenAI and China's "Six Little Tigers"—despite securing substantial funding, remain heavily reliant on sustained capital infusions from the primary market.

In reality, AI companies commonly face a dual dilemma. On one hand, with competitive dynamics still unfolding, they are compelled to "stockpile resources", allocating a significantly higher proportion of spending to R&D than the industry average. On the other hand, long profitability cycles create uncertainty around securitization prospects, which in turn constrains their fundraising capacity in the primary market. The chairman of a Hong Kong-listed AI company noted that early-stage financing for domestic startups is often restricted by their intended listing destination. Compared with the Nasdaq's more accommodating stance toward unprofitable companies, the A-share market's previous profitability thresholds led institutional investors to adopt a more conservative approach—at times even operating under the logic of "only investing money they can afford to lose".

Looking Ahead: "Giving a Boost"

At the heart of the new policy lies a fundamental breakthrough—removing the rigid requirement for profitability. Recently, several unprofitable AI companies, including Moore Threads and MetaX, have been accepted for review on the STAR Market, sending a clear signal: the capital market is leveraging institutional innovation to give early-stage tech enterprises a boost. According to Zhang Ju, CFO of UBTECH, the creation of the Sci-Tech Growth Tier has normalized the listing of unprofitable companies, offering AI startups a new path to independent IPOs. This marks a shift from the previous development outlook, which was largely centered on being acquired.

For enterprises, the new policy eases short-term profitability pressure, allowing them to concentrate resources on technological breakthroughs and real-world application deployment. Sun Huifeng, Chairman of Shangqi Digital, stated that the company plans to leverage the clearly defined listing thresholds under the new policy to expand its industry-specific datasets to 100 and grow its user base to the tens of millions, thereby transforming its large model capabilities into intelligent decision-making services. For small and medium-sized enterprises facing competition from tech giants, the policy removes the need to scale back strategic investments in pursuit of short-term profits. Instead, they can focus on developing modular products by harnessing the benefits of declining marginal costs.

Primary Market Now "More Willing" to Invest in AI

The new STAR Market policy is also reshaping investment logic in the primary market. Xia Chao, head of Sci-Tech CAP, admitted that past investment strategies focused more on short-term profit validation. Today, however, there is a stronger commitment to supporting leading enterprises in long-term tracks such as sovereign computing power, with a shift from "picking ripe fruit" to "nurturing seedlings". A representative from Lenovo Capital noted that the differentiated criteria of the fifth set of listing standards—centered on "market capitalization + R&D investment"—align well with the valuation characteristics of AI companies, where technology carries more weight than revenue. This mirrors the success seen in the biopharmaceutical sector: following the listing of around 20 companies under the fifth set of standards, 17 domestically developed Category 1 new drugs gained approval, with R&D intensity significantly exceeding the A-share market average.

Institutions are actively working to build a closed-loop ecosystem around the AI industry chain. Xia Chao revealed that his fund plans to collaborate with computing power application companies to establish a domestic substitution pathway, creating a virtuous cycle of "investment–technology–application". A source close to regulators noted that if AI can achieve "capital nourishment" through the STAR Market, it will set a precedent for other hard-tech emerging industries, fostering a deeper integration between the capital market and industrial upgrading.