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China to Launch New STAR Market Segment for Pre-Profit Growth Companies

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China’s securities regulator announced plans to create a new segment within Shanghai’s tech-focused STAR Market designed specifically for pre-profit growth companies, aiming to bolster innovation amid rising China-U.S. tensions in trade and technology.

The upcoming “growth segment” will support companies that have yet to turn a profit but demonstrate significant technological breakthroughs, strong commercial potential, and substantial investment in research and development, according to guidelines from the China Securities Regulatory Commission (CSRC).

CSRC Chairman Wu Qing emphasized the need for robust capital market support for both tech giants and emerging startups, highlighting ongoing reforms to strengthen China’s financial ecosystem amid shifting global economic and trade dynamics.

The regulator will also establish mechanisms to bring in experienced institutional investors to the STAR Market, reinforcing its role as a platform to advance China’s strategic goal of achieving technological independence and global leadership.

The CSRC further pledged to facilitate listings from companies working on frontier technologies, including artificial intelligence and aerospace, aligning with China’s ambitions in cutting-edge sectors.

This move comes as many Chinese firms are considering public listings in Hong Kong, which is actively attracting new listings amid a recovering stock market environment.

Taiwan Adds Huawei and SMIC to Strategic Export Control List Amid Security Concerns

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Taiwan has placed China’s tech giants Huawei Technologies and Semiconductor Manufacturing International Corp (SMIC) on its export control list, requiring Taiwanese firms to obtain government approval before exporting any products to these companies.

The additions were part of a recent update to the Ministry of Economic Affairs’ trade administration strategic high-tech commodities entity list, announced on June 10. Alongside Huawei and SMIC, the update included 601 entities from countries such as Russia, Pakistan, Iran, Myanmar, and China, including groups like the Taliban and al Qaeda.

Taiwan’s trade administration stated the review and update were driven by “prevention of arms proliferation and other national security considerations.” It urged manufacturers to comply with export control regulations, fulfill verification obligations, and carefully assess transaction risks.

Taiwan is home to TSMC, the world’s largest contract chipmaker and a key supplier to AI leader Nvidia. Both Huawei and SMIC are pivotal to China’s ambitions in chips and artificial intelligence and have been striving to close the technology gap.

Taiwan already enforces strict chip export controls on Taiwanese companies that manufacture domestically or supply Chinese firms, reflecting ongoing tensions between Taipei and Beijing, which claims Taiwan as its territory.

Huawei is also subject to U.S. export restrictions barring access to American and foreign-made goods involving U.S. technology, including chips manufactured by TSMC. Last year, TSMC was ordered by the U.S. Commerce Department to halt shipments of certain chips to Chinese customers, including Huawei and Sophgo, a Chinese chip designer linked to Huawei’s AI processor.

Taiwan’s government has repeatedly pledged to combat Chinese efforts to steal technology and attract Taiwanese chip talent, emphasizing the strategic importance of the semiconductor sector.

SMIC, China’s largest chipmaker, continues to invest heavily to expand capacity amid U.S. export curbs, aiming to boost China’s domestic semiconductor capabilities.

Unglamorous World of Data Infrastructure Drives Surge in AI-Focused Tech M&A

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Despite a slowdown in global dealmaking due to tariffs and geopolitical uncertainty, the data infrastructure sector is booming as legacy tech giants scramble to secure their positions in the AI race. Companies that handle the vast volumes of data required to train advanced AI models have become key acquisition targets for firms like Meta, Salesforce, and ServiceNow, eager to compete with leaders such as OpenAI, Google, and Anthropic.

“AI without data is like life without oxygen, it doesn’t exist,” said Brian Marshall, global co-head of software investment banking at Citi, highlighting how data management has taken center stage in the tech industry’s current moment.

Technology deals have been one of the few bright spots in a subdued M&A market, accounting for $421 billion out of the $1.67 trillion in global deals announced in the first five months of 2025—roughly 25% of total M&A volume. This marks a steady rise from 20% in 2024 and 17% in 2023. Notably, nearly 75% of the value of tech deals involves AI software makers.

Goldman Sachs Managing Director Matthew Lucas described enterprise data as the “most dynamic area in software M&A right now,” emphasizing that speed and being first to market are critical, driving companies to acquire rather than build their own capabilities.

Investment bankers identify companies like Confluent, Collibra, Sigma Computing, Matillion, Dataiku, Fivetran, Boomi, and Qlik as likely acquisition targets. These firms specialize in integrating, analyzing, and managing data on cloud platforms—capabilities essential for effective AI deployment.

Executives from Boomi, Dataiku, Fivetran, and Qlik expressed no surprise at the increased attention. Dataiku CEO Florian Douetteau noted that “messy, siloed data” has long limited analytics potential, but the urgency of AI has made resolving these issues existential for businesses.

Recent multibillion-dollar acquisitions illustrate this trend. Meta’s $14.8 billion deal for a 49% stake in data-labeling company Scale AI, Salesforce’s $8 billion plan to buy data integration firm Informatica, and ServiceNow’s acquisition of data catalog platform Data.world exemplify how legacy tech companies are investing heavily to own the data pipeline critical for AI.

Globally, generative AI spending is forecast to hit $644 billion in 2025, a 76.4% increase from 2024, underscoring the scale and pace of AI investment.

IBM also recently closed its acquisition of data management company DataStax, aiming to improve handling of unstructured data for its AI platform.

However, dealmakers caution that acquiring data infrastructure alone does not guarantee AI success. Proper organization and filtering of data are essential to avoid errors, as seen when Air Canada faced legal issues over bad AI chatbot advice due to poor data input.

“A lot of companies have a huge amount of data, but they’re learning that you can’t just funnel every piece of data you have into an AI engine without organization and expect correct results,” said Brian Mangino, partner at Latham & Watkins.

The rapid pace of acquisitions and the high stakes in AI competition highlight how data infrastructure—though less glamorous than AI algorithms themselves—is becoming the backbone of future tech innovation.