China’s artificial intelligence funding race gathered further momentum after video-generation startup Kling AI secured one of the largest financing rounds in the country’s generative AI sector, drawing backing from some of China’s biggest technology companies as competition with U.S. AI leaders intensifies.

Kuaishou Technology said Thursday that a consortium of investors led by Alibaba and Tencent will inject more than 19 billion yuan ($2.80 billion) into Kling AI, valuing the AI video platform at about $15 billion on a pre-money basis.

The deal comes at a time when China’s AI ecosystem is attracting record levels of funding. Technology companies have raised roughly $3.1 billion through stock market listings in China this year through mid-June, according to Reuters calculations, more than five times the amount raised during the same period last year. Investors have increasingly shifted their attention toward AI-related businesses as Beijing pushes technological self-sufficiency and domestic companies accelerate efforts to compete with leading U.S. developers.

Under the terms of the fundraising, Kling AI can admit one additional investor within the next two months, bringing the total financing to as much as 20.45 billion yuan. Once the transaction is completed, Kuaishou’s ownership in Kling AI will fall to approximately 68% from its current 100%, while the parent company will retain majority control over the fast-growing business.

The investor lineup includes some of China’s most influential technology firms. Alibaba, Tencent and Baidu have all agreed to acquire stakes in Kling AI, highlighting broad industry confidence in AI-generated video as one of the fastest-growing segments of generative artificial intelligence.

The participation of China’s internet heavyweights is notable because each company is simultaneously investing billions of dollars into its own AI ambitions. Alibaba has sharply increased spending on AI infrastructure and cloud computing while developing its Qwen family of large language models. Tencent has expanded investments in foundation models and AI applications across gaming, advertising and enterprise software. Baidu continues to commercialize its Ernie models while also developing AI chips and autonomous driving technologies.

Kling AI has emerged as one of China’s leading AI video-generation platforms, competing against both domestic rivals and international products such as OpenAI’s Sora and Google’s Veo. Demand for AI-generated video has surged over the past year as enterprises, advertisers, filmmakers and content creators seek cheaper and faster methods of producing high-quality visual content.

The company’s rapid commercial expansion appears to be validating investor enthusiasm. Kling AI generated 650 million yuan in revenue during the quarter ended March, more than quadrupling from a year earlier, demonstrating that enterprise demand for AI-generated content is translating into meaningful revenue growth rather than remaining purely experimental.

The strong financial performance also distinguishes Kling AI from many AI startups that continue to prioritize user growth over monetization. As investors focus on commercial viability following the first wave of generative AI adoption, companies capable of producing significant recurring revenue have attracted premium valuations.

Analysts said the fundraising valuation itself broadly matched market expectations, but the caliber of participating investors stood out.

Citi analysts described the shareholder roster as “impressive,” noting that attention will now shift toward Kling AI’s next-generation product upgrades, which are expected to determine whether the company can maintain its rapid growth and defend its leadership position in China’s increasingly crowded AI video market.

The financing is seen as part of a broader restructuring strategy by Kuaishou. In May, the company acknowledged it was exploring options for reorganizing Kling AI after media reports suggested a potential spin-off. At the time, management emphasized that discussions remained preliminary, but Thursday’s capital raise represents the clearest step yet toward establishing Kling AI as a more independent business capable of attracting outside capital.

Creating standalone AI subsidiaries has become a common strategy among major technology companies seeking to unlock value while giving high-growth AI businesses greater operational flexibility. Separate financing also enables AI units to raise capital without placing additional pressure on parent companies already investing heavily in data centers, semiconductors and computing infrastructure.

The transaction arrives amid an escalating global race to finance AI development. Chinese companies are aggressively raising capital to build computing capacity, train increasingly sophisticated foundation models and develop AI applications spanning video, coding, enterprise software and robotics.

That competition mirrors developments in the United States, where companies including OpenAI, Anthropic and xAI have secured record funding rounds to finance massive investments in AI chips and data centers.

Meta Chief Executive Mark Zuckerberg has acknowledged that the company’s sweeping AI-driven restructuring has not delivered the rapid gains management anticipated, offering one of his clearest admissions yet that the social media giant’s aggressive reorganization has fallen short of expectations even as it pours unprecedented sums into artificial intelligence.

Speaking during an internal town hall on Thursday, Zuckerberg told employees that Meta had overestimated how quickly AI agents would transform software development and workplace productivity, while conceding that the company’s restructuring, which included thousands of layoffs and internal transfers, had been more disruptive than executives intended.

His remarks come at a critical juncture for Meta, which has emerged as one of the biggest spenders in the global AI race. The company is projected to invest as much as $145 billion this year in AI infrastructure, contributing to a broader wave of more than $700 billion in AI spending by the world’s largest technology companies. Investors have increasingly scrutinized whether such enormous capital expenditure will translate into meaningful productivity gains and new revenue streams.

Zuckerberg said the company’s expectations for AI-powered software agents had proved overly optimistic.

“In retrospect, the trajectory of the agentic development over at least the last four months hasn’t really accelerated in the way that we expected,” Zuckerberg told employees, according to a recording heard by Reuters.

He added that the company’s strategic bets on its new organizational structure “haven’t come to fruition yet.”

The Meta chief was referring to AI agents, software systems capable of autonomously carrying out complex tasks on behalf of users with minimal human intervention. Much of the technology industry’s current investment cycle is centered on the belief that these systems will eventually automate programming, research, customer service, content creation, and many other knowledge-based tasks.

The comments amount to a rare public acknowledgment that even the world’s largest AI investors are encountering difficulties turning cutting-edge models into immediate productivity improvements.

Zuckerberg also conceded that Meta’s restructuring had not been executed as effectively as management had hoped. The company laid off roughly 10% of its global workforce in May while reassigning about 7,000 employees to AI-focused teams, moves that triggered internal criticism and renewed concerns over employee morale.

“We probably didn’t do as clean of a job on that as we could have,” Zuckerberg acknowledged, according to the recording.

The restructuring was designed to redirect resources toward AI development while reducing spending elsewhere as Meta sought to compete more aggressively against rivals including OpenAI, Anthropic, Google and xAI.

When executives began planning the overhaul earlier this year, they feared Meta was moving too slowly to capitalize on the industry’s rapid evolution.

“The conversations that I was having with our top people when we started planning all this in January and February were that they were worried that we weren’t going to move fast enough to adapt,” Zuckerberg said.

He added that executives at the time were “super optimistic” about emerging AI coding systems such as Anthropic’s Claude Code, believing that such tools would rapidly transform software engineering productivity. That optimism has since moderated as AI agents have proven less capable than many industry leaders initially anticipated.

Still, Zuckerberg maintained that Meta remains committed to its long-term AI strategy and expects the company’s massive investments to begin producing more tangible returns over the coming months.

“I expect that we’ll begin to experience more significant benefits from our AI investments within the next three to six months,” he told employees.

While AI models have demonstrated impressive capabilities in coding, reasoning and content generation, many companies are discovering that integrating those systems into real-world business workflows is proving more complex and slower than expected.

Even so, Meta executives sought to reassure employees that the company’s next generation of AI models is making rapid technical progress.

Alexandr Wang Says Meta’s Catching Up

During the same town hall, Meta’s recently appointed superintelligence chief, Alexandr Wang, said the company’s upcoming frontier model, codenamed “Watermelon,” has reached performance levels comparable to GPT-5.5, according to two people familiar with the meeting.

Wang said the assessment was based on widely followed AI benchmark tests, although he did not specify which benchmarks were used.

“Watermelon, our next model after Avocado, is currently in training,” Wang said during the town hall, according to a person familiar with the meeting.

“Watermelon uses an order of magnitude more compute than Avocado,” he added.

“Avocado” is Meta’s internal codename for Muse Spark, the first model in a new family of AI systems the company introduced in April.

The increased computing requirements illustrate the escalating AI arms race, with companies deploying ever-larger data center clusters and advanced chips to train increasingly sophisticated models.

Wang reinforced that message publicly later on Thursday in a post on X, where he indicated that an updated version of Muse Spark would be released soon.

He said the update would deliver major improvements in coding and agentic capabilities aimed at narrowing the performance gap with competing models.

When asked by an X user when Meta would produce a coding model comparable to Anthropic’s Claude Opus, Wang replied that it would be “pretty soon,” adding that users would like what the company has “cooking.”

This means Meta believes its latest generation of models can substantially improve its competitive position after earlier AI releases received mixed reviews compared with offerings from OpenAI and Anthropic.

The town hall also addressed another controversy that has generated internal criticism. Meta Chief Technology Officer Andrew Bosworth told employees that an internal investigation into the company’s mouse-tracking software found that employee information had not been incorporated into AI model training.

The software, introduced on U.S. employees’ computers in April, monitored mouse movements and digital activity to collect data intended to improve AI systems. The initiative quickly became controversial after employees objected to the level of workplace monitoring. Last month, Meta suspended the program while investigating whether sensitive information had been exposed.

Bosworth said the review concluded that employee data had not been used to train AI models.

He also announced a significant policy reversal if the program resumes.

“For people who are comfortable, that’s great, they can contribute to this kind of great human survey. To people who are not, it is not an issue,” Bosworth told employees.

Unlike the original rollout, which employees were told they could not refuse, Bosworth said any future version of the program would operate on an “opt-in” basis, allowing employees to choose whether to participate.

Meta declined to comment publicly on the town hall discussions. However, the internal admissions underscore the mounting pressure facing Meta and other technology giants as investors demand evidence that record-breaking AI spending will ultimately translate into stronger earnings growth.