China’s largest technology companies are signaling a major acceleration in domestic semiconductor deployment, indicating that the country’s artificial intelligence ambitions are increasingly being built around homegrown chips even as reports emerge that Nvidia could regain limited access to the Chinese market.

Fresh comments from executives at Tencent and Alibaba show that Beijing’s drive for technological self-sufficiency is no longer merely a policy aspiration. It is rapidly becoming an operational reality inside China’s AI infrastructure ecosystem.

The shift comes after years of escalating U.S. export restrictions aimed at limiting China’s access to advanced semiconductors critical for training and deploying sophisticated AI systems. Washington’s controls effectively forced Chinese firms to rethink their dependence on Nvidia’s graphics processing units, long regarded as the global standard for artificial intelligence workloads.

Now, Chinese technology giants appear to be building a parallel ecosystem capable of reducing that reliance.

Tencent Chief Strategy Officer James Mitchell said the company expects a “substantial increase” in capital expenditure this year, especially in the second half, as more domestically designed chips become available.

Mitchell said supply of Chinese-designed GPUs would “progressively” ramp up throughout the year, adding that manufacturing output was expanding both inside China and in “neighboring countries,” a phrase that likely reflects Beijing’s broader effort to diversify semiconductor supply chains beyond areas vulnerable to U.S. export pressure.

The comments come boldly because Tencent is one of China’s largest consumers of AI computing power through its cloud, gaming, social media, and enterprise businesses. Increased deployment of domestic chips by a company of Tencent’s scale would provide a substantial commercial boost to Chinese semiconductor firms attempting to challenge Nvidia’s dominance.

China has spent years trying to develop alternatives to Western semiconductor technology, but the U.S.-China technology war dramatically accelerated those efforts. Since Washington blocked Nvidia from selling its most advanced AI chips to China, companies including Huawei, Moore Threads, and MetaX have intensified product launches, fundraising, and public listings in an effort to fill the vacuum.

The momentum is now beginning to show in financial performance. Chinese chip firms have reported surging revenues as local demand shifts toward domestic suppliers under both political encouragement and practical necessity.

Alibaba’s earnings call provided further evidence that China’s AI giants are internalizing semiconductor development rather than depending solely on external suppliers. Executives said Alibaba’s semiconductor arm, T-Head, had achieved scaled mass production of proprietary GPU chips used in the company’s cloud-computing infrastructure.

The company framed its chip development programme not merely as a technological achievement but as a strategic advantage in a constrained global semiconductor environment.

“In an environment of compute scarcity, this structural advantage is favorable to our revenue growth and gross margin improvement,” an Alibaba executive said.

That statement reflects a deeper reality in the global AI race, where computing power has become one of the world’s most valuable resources. As demand for AI infrastructure explodes, access to advanced chips increasingly determines which companies and countries can scale large language models, autonomous systems, and next-generation AI applications.

Alibaba also hinted at ambitions extending beyond internal usage. The company suggested it may eventually sell servers equipped with its own chips or co-build data centers with external partners, signaling its intention to become a broader infrastructure provider within China’s AI ecosystem.

The development aligns with Beijing’s long-term industrial policy objectives, which seek to reduce exposure to foreign technology chokepoints in critical sectors such as semiconductors, cloud computing, and AI.

Yet even as China’s domestic ecosystem expands, Nvidia’s technology remains difficult to replace completely.

Reuters reported Thursday that the U.S. government may have authorised several Chinese firms, including Alibaba and Tencent, to purchase Nvidia’s H200 chips, among the company’s most advanced AI processors. The report said no H200 shipments had yet been produced.

The situation remains uncertain. Asked about the report, U.S. Treasury Secretary Scott Bessent said he was unaware of any approval and noted that export licensing decisions fall under the Commerce Department’s authority.

Over the past year, Washington has repeatedly adjusted chip export rules, sometimes permitting sales of downgraded AI processors such as Nvidia’s H20 while blocking more advanced systems. At the same time, Chinese authorities have reportedly encouraged local companies to prioritize domestic alternatives.

Analysts say Nvidia’s technology would still be highly attractive to Chinese firms because the next phase of AI competition increasingly depends not just on training models but on scaling inference, the computational process required to run AI applications at mass scale.

Neil Shah said China’s transition toward so-called “agentic AI,” systems capable of carrying out complex autonomous tasks, will require more advanced semiconductor performance.

“We are seeing the Chinese AI roadmap pivot towards ‘domestic-only’ with AI training infrastructure,” Shah told CNBC.

However, he added that the competitive battle has shifted toward “massive inference scaling,” where Nvidia’s chips still maintain significant advantages.

“Chinese hyperscalers simply cannot afford to wait,” Shah said, arguing that Nvidia’s H200 chips could become part of a hybrid AI infrastructure combining both Chinese and U.S. hardware.

That hybrid scenario increasingly appears to define the current phase of China’s semiconductor strategy. Beijing is aggressively building domestic capabilities while still attempting to retain selective access to the world’s best foreign technology wherever possible.

The result is a dual-track system in which Chinese firms pursue self-sufficiency not necessarily because domestic alternatives are fully equivalent yet, but because geopolitical uncertainty has made reliance on foreign chips strategically risky.

China was historically one of Nvidia’s largest markets, and continued restrictions threaten billions of dollars in lost revenue while creating space for Chinese competitors to mature technologically. But the broader objective extends beyond replacing Nvidia for China. The country is trying to establish an entirely sovereign AI stack spanning chips, cloud infrastructure, operating systems, and AI models, reducing vulnerability to future sanctions or export controls.

The outcome of that effort could shape the global balance of technological power for years to come.

Young People, the best time to audition for a job is when there is no opening. And the best time for an entrepreneur to raise money in Nigeria is when he or she is not actively fundraising. Why? Because by the time opportunities formally arrive, many of the real decisions may have already been made.

Fundraising does not truly begin in conference rooms, board meetings, or investor presentations. It often starts years earlier, in dormitories, canteens, offices, classrooms, churches, villages, and in ordinary interactions where people quietly observe who you are. What you did ten years ago can determine whether your classmate, colleague, uncle, friend, or former teammate decides to support you today when they have resources to invest.

At Tekedia, I often explain that much of life runs on what I call ITT Capital: Integrity, Trust, and Tenacity. This capital is not built during fundraising rounds. It is not assembled during a crisis or activated when money suddenly becomes necessary. ITT Capital compounds over years through repeated interactions and transactional moments.

Think about it: can your classmate confidently give you money? Can your colleague at work support your idea? Can your auntie invest in your business? If people around you have the resources but consistently hesitate, perhaps the issue is not the economy or timing. Perhaps your ITT Capital before them is weak.

Investment itself has two phases: the transactional and the relational. ITT Capital governs the transactional phase. People first watch your behavior, reliability, discipline, and consistency. If you perform well there, you unlock the relational phase where trust deepens and opportunities emerge. And from that relationship comes the possibility of long-term support.

Within that relationship, however, another important question always emerges: in moments of truth, who comes first: you or the person who trusted you enough to invest? The individual, institution, or company that believed in you should always matter deeply in your thinking. The best founders understand stewardship. They understand that money entrusted to them carries responsibility.

Get it from me: people rarely invest because they merely like an idea. They invest because they respect people and believe the builder has a higher chance to grow their money. An investor invests in YOU before investing in your company because the investor has modelled that you are going to handle this fund better than he or she can! It is a sacred economic positioning because you cannot give money to someone you think you can do better than.

Forget the pitch deck for a moment. Forget the grand narrative and the product story. The first “company” investors evaluate is YOU. If they do not like the product called YOU, they may never buy shares in the company you are building. To build a great company, first build yourself. Because before capital enters a business, confidence enters a person. As you do that, remember that no career can blossom if people cannot recommend you in your absence. And for that to happen, you must reduce the burden for them to do that by boosting your ITT.