Alibaba CEO Eddie Wu bets heavily on AI as profit plunges 75%

Alibaba is accepting significant pressure on near-term profit to accelerate its artificial intelligence infrastructure. The strategy led by Eddie Wu shows how the AI race is forcing major technology companies to trade some immediate profitability for computing capacity and future growth.

Alibaba’s profit plunged as AI took center stage

Alibaba reported a 75% year-over-year decline in net profit for the quarter ended June 2026. Net income fell to roughly 10.5 billion yuan, compared with 43.1 billion yuan during the same period a year earlier.

The decline came as the company sharply increased spending on artificial intelligence infrastructure. Capital expenditures rose 75% to approximately 67.7 billion yuan during the quarter.

The immediate cost of the AI race

The expansion of computing capacity has increased Alibaba’s costs at a time when the company is trying to turn AI into a significant new source of revenue.

The move highlights an important characteristic of today’s technology market: developing and operating advanced AI systems requires substantial investment before all of the installed capacity can generate a financial return.

Revenue is growing despite pressure on profit

While profitability came under heavy pressure, Alibaba’s total revenue increased by about 9% to approximately 269 billion yuan.

That contrast matters. The company is not simply spending more without generating growth. It is increasing investment while businesses directly connected to AI and cloud computing are expanding rapidly.

Eddie Wu is maintaining Alibaba’s AI infrastructure bet

For Eddie Wu, Alibaba’s CEO, the increase in investment needs to be viewed as a long-term strategic bet. The company wants to expand the capacity required to meet rising demand for AI services.

Eddie Wu is leading Alibaba’s expansion in artificial intelligence, cloud computing and proprietary infrastructure.

A 380 billion yuan investment plan

Alibaba has committed to investing 380 billion yuan in AI infrastructure and cloud computing between 2026 and 2029.

The scale of the project shows that the company no longer views artificial intelligence as simply another product feature. The technology has become central to Alibaba’s infrastructure and growth strategy.

The expectation of a three-year payback

Wu said that, based on the current average margins of AI products, investments in computing capacity could reach break-even in roughly three years.

That timeline turns the decision into a long-term financial bet. Alibaba needs to increase infrastructure utilization while also improving the monetization of its services so the investment can generate the expected return.

Alibaba Cloud shows where the strategy is starting to work

The clearest evidence that Alibaba’s AI strategy is about more than simply increasing spending can be seen in the performance of its cloud computing division.

Alibaba Cloud’s external revenue grew 45% during the quarter, reaching approximately 48.4 billion yuan. Growth was driven primarily by demand for computing capacity and artificial intelligence-related products.

Businesses are driving demand

The expansion of enterprise AI is increasing the need for infrastructure capable of training, running and integrating models into corporate systems.

That creates an opportunity for Alibaba beyond developing its own models. The company can monetize infrastructure that other businesses use to build AI-powered applications.

AI is becoming more than a product bet

The shift also helps explain why Alibaba is investing simultaneously in models, cloud services, chips and AI agents.

The strategy is designed to control different parts of the technology stack. The greater the integration between these components, the greater Alibaba’s potential ability to reduce costs, improve margins and capture revenue across multiple layers of the market.

This transformation reflects a broader shift in how AI infrastructure and computing capacity are influencing the competitive position and value of technology companies. The Notícia Tech has analyzed this broader change in how AI is changing the value of technology companies.

Proprietary chips could change the economics of AI infrastructure

One of the strategic elements of Eddie Wu’s bet is Alibaba’s growing use of internally developed chips.

Alibaba is expanding the use of proprietary technology to reduce dependencies and improve the economics of its AI infrastructure.

Less dependence on commercial chips

AI expansion requires enormous amounts of computing power, making the cost of accelerators and other components an important variable in the profitability of AI services.

Developing and deploying proprietary chips could give Alibaba greater control over the infrastructure used in its data centers.

Margins could become decisive

If Alibaba can increase the utilization of its proprietary chips and improve infrastructure efficiency, the cost of operating AI services could decline over time.

That possibility is important to Wu’s investment thesis. The return does not depend only on selling more services. It also depends on building an infrastructure platform capable of operating those services at better margins.

Alibaba’s bet is part of a much larger race

Alibaba’s decision to continue investing despite the sharp decline in profit is not happening in isolation. Major technology companies are increasing computing spending because AI capacity has become a strategic asset.

Alibaba is competing not only for users, but also for infrastructure, models, developers and enterprise customers.

The race for computing capacity

The growth of AI agents and enterprise applications is increasing the amount of computing required to run these technologies at scale.

In this environment, having enough infrastructure can be as important as having a competitive model. Companies that fail to keep pace with demand may face capacity constraints or higher costs when relying on third-party infrastructure.

Alibaba wants to turn scale into an advantage

Wu’s strategy is based on the idea that today’s investment can create an operational advantage in the future.

If demand continues to grow, the infrastructure being built now can support more customers and products. The challenge will be turning that increased scale into recurring revenue and, eventually, stronger profitability.

Eddie Wu is betting that AI will pay the bill in the future

Alibaba’s strategy reveals an important shift in how major technology companies are approaching artificial intelligence.

The company is accepting a significant short-term decline in profit to build capacity in a technology it considers fundamental to the coming years.

Alibaba is trying to turn investments in infrastructure, models and AI services into a growth platform for the years ahead.

The risk is the return on investment

The central question is no longer simply how much Alibaba can invest, but whether it can turn that capital into sustainable growth.

The 45% increase in Alibaba Cloud’s external revenue is a positive signal. However, the company still needs to demonstrate that demand will be strong enough to justify the enormous amount of capital being directed toward infrastructure.

Wu’s strategy will ultimately be tested by execution

The expectation of recovering the investment in roughly three years creates a clear benchmark for Eddie Wu’s strategy.

If AI revenue continues to grow and infrastructure achieves greater scale, Alibaba could turn the current pressure on profit into a competitive advantage. If monetization fails to keep pace with investment, financial pressure could persist.

That equation is what makes Alibaba’s strategy relevant to other companies. The AI race is no longer simply about choosing a model or adopting a tool. It is increasingly about deciding how much capital an organization is willing to commit to building AI capacity.

For companies following this transformation, the expansion of enterprise AI services also shows why infrastructure is becoming a central part of digital strategy. The Notícia Tech has already examined this shift through how ChatGPT’s integration with Google Drive is changing AI use inside businesses.