Alibaba's AI Transformation and Evolution

Author | Little Cat

Editor | Hard AI

Observing the recent financial reports of tech giants, a significant commonality is the sharp increase in AI investments and its gradual manifestation as a growth driver.

Amazon CEO Andy Jassy emphasized multiple times during the earnings call that AWS's growth stems from strong enterprise demand for AI, stating that "AI will become one of Amazon's largest businesses in the coming decades." Meta has listed AI as a core strategy, with Zuckerberg highlighting that AI is driving improvements in the precision and efficiency of its advertising business.

A consensus is forming in the industry that AI has moved from the early "experimental exploration" phase to a significant "operational leverage" phase driving growth. The procurement of computing power and AI R&D investments at the "tens of billions of dollars" level annually is becoming the norm for top tech players.

Alibaba has demonstrated the same strategic vision in this round of technological transformation. Market perception has shifted accordingly—Alibaba is no longer just China's leading e-commerce platform, but a globally competitive technology company with its strategic focus shifting towards AI.

This transformation is reflected not only in corporate strategic positioning but also validated in technological evolution and industrial applications.

The Foundation of Tech Companies

On May 15, Alibaba announced its Q4 2025 financial report, revealing that the group's overall revenue, excluding RT-Mart and Intime, grew by 10% year-on-year, with cloud intelligence business revenue increasing by 18%, further up from 13% in the previous quarter. Notably, external commercialization revenue grew by 17%, and public cloud revenue continued to accelerate.

Even more noteworthy is that AI-related product revenue has maintained triple-digit year-on-year growth for seven consecutive quarters, making the tech business a new growth engine for the company.

The company previously announced plans to invest over 380 billion yuan in Capex over the next three years to upgrade cloud computing and AI infrastructure—this amount exceeds the total related investments of the past decade.

This aligns with the trend of global tech giants entering the mid-stage of the S-curve in AI capital expenditures, where large-scale, sustained investments in AI infrastructure have become industry standards.

In this quarter, the company's Capex was 24.6 billion yuan, and during the earnings call, the company stated: There are some uncertainties in the global AI supply chain, but the growth in customer demand is certain. We see that customer demand for cloud and AI continues to grow, representing a historic opportunity for the next 10-20 years, which will not change due to short-term fluctuations in the supply chain. Alibaba's confidence and determination to invest in cloud and AI infrastructure will not waver.

In light of the enormous potential brought by the certainty of AI demand, Morgan Stanley previously projected that Alibaba Cloud's revenue growth would accelerate to 25% in the fiscal year 2026. Thus, AI-driven tech business will provide Alibaba with more growth momentum in the foreseeable future, truly making it a globally leading technology company.

Reaching the Pinnacle of Open Source Models, Maintaining Alibaba's Global Competitiveness in Technology

For top tech companies, technological strength is the foundation of their existence.

Alibaba's accumulation in the AI field is concentrated in its self-developed Tongyi Qianwen (Qwen) model series At the end of April, Alibaba open-sourced the next-generation Tongyi Qwen model Qwen-3, which has only one-third the parameters of DeepSeek-R1, significantly reducing costs while outperforming in performance. Upon release, it successfully topped multiple global authoritative open-source model rankings and was quickly adopted by major global development communities and enterprises.

In addition to model performance, Alibaba's unwavering open-source strategy has played a crucial role. Looking towards the distant future, Alibaba CEO Eddie Wu has clearly stated in multiple public occasions that "pursuing the realization of AGI" is the primary goal of the group's AI strategy. Open-source is the strategic consideration behind this.

Firstly, on the long journey towards AGI, the ultimate goal of artificial intelligence, no single company or organization can monopolize all innovations and breakthroughs.

Open-source is an effective way to gather global wisdom, accelerate technological iteration, and share exploration risks. By making the core model available to developers, research institutions, and enterprises worldwide, Alibaba can build a vibrant Qwen ecosystem.

Secondly, the collective wisdom of the open-source community can give rise to innovative applications and model variants that transcend the boundaries of individual organizations.

As of the end of April 2025, the number of derivative models based on the Tongyi open-source model has exceeded 100,000, with a cumulative global download exceeding 300 million times, fully demonstrating the strong vitality and creativity of the open-source ecosystem.

In the foreseeable future AGI world, the form of intelligence is likely to be distributed, with various intelligent systems cross-validating and co-evolving based on different advantages, collectively promoting the overall intelligence level of society, and open-source is the fertile ground for nurturing this diversified intelligent ecosystem.

Furthermore, through open-source, a broader range of users can conveniently use and improve the model, allowing for quicker identification of potential issues and shortcomings, and collecting more diverse application scenario feedback, thereby accelerating the model's evolution towards a more general and powerful AGI. From this, Alibaba's technological ambition is evident.

On the journey of AI, what is important may not be to precisely define the ultimate form of AGI at present—because "no one can define the ultimate form now"—but rather in the process of widely applying AI technology across various industries and deeply integrating it into real-world scenarios, continuously accumulating valuable data, optimizing core algorithms, and rapidly iterating model capabilities, allowing AI to solve one real-world problem after another, continuously trial and error, learn, and evolve, ultimately giving rise to true general intelligence.

The implementation of AI across various industries is the inevitable path to pursuing AGI

As AI applications shift from model training to large-scale inference deployment, the demand for cloud computing resources is growing exponentially. Alibaba Cloud, with its leading technological strength and large-scale advantages, has become the core platform to meet this historic demand, also supporting the accelerated implementation of AI across various industries with its technological capabilities.

In a conference call with financial analysts, Alibaba CEO Eddie Wu shared two major trends in the AI field: first, in large and medium-sized enterprises, AI applications are beginning to penetrate from internal systems to user-side scenarios; second, customers actively using AI products are extending from large and medium-sized enterprises to a large number of small and medium-sized enterprises. The industry penetration rate of AI products is rapidly expanding, with many traditional industries joining alongside the faster-adopting sectors such as the internet, smart vehicles, finance, and online education Industries such as aquaculture and traditional manufacturing are also actively exploring AI applications.

The universality of AGI determines that AI models can only truly evolve into powerful generalization capabilities and practical value when they are continuously refined through practice and feedback from data in real, complex industrial environments, facing specific and urgent business pain points.

In the automotive industry, Alibaba's strategic cooperation with global leading car manufacturers such as BMW, as well as the active integration of Tongyi Qianwen in the intelligent cockpit systems by domestic new energy vehicle companies like XPeng, Nio, and ZEEKR, all signify Alibaba's deep involvement and value contribution in the wave of automotive intelligence.

In the telecommunications industry, Alibaba's strategic partnership with telecom operators such as China Mobile and China Unicom aims to jointly build a new ecosystem for the AI industry, actively promoting the integration, innovation, and application expansion of AI with cutting-edge technologies like 5G and computing networks.

Alibaba's earnings call also revealed that recently, the Industrial and Commercial Bank of China officially chose Alibaba Cloud's PolarDB database as its bank-wide transactional distributed database. This not only recognizes Alibaba Cloud's technological capabilities by top enterprises but also reflects Alibaba's active promotion of AI products in industrial implementation.

Moreover, the most talked-about progress in cooperation with Apple shows that Alibaba's AI is flourishing across various industries. This aligns perfectly with Alibaba's fundamental logic in developing AI. On May 13, Morgan Stanley expressed optimism about Alibaba, pointing out that Alibaba is China's best AI "enabler," and as a unique GPU service provider, Alibaba AI accelerates industrial implementation, which is highly anticipated by the market.

If the expedition towards AGI is the starry sky that Alibaba looks up to, then deeply integrating the powerful capabilities of AI into the real scenarios of various industries to build a sustainable business value closed loop is its down-to-earth long march