AI rivalry shifts from smart models to smart factories

For years, the global discussion about artificial intelligence revolved around large language models, algorithms and computing power. The competition appeared straightforward: Whoever built the most powerful neural network would dominate the digital economy. That perception fueled a fierce technological race among leading US companies such as OpenAI, Google, Microsoft, Amazon and Anthropic. In China, companies such as Deep-Seek, Alibaba, Tencent, Huawei and Baidu responded by accelerating investment in large models, chips and cloud infrastructure.

But over the past year, a deeper transformation has become evident. AI is steadily moving beyond chatbots, search engines and office tools into manufacturing, logistics, pharmaceuticals, automotive engineering, robotics and industrial planning. Consequently, the focus of the global AI race has changed. The next phase of the competition may depend less on algorithms and more on productive capacity, industrial organization and the ability to embed AI into large-scale economic activity.

This shift has changed the very nature of AI rivalry. The first phase of the AI race primarily featured frontier models and computing supremacy. Companies competed for elite engineers, semiconductors, cloud infrastructure and venture capital. The goal was technological leadership.

But industrial deployment is a far more complex challenge. It requires coordination among software developers, manufacturers, supply chain operators, universities, industrial engineers, energy systems and governments. In other words, the future of AI increasingly depends on ecosystems rather than isolated technological breakthroughs.

This is precisely why strategic alliances are proliferating across the AI sector.

In the United States, collaboration between technology firms and industrial corporations has gathered momentum. Microsoft has expanded its partnership with the multinational automaker Stellantis to develop AI applications in engineering, cybersecurity and manufacturing systems. Google Cloud has deepened cooperation with the German pharmaceutical company Merck to deploy AI tools across the entire drug-discovery pipeline, while also broadening its collaboration with Mars to integrate AI agents into operational and industrial processes.

Meanwhile, Nvidia has evolved from just a chip supplier to the infrastructure backbone of global AI deployment, working simultaneously with cloud providers, manufacturers, robotics developers and national technology ecosystems. US companies are increasingly realizing that industrial integration — and not just model quality — will define long-term leadership.

At the same time, universities have become central actors in the emerging AI-industrial landscape. OpenAI's NextGenAI consortium brings together leading universities and research institutes in the US and Britain, offering grants, computing power and API access to researchers and students. Anthropic has established similar partnerships with academic institutions and educational organizations focused on computer science and AI engineering.

These collaborations are not just philanthropic initiatives. They help cultivate future talent, accelerate applied research, create industry standards, and familiarize future engineers with specific AI ecosystems. In effect, universities have become part of national AI supply chains.

China is pursuing a particularly distinctive path because it enjoys a structural advantage that many Western countries can't easily replicate: a comprehensive industrial ecosystem capable of integrating AI directly into manufacturing and production.

Chinese companies are not focusing solely on consumer-facing AI applications. Instead, they are integrating AI into factories, robotics, logistics systems, semiconductors, telecommunications infrastructure, electric vehicles and industrial automation.

Huawei is a clear example. The company has expanded cooperation with manufacturers, local governments, telecommunications providers and leading universities to accelerate AI deployment across industrial sectors. Partnerships with institutions such as Tsinghua University and Peking University have contributed to advances in chip design, distributed computing, industrial AI systems and optimization technologies.

Rather than treating AI as an isolated digital product, China regards it as infrastructure embedded across the economy.

DeepSeek illustrates another important trend. Its technical team includes specialists connected to China's leading universities, particularly in mathematics, engineering and computer science. This close integration has reportedly enabled the company to optimize training efficiency, reduce costs and maintain competitive performance, demonstrating how academic expertise can directly enhance industrial competitiveness.

Meanwhile, Alibaba Cloud and Tencent are accelerating AI deployment across retail, logistics, finance and smart-city ecosystems.

Chinese electric vehicle manufacturers are integrating AI into production lines, battery systems, autonomous driving and supply chain management.
In sectors ranging from robotics to advanced manufacturing, collaboration between AI developers and industrial enterprises is becoming increasingly institutionalized.

This evolution matters because the economics of AI are changing.
The early AI race rewarded companies capable of building the largest general-purpose models. But these large models are very expensive to train and maintain. Businesses are discovering that smaller, specialized AI systems integrated into industrial workflows generate greater economic value than universal chatbots.

As a result, the strategic advantage may shift toward countries that can deploy AI across large-scale manufacturing ecosystems rather than simply produce the most advanced algorithms.

This would favor economies with deep industrial capacity, integrated supply chains, strong engineering traditions and close coordination between universities, industry and state institutions. AI has become inseparable from energy infrastructure, semiconductor production, robotics, industrial automation and logistics networks.

In many ways, the emerging AI competition has begun to resemble the historical competition among industrial powers. The next phase of global AI rivalry may not be decided primarily in Silicon Valley or by benchmark rankings. Instead, it may unfold inside factories, ports, laboratories, industrial parks and supply chains. In that sense, AI is no longer just a software revolution. It has become a new industrial revolution.

The author is a former prime minister of the Kyrgyz Republic.

The views do not necessarily reflect those of China Daily.

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