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UNCTAD warns that strategic investment is becoming more concentrated

Investment in strategic sectors, including AI infrastructure, semiconductors, critical minerals and energy transition technologies, has surged over the past five years. According to UN Trade and Development’s (UNCTAD) World Investment Report 2026, these sectors accounted for 44% of global greenfield investment in 2025, up from 16% in 2020.

The report also highlights a growing concentration of investment among advanced economies. The three largest investor economies accounted for 72% of strategic sector project values in 2025, while the three biggest recipient economies attracted 56%. Low-income and lower-middle-income countries received just 10% of global greenfield investment in strategic sectors between 2020 and 2025, compared with more than 20% in other industries.

At the same time, manufacturing investment outside strategic sectors is declining. The value of announced greenfield manufacturing investment beyond these industries fell by 17% between 2021 and 2025 compared with the 2015–2019 period. The decline was particularly pronounced in developing and least-developed countries, where manufacturing has traditionally played a key role in building productive capacity and creating jobs.

The report also highlights widening differences in technological capabilities. The United States leads outward investment in AI and advanced technologies, while the EU has become the largest destination for those investments. China remains a major investor in critical minerals and downstream supply chains. Between 2016 and 2024, developed economies provided an estimated US$174 billion in industrial subsidies, compared with just US$19 billion in developing economies.

Why does it matter?

The report points to a structural shift in global investment that could deepen the divide between advanced and developing economies. Countries lacking the capital, infrastructure and skills needed to compete in strategic sectors risk missing out on the industries expected to drive future growth and productivity.

Rather than competing directly with the large subsidy programmes of major economies, UNCTAD argues that developing countries should identify targeted opportunities within strategic value chains, such as critical minerals processing, data infrastructure or regional manufacturing networks. Without stronger international cooperation and investment partnerships, the report warns that technological and economic disparities are likely to widen, with implications for global development and geopolitical stability.

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China calls for greater self-reliance in science and technology

Chinese President Xi Jinping has called for faster progress towards high-level scientific and technological self-reliance, arguing that innovation should become the primary driver of China’s modernisation.

Speaking at the national science and technology conference in Beijing, Xi described the 2026–2030 period as critical to achieving China’s goal of becoming a global science and technology leader by 2035.

Xi highlighted China’s recent advances in AI, quantum technology, advanced manufacturing, robotics, pharmaceuticals and space exploration. At the same time, he acknowledged persistent challenges, including gaps in original innovation, inefficient research investment and shortages of high-quality scientific talent.

He called for stronger coordination of national research priorities, greater support for technology transfer, improved intellectual property protection and a financial system better aligned with scientific and technological innovation.

Xi also emphasised the importance of frontier technologies, calling for greater investment in AI, quantum technologies, life sciences, integrated circuits, and strategic areas including deep-sea, deep-space and deep-earth exploration.

He argued that scientific research should become more application-oriented while industry should play a greater role in scientific discovery, strengthening links between research institutions and commercial innovation.

Alongside investment, Xi stressed that technological development must remain secure, ethical and people-centred. He called for stronger governance of AI and other emerging technologies, clearer ethical standards, improved security risk monitoring and greater support for young scientific talent.

China also honoured 258 scientific projects and researchers during the conference, underscoring the country’s continued emphasis on innovation as a strategic national priority.

Why does it matter?

The speech reinforces China’s long term strategy of reducing dependence on foreign technologies while accelerating domestic innovation in critical fields such as AI, semiconductors and quantum computing. It also illustrates how Beijing increasingly views scientific leadership as a foundation of economic competitiveness, national security and geopolitical influence.

By linking research policy, industrial development and AI governance, China is pursuing a coordinated model in which technological innovation is treated as a strategic state priority. That approach is likely to shape global competition in emerging technologies as countries race to build sovereign capabilities in frontier sectors.

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China and Denmark expand cooperation on AI and innovation

Chinese Foreign Minister Wang Yi has expressed China’s readiness to strengthen cooperation with Denmark in areas including the green economy, innovation and AI during a visit to Copenhagen. Wang made the remarks in a meeting with Danish King Frederik X, alongside separate talks with Danish Foreign Minister Lars Lokke Rasmussen.

During a meeting with King Frederik X, Wang highlighted the longstanding relationship between China and the Danish royal family, noting previous state visits and describing them as a symbol of mutual respect and friendship.

King Frederik X said bilateral relations continue to develop positively, highlighting active trade and people-to-people exchanges. He added that the Danish royal family is ready to support closer cooperation, including in AI and other areas of mutual interest.

Wang also stressed the importance of people-to-people exchanges as the foundation of bilateral friendship during his visit to Copenhagen.

Why does it matter?

The discussions illustrate how AI is becoming a regular feature of bilateral diplomacy alongside trade, innovation and green technologies. Governments are increasingly treating cooperation on emerging technologies as part of broader economic and strategic partnerships rather than as a standalone technology issue.

The talks also reflect China’s continued effort to strengthen relations with individual EU member states despite broader tensions between Beijing and the European Union over trade, technology and economic security. Cooperation in areas such as AI and innovation offers a channel for engagement even as wider geopolitical differences persist.

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CSIS says Chinese AI models are narrowing the gap with US systems

Chinese AI models are narrowing the gap with leading US systems, according to a new analysis by the Center for Strategic and International Studies.

CSIS said recent releases from Z.ai, Moonshot, DeepSeek and Alibaba-backed Qwen show that China’s rapid progress in AI was not limited to DeepSeek-R1, but reflects a broader pattern of fast technical catch-up.

The analysis points to Z.ai’s GLM-5.2 model, which performs close to the top US closed models in coding and agent-based tasks. It also highlights strong results from Moonshot’s Kimi, DeepSeek V4-Pro and Qwen3.7-Max across software engineering, reasoning and agent benchmarks.

CSIS argues that Chinese models are now only months, rather than years, behind US frontier systems in several practical areas.

The report identifies knowledge distillation, open-weight research communities and efficiency-driven engineering as key factors behind this progress. Chinese labs can learn quickly from stronger models, shared research practices and open-source ecosystems, while US chip export controls have pushed them towards more efficient training and inference strategies.

Cost is another important factor. CSIS said Chinese models are often cheaper to access than leading US closed systems because open-source releases can be hosted by many providers, increasing price competition and making them easier for developers and governments to adopt.

The analysis says US firms still retain major advantages in frontier capabilities, cloud platforms, enterprise products and user feedback loops. However, Chinese models are now capable, affordable and open enough to shape global AI competition.

CSIS argues that US policy should therefore focus not only on protecting technological advantage, but also on building global trust, lowering access costs and ensuring partners see the American AI stack as reliable.

Why does it matter?

The analysis shows that AI competition is not only about which country has the most powerful frontier model. Chinese open-weight models are spreading because they are increasingly capable, cheaper to run and easier to deploy through third-party hosts or local infrastructure. That could shape global adoption, especially for governments, startups and developers that cannot afford or do not want to depend entirely on US closed-model providers. For the US, the challenge is no longer only maintaining a technical lead, but also making its AI ecosystem trusted, affordable and reliable for international partners.

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China adopts national standards for AI agents

China’s State Administration for Market Regulation has released seven national standards for AI agent interconnection, establishing a common framework for how autonomous AI systems identify themselves, communicate and operate across platforms and industries.

The standards define AI agents as intelligent systems capable of autonomous perception, memory, decision-making, interaction and execution. The administration described them as a key application of next-generation AI and an important mechanism for deploying AI capabilities across industries.

By standardising architecture and interaction rules, the framework aims to help companies reuse common components, reduce customised development and shorten the time needed to bring AI-powered products to market.

The standards also introduce unified identity authentication and end-to-end traceability mechanisms, addressing what the regulator described as a significant gap in existing governance of AI agent systems.

Why does it matter?

AI agents will increasingly need to interact with other systems, services and organisations rather than operate in isolation. Common technical standards can improve interoperability, reduce development costs and make it easier for businesses to deploy AI applications across different sectors and platforms.

The standards also illustrate China’s strategy of shaping emerging AI technologies through nationally coordinated technical frameworks. By establishing common rules for identity, interaction and traceability at an early stage of the technology’s development, China is positioning itself to influence how agentic AI ecosystems evolve domestically and potentially internationally.

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China links AI data centre to direct green electricity supply

China has launched what state media described as the country’s first AI data centre powered entirely through a direct green electricity connection, linking AI infrastructure more closely with renewable energy supply.

The facility has started operations in Zhongwei, in the Ningxia Hui Autonomous Region, a western region that has become central to China’s computing and clean-energy strategy.

Operated by China Telecom Ningxia Branch, the data centre is built to a wind-powered liquid-cooling standard. According to the company, the facility achieves a Power Usage Effectiveness rating of 1.15, supporting high-performance AI computing while reducing energy use compared with conventional data centres.

The project is part of China’s wider effort to connect computing capacity with renewable energy resources. Ningxia has already hosted large-scale projects that directly supply green electricity to data centre clusters, including a 500 MW solar facility in Zhongwei linked to China’s computing-electricity coordination model.

Zhongwei is also a key node in China’s ‘Eastern Data, Western Computing’ initiative, which aims to shift data-intensive workloads from eastern economic centres to western regions with more land and renewable-energy resources.

The new facility is expected to support AI computing, data processing and industrial digital transformation. It could also increase demand for servers, AI chips, liquid-cooling equipment and other parts of China’s domestic technology supply chain.

The project highlights how energy availability and efficiency are becoming central to AI infrastructure policy, as countries and companies face rising power demand from data centres and advanced AI systems.

Why does it matter?

AI infrastructure is becoming an energy-policy issue. China’s green-powered data centre model shows how governments may try to match growing AI compute demand with renewable-energy deployment, regional data-centre planning and industrial supply-chain development. For China, the project also supports a broader strategy of moving compute workloads westward, reducing pressure on eastern cities and using renewable resources in regions such as Ningxia. The challenge will be proving that such facilities can deliver reliable AI computing at scale while genuinely reducing emissions across the full power and data-centre system.

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China’s latest supercomputer strengthens AI ambitions

China has regained the world’s leading position in supercomputing after the LineShine system became the fastest computer in the latest TOP500 ranking, replacing the US’s El Capitan at the top of the list.

The achievement marks China’s return to first place for the first time since 2017 and highlights the growing strategic importance of high-performance computing in the AI era.

Unlike many recent AI-focused supercomputers that rely heavily on graphics processing units (GPUs), LineShine achieves exascale performance using conventional central processing units (CPUs).

Beyond topping benchmark rankings, the system is expected to support scientific research, advanced simulations, climate modelling, pharmaceutical development and the training of increasingly sophisticated AI models.

The announcement also reflects the broader ambition of China to strengthen technological leadership while presenting its innovation ecosystem as a contributor to global technological development.

Europe also remains a major player in high-performance computing. Four European systems rank among the world’s ten fastest supercomputers, while the EU continues to invest in AI factories, next-generation supercomputing infrastructure and collaborative research centres.

The growing investment in supercomputers reflects how computing infrastructure is increasingly being treated as a strategic asset alongside semiconductors, cloud infrastructure and advanced data centres.

As governments increasingly link AI capabilities with economic competitiveness, scientific leadership and national security, access to world-class computing resources is becoming one of the defining factors shaping the global technology balance.

Why does it matter?

The latest TOP500 ranking underline that computing capacity is becoming a defining factor in AI development and scientific competitiveness. As frontier AI models require ever-greater computational resources for training and inference, access to world-class supercomputers is emerging as a strategic advantage alongside semiconductor manufacturing and cloud infrastructure.

China’s return to the top of the rankings also highlights the geopolitical dimension of high-performance computing. At the same time, continued European investment in AI factories and supercomputing infrastructure reflects a broader effort to strengthen technological sovereignty and reduce dependence on external computing resources as countries compete for leadership in AI and advanced research.

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China pushes AI and biomedicine as strategic growth sectors

Chinese Vice Premier Liu Guozhong has called for stronger development of the biomedicine sector and brain-computer interface (BCI) technologies, describing them as strategic industries that will support the Healthy China initiative and China’s future industrial development.

During a visit to Jiangsu Province, Liu called for greater use of AI, big data, and other digital technologies in pharmaceutical research and development to boost innovation and accelerate high-quality growth in the biomedicine sector.

Liu also described brain-computer interfaces as a frontier technology and a strategic area of international competition. Liu called for stronger interdisciplinary collaboration, expanded brain science research, faster breakthroughs in core technologies, and greater original innovation capacity.

The remarks reinforce China’s broader strategy of promoting AI-enabled innovation and emerging technologies to strengthen industrial competitiveness and modernise its healthcare sector.

Why does it matter?

China’s emphasis on AI-powered biomedicine and brain-computer interfaces reflects its strategy of combining healthcare innovation with industrial policy. By encouraging the use of AI in drug discovery while investing in frontier technologies such as BCIs, Beijing is seeking to strengthen domestic innovation and compete in sectors expected to play an important role in future economic growth.

The remarks also underscore the growing geopolitical significance of advanced health technologies. As countries invest in AI, biotechnology and neurotechnology, these fields are increasingly viewed not only as drivers of scientific progress but also as strategic capabilities linked to economic competitiveness, technological sovereignty and national resilience.

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China pledges continued role in global AI governance

Chinese Premier Li Qiang has said China will continue to participate in global governance on AI responsibly and constructively.

Li made the remarks during the opening plenary of the 17th Annual Meeting of the New Champions, also known as Summer Davos, in Dalian.

According to the Chinese government’s account of the speech, Li said China would work with other parties to strengthen institutional frameworks and rules, improve regulatory effectiveness and address potential AI risks.

He said AI has significantly improved innovation efficiency, but warned that risks linked to technological loss of control and ethical failures are becoming more pronounced.

Li said governance needs to keep pace with AI development, warning that the consequences could be severe if regulatory systems fail to keep to with the pace of technological change.

The remarks underline China’s continued effort to position itself as a participant in international AI governance debates, while also linking AI regulation to broader questions of innovation, economic development and global cooperation.

Why does it matter?

Li’s remarks show that AI governance remains part of China’s wider diplomatic and economic positioning. As frontier AI advances, governments are treating safety, ethics and regulatory coordination as strategic issues alongside competition over models, compute and industrial capacity. The speech does not introduce a new Chinese AI policy, but it reinforces Beijing’s message that global AI governance should involve international coordination rather than being shaped only by a few countries or companies.

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China reports a surge in AI adoption and large language model use

Chinese Premier Li Qiang said China’s AI sector has experienced ‘explosive growth’, citing significant performance improvements across multiple Chinese large language models.

Speaking at the opening plenary of the 17th Annual Meeting of the New Champions in Dalian, Li said daily token consumption across Chinese large language models had exceeded 100 trillion by the end of May, placing China among the world’s leading AI markets by usage.

Li also pointed to advances in embodied AI, saying the technology is beginning to move towards large-scale commercial deployment. The remarks came at the forum commonly known as Summer Davos, an annual gathering held in China focused on global economic and technological trends.

Li did not announce new policy measures or provide additional supporting data. His remarks nevertheless reinforce China’s broader narrative of rapid progress in AI model development and commercial deployment.

Why does it matter?

China’s remarks underscore the growing importance of AI as a strategic driver of economic competitiveness and technological leadership. Claims of daily token consumption exceeding 100 trillion suggest that large language models are being deployed at a significant scale, although the figures were presented by the Chinese government and were not independently verified.

The announcement also reflects intensifying global competition in AI. By highlighting advances in foundation models and embodied AI at a high-profile international forum, China is signalling its ambition to compete with other leading AI economies while showcasing progress in both AI research and commercial applications.

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