WIC report calls for collaborative governance to address global intelligence divide

Artificial intelligence (AI) was once described as the great equalizer — a technological leap that could broaden access to knowledge, accelerate development, and unlock unprecedented opportunities for humanity. Yet a new report from the Laboratory of Intelligent Society and Governance at Zhejiang Lab suggests a far more complex reality is emerging. 

The report, Evolution Trends, Multidimensional Impacts and Cooperative Governance Paths of the Global Intelligence Divide, warns that the world is rapidly entering a new age of inequality, one not defined solely by wealth, geography, or industrial capacity, but by access to intelligence itself. 

Today, a small number of countries and technology corporations dominate the infrastructure powering the global AI revolution. The concentration of advanced computing resources, proprietary foundation models, and elite AI talent is reshaping the international AI ecosystem at a remarkable speed. Nations unable to participate meaningfully in this transformation risk becoming consumers rather than creators of the next technological era. 

This is becoming a question of economic sovereignty, developmental justice, environmental equity, and global governance. Throughout modern history, transformative technologies have often widened gaps before narrowing them. The industrial revolution concentrated manufacturing power. The internet age rewarded digitally connected economies. AI, however, may deepen disparities at an even faster and more systemic scale.

The report identifies three major forces accelerating the intelligence divide: 

The first is computing power. Advanced AI systems now require enormous quantities of computational resources, energy infrastructure, and capital investment. Training frontier models increasingly depends on vast data centers, specialized chips, and uninterrupted energy supply chains. The financial threshold for participation has risen so dramatically that only a handful of states and corporations can realistically compete at the highest level. 

The second is the dominance of closed-source ecosystems. As proprietary AI models become central to innovation, access to critical technologies is increasingly controlled through commercial licensing structures, restricted APIs, and tightly guarded datasets. This limits knowledge diffusion and reinforces technological dependency for countries outside the leading innovation hubs. 

The third is the concentration of talent. The world’s top AI researchers, engineers, and institutions remain heavily clustered in a small number of advanced economies. This concentration creates a compounding effect that capital attracts talent, talent attracts innovation, and innovation attracts further capital. 

Together, these dynamics risk creating a self-reinforcing cycle where technological leadership becomes increasingly difficult to challenge. 

The report argues that this is not simply a competition gap, rather, it is becoming an intelligence hierarchy. 

For decades, international development discussions have focused on bridging the digital divide — expanding internet access, connectivity, and digital literacy. However, AI introduces a more sophisticated layer of inequality. 

Having internet access no longer guarantees meaningful participation in the global digital economy. The defining question now is whether nations possess the infrastructure, expertise, governance capacity, and innovation ecosystems necessary to shape intelligent systems themselves. 

Countries lacking these capabilities may find themselves dependent on external AI systems for everything from healthcare diagnostics and educational platforms to industrial optimization and public administration. Such dependency carries strategic consequences. 

When core AI technologies are concentrated in a few global centers, the ability of developing countries to influence standards, values, regulatory frameworks, and governance principles becomes significantly constrained. Nations risk becoming passive rule-takers in a world increasingly governed by algorithmic systems designed elsewhere. 

This concern is particularly urgent for many Global South countries. 

Historically, late-developing economies could gradually narrow technological gaps through industrialization and technology transfer. AI’s rapid scaling dynamics, however, may compress that window of opportunity. Without coordinated international action, some countries may face a transition from developmental lag to structural dependency. 

One of the report’s most striking contributions is its focus on the environmental dimension of the intelligence divide. 

The race for increasingly powerful AI models is driving extraordinary growth in energy consumption and computing infrastructure. Massive data centers require enormous electricity supplies and cooling systems, while semiconductor production depends on highly resource-intensive industrial processes. Yet the ecological burden of this transformation is not distributed equally. 

Developing countries often bear disproportionate environmental costs within global supply chains while receiving only limited benefits from high-value AI industries. The report warns that the pursuit of AI supremacy could deepen existing inequalities in energy access, carbon allocation, and sustainable development.

In this sense, the intelligence divide is not merely digital. It is ecological. If left unaddressed, the next wave of technological progress could intensify tensions between climate goals and economic development aspirations. 

The report calls for a transition away from zero-sum competition toward collaborative international governance. Rather than viewing AI solely through the lens of geopolitical rivalry, it proposes a framework grounded in shared development, open innovation, and multilateral coordination. 

At the center of this vision, the report proposes a five-pillar governance pathway. 

• First, the report advocates building inclusive and open innovation infrastructure to reduce barriers to technological participation. 

• Second, it emphasizes the creation of international public goods that support sustainable development and global knowledge sharing. 

• Third, it highlights the importance of open-source ecosystems capable of lowering research and development thresholds for developers worldwide. 

• Fourth, it calls for strengthening local AI capacity through education, training, and institutional development, enabling countries to move from dependence toward self-sustaining innovation. 

• Finally, the report stresses the need for stronger multilateral governance mechanisms — particularly within frameworks such as the United Nations — to ensure that developing countries have a meaningful voice in shaping global AI norms and standards. 

This vision reflects a growing recognition that technological leaders cannot determine AI governance. 

The emergence of AI represents one of the most consequential transitions in modern history. Like electricity, the printing press, or the internet, AI is becoming foundational infrastructure for economic, political, and social systems.

But foundational technologies do not automatically produce inclusive outcomes; they reflect the structures, incentives, and governance systems built around them. The central question facing the international community is therefore not whether AI will transform the world. It already is. 

The real question is whether humanity can prevent that transformation from hardening into a permanent architecture of inequality. 

If intelligence becomes concentrated in the hands of a few actors, the future digital landscape may grow increasingly fragmented, unequal, and unstable.

However, if nations succeed in building inclusive mechanisms for participation and governance, AI could still become a force for shared prosperity and collective advancement. 

Read the report: https://wicinternet.org/2026-04/08/c_1173997.htm