AI Power Isn’t Just US vs China
Hamza Naseer
Islamabad: Artificial intelligence is widely described as the next major arena of great power competition. Much of the global discourse focuses on the United States and China, often portrayed as locked in a technological and strategic race to dominate advanced AI systems, secure semiconductor supply chains, and control the infrastructure that will define the twenty-first century.
This framing is not without merit.
The most influential AI companies and research ecosystems are heavily concentrated in these two countries, and both governments increasingly view AI as a strategic asset.
However, this emphasis on technological rivalry overlooks a more critical and evolving reality: while great powers lead in innovation, middle powers are increasingly shaping the governance of artificial intelligence. The real influence of AI does not lie solely in its creation, but in how it is regulated, deployed, and controlled. In this sense, governance—rules, norms, and institutional frameworks, may ultimately matter as much as technological capability.
It is important to distinguish innovation from governance. A country may lead in computing power and investment yet still exert limited influence over global regulatory standards.
In contrast, several middle powers have begun to play a disproportionate role in shaping the global governance landscape of AI through consensus-building, policy design, and the translation of ethical principles into actionable regulation.
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The European Union stands out as the most prominent example. While global attention often remains fixed on Washington and Beijing, the EU has positioned itself as a regulatory leader through its landmark AI Act, the first comprehensive legal framework on artificial intelligence. Coming into force from 2024, with phased implementation through 2026 and beyond, the Act is already influencing how companies design and deploy AI systems worldwide.
Regardless of where firms are based, access to the European market increasingly requires compliance with EU standards. In effect, Brussels is exporting governance through regulation rather than through technological dominance.
This “Brussels effect” reflects influence grounded in regulatory credibility, emphasizing transparency, risk management, and accountability as global benchmarks.
Canada offers another important example. Long recognized for its contributions to foundational AI research, Canada has increasingly focused on governance and responsible AI use.
Through its federal AI strategy and ethical frameworks, Ottawa has sought to promote safe, transparent, and publicly trusted AI systems. Although it cannot match the technological scale of the United States or China, Canada has positioned itself as a credible voice in responsible AI governance, emphasizing safety, accountability, and inclusivity.
Similarly, Singapore has emerged as a global policy innovator despite not being a technological superpower. Rather than competing in scale, it has focused on developing practical governance tools that can be adopted across sectors.
Its Model AI Governance Framework is widely recognized for bridging the gap between abstract ethical principles and real-world implementation, offering actionable guidance for organizations deploying AI systems. In doing so, Singapore has established itself as a key contributor to global AI governance architecture.
Together, these cases reflect a broader pattern of middle power diplomacy. Historically, middle powers have exercised influence through coalition-building, institutional design, and norm entrepreneurship.
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AI governance is no exception. While great powers are often locked in strategic competition, middle powers are more flexible in acting as conveners, mediators, and bridge-builders between competing regulatory visions.
This role is becoming increasingly important as global approaches to AI regulation diverge. The United States generally favors a market-driven model, China emphasizes strong state supervision and strategic control, while the European Union prioritizes rights-based regulation.
At the same time, many developing countries risk being excluded from these debates despite their vulnerability to the social, economic, and security implications of AI deployment.
In this fragmented environment, middle powers can help prevent excessive polarization by facilitating dialogue, encouraging multilateral cooperation, and promoting inclusive governance frameworks.
While technological leadership remains concentrated in a few powerful states, governance legitimacy depends increasingly on broader participation and consensus.
It is true that power still matters. The United States and China remain unrivaled in their control over core infrastructure, investment networks, and advanced research ecosystems. Their technological scale far exceeds that of any middle power.
Yet international governance has never been determined by material power alone. States without overwhelming military or economic strength have historically shaped global norms through diplomacy, institutional leadership, and coalition-building.
AI governance is likely to follow a similar trajectory. While cutting-edge systems may continue to originate in a small number of countries, the rules governing their use will be shaped by a wider set of actors, including regulatory innovators, diplomatic intermediaries, and institutional entrepreneurs.
The dominant narrative of a bipolar AI world centered on Washington and Beijing therefore captures only part of the picture. The future of artificial intelligence will not be defined solely by who builds the most powerful systems, but also by who defines the principles for their responsible use.
In that broader struggle over norms and standards, middle powers are already exerting an influence that is greater than is often acknowledged.
The author is an MPhil Scholar at Defence and Strategic Studies, Quaid-i-Azam University, Islamabad.
The log is the writer’s opinion, it may or may not adhere to the organization’s editorial policy.
