Daniel Grocs, Director of the Institute for European Policymaking at Bocconi University, Milan, Italy. The deep-seated dilemma facing European AI development lies in the fact that, despite considerable academic research contributions, Europe’s industrial base remains weak, lacking major technology companies to support the translation of research into applications.

As the global governance of artificial intelligence continues to evolve, the issue of imbalanced AI development is becoming increasingly prominent. China and the United Nations play crucial roles in building sovereign AI capabilities. Currently, three major trends are shaping global AI governance.

Over the past year, significant progress has been made in global artificial intelligence governance. With the United Nations at the core, the role of multilateral mechanisms such as the G20 and BRICS has continued to strengthen, while the voice of Global South countries in UN discussions on AI governance has been increasingly amplified.

Over the past year, AI governance has entered a critical turning point, urgently requiring expanded global collaboration to achieve inclusive development. Currently, AI governance faces four major challenges: widening the intelligence gap, data security and sovereignty, insufficient AI explainability, and ethical risks.

The focus of discussions on AI governance is shifting from abstract issues such as ethics and security to technological competitiveness and application implementation. Regions like Central Asia are also actively embracing AI. However, the global governance system still faces two major difficulties: first, some government officials find it difficult to keep up with technological iterations in a timely manner; second, existing initiatives lack implementation and supervision mechanisms.

Artificial intelligence has not yet achieved ecological security and equality. While holding great promise, it is also accompanied by significant potential risks. AI governance is therefore particularly necessary, with science, security, and accessibility serving as its three cornerstones.

AI governance currently faces three challenges: geopolitical divisions, gaps in independent development capabilities between countries, and the monopoly of large private companies. The short-term outlook is not optimistic and the fragmented trend may continue. Given that the governance system for AI is still in the formation stage, it is necessary to strengthen the perspective of developing countries to avoid the expansion of the technological gap and the 'center-periphery' structure.

Over the past year, while global AI governance has made positive progress, the divergence in risk concerns between Western countries and Global South countries has hindered cooperation. To build a balanced, inclusive, and forward-looking governance system, attention should be paid to four aspects.