In the information age, we are witnessing major transformations that profoundly shape international relations. Among the most significant of these is generative artificial intelligence (generative AI), which is emerging as a central force of change in today’s world. The global race to dominate this technology is intensifying, as countries seek to leverage their unique capacities to influence its future trajectory and secure their place in the new world it is helping to shape. The United States and China, the two principal actors in this arena, are both cooperating and competing, creating complex geopolitical and economic dynamics.
Despite the immense potential of generative AI to streamline processes and boost productivity, serious concerns are emerging about its impact on the global balance of power. This article provides a general overview of the relationship between generative AI and international relations and the global economy while also briefly examining the associated challenges and implications.
The Challenge of Bias in Large Language Models (LLMs)
One of the major challenges in using large language models is the presence of biases embedded in their training data. These data sets often contain racial, cultural, geographical, and social biases, which, once processed by the models, can lead to inaccurate outputs and flawed analyses. In sensitive areas such as international relations, these biases can distort reality and promote misleading perspectives. For instance, some models may favor particular cultural or political viewpoints due to the nature of their training sources.
The Impact of LLMs on International Relations
International relations, as a complex and dynamic field, is increasingly influenced by large language models. These models are used to analyze global policies and international events. However, the risk of transmitting political and cultural biases through these models could result in skewed interpretations of global issues. A study conducted on five major LLMs—ChatGPT, Llama, Mistral, Qwen, and Doubao—found that each displayed specific inclinations in addressing global matters, largely shaped by the data they were trained on.
Geopolitical and Economic Implications of AI
The race for AI supremacy carries significant geopolitical dimensions. Countries with economic strength, advanced technologies, and skilled talent—especially during the so-called “interim years of AI”—will play a critical role in shaping the future of this technology and the emerging global order. Nations such as the United States, China, the United Kingdom, South Korea, the Netherlands, the UAE, Japan, and India possess distinct advantages that position them as leading players in this competition. In the future, this race could lead to the formation of innovation blocs and strategic alliances among states.
The Rise of Generative AI and Global Competition
With the emergence of generative AI, we are witnessing dramatic changes in how information is processed and produced. This new technology is capable of generating content in various formats—text, images, audio, and video—while enhancing performance across multiple sectors, including commerce, defense, and healthcare. Along this trajectory, global competition—especially between the U.S. and China—faces new challenges. The United States currently leads in developing LLMs and other AI technologies, while China struggles with certain barriers in training these models. Such disparities are likely to influence the geopolitical and economic power of nations.
Generative AI and Global Economic Growth
Generative AI holds great potential to stimulate global economic growth. A study by Goldman Sachs suggests that the widespread adoption of this technology could boost annual productivity growth by up to 1.5%, adding nearly $7 trillion to global GDP. However, the realization of this potential depends on four key factors: energy, computing infrastructure, data, and AI models. Countries at the forefront of this technological revolution stand to reap significant economic benefits.
Key Challenges of Generative AI
1) Regulation and International Tensions
Connor Grennan, a chief AI architect, warns that the rapid evolution of AI could transform global power structures. He stresses that without effective regulation—especially if AI surpasses human intelligence—the world could face grave consequences. Grennan highlights divergent national approaches: Europe emphasizes safety and strict regulation, the U.S. adopts a more experimental and loosely regulated stance, and China pursues a centralized regulatory strategy through state-private sector collaboration. He predicts that strict U.S. policies could hinder its competitiveness against China. Grennan also cautions that political leaders lack a comprehensive understanding of AI’s implications and that governments are overly reliant on tech companies. Ultimately, he argues that failure to establish timely and effective regulatory frameworks could lead to geopolitical conflict and destabilize global power dynamics during the AI “red zone” phase.
2) Measuring the Impact of Generative AI
Assessing the effects of GenAI is inherently complex for several reasons. First, the structural complexity of human and social processes makes it difficult to isolate AI’s role from other influencing variables. Second, the mechanisms of social and institutional impact are not yet fully understood, making it hard to identify emerging shifts.
3) Lack of Field Research and Evidence Disparities
A review of academic literature from 2019 to 2024 reveals that over one-third of scholarly articles warn of GenAI’s threats to democracy. However, only nine studies have attempted to empirically assess its real-world impacts, and most of these were conducted in limited laboratory settings. The lack of robust field data poses a serious gap in policy-relevant analysis.
Conclusion
Generative AI is not only a technological innovation but also a geopolitical phenomenon with wide-ranging global implications. Without effective governance and the institutionalization of regulatory frameworks, it could fundamentally reshape the global power structure. While the economic potential of this technology is evident, its political and security implications remain unclear, and a lack of empirical data hinders realistic policymaking. The competition between major powers like the U.S. and China over AI supremacy has extended beyond economics to the core of international politics, potentially leading to new global alignments. Thus, the future of generative AI will depend less on its technological capabilities and more on how governments understand its implications and design regulatory institutions to manage it.
