The Geography of Artificial Intelligence: The Spatial Configuration of Technological Power

Abstract

This paper investigates the geographical distribution of Artificial Intelligence (AI) and its implications for global technological inequality. AI has transcended the boundaries of a mere technological innovation and emerged as a pivotal driver of global economic and political power. Its development is influenced by geographically differentiated factors, including infrastructural resources, state policies, levels of investment, and the availability of human capital. Drawing on international indices and data (such as the AI Readiness Index and the Global AI Index), this paper examines the spatial logic of AI deployment and highlights the regional disparities that define divergent opportunities and challenges for countries at different levels of economic development. Today, AI no longer solely resides within the domain of science and technology but has become a key element in global competition, with its development and implementation heavily dependent on geographical factors such as infrastructure, the availability of financial and human resources, governmental policies, and the cooperation between the private sector and academic institutions. The growing significance of AI is evident in energy consumption projections: by 2030, data centres are expected to account for up to 8% of the United States' total energy consumption. The global dissemination of AI remains uneven, contributing to geographical inequality. Countries like China and the United Arab Emirates adopt unique national strategies to accelerate AI deployment, whereas many African nations continue to face considerable infrastructural and resource-based challenges. According to the 2025 AI Index by Stanford University, despite the global increase in optimism, regional disparities persist. Populations in China (83%), Indonesia (80%), and Thailand (77%) exhibit the highest levels of optimism toward AI. In comparison, traditionally sceptical countries such as Germany (+10%), France (+10%), and Canada (+8%) have seen notable increases in positive perceptions since 2022. The United Kingdom (+8%) and the United States have witnessed a rise of 4%. Overall, the majority of populations demonstrate a favourable outlook toward AI. The study employs a comparative methodology based on various international indices (AI Readiness Index, Global AI Index, AI Talent Index), alongside global economic and technological reports (e.g., WEF, McKinsey), and indicators that analyse the geographical distribution of AI patents, investment flows, and the concentration of skilled human capital, among other factors. Through the analysis of geographical structures, three categories of countries are identified: AI leaders (e.g., the United States, China), regional powers (e.g., India, Israel, South Korea), and peripheral nations that remain largely excluded from the global AI development process. This classification emphasises how geopolitical forces shape the formation of technological innovation centres and highlights the challenges of achieving technological equality in a structurally unequal global landscape. The field of AI geography is becoming increasingly important. AI geography refers to the geographical aspects of the development and application of AI systems, as well as their social, economic, and political impacts within and across countries, the integration of countries or regions, the concentration of infrastructure and resources, and the dynamics of research and investment. Notably, Oxford University has initiated a research project examining the political geography of AI infrastructure, with a particular focus on the global distribution of "hyperscale" cloud systems and the role of states in their development. The paper concludes that a comprehensive understanding of AI’s geographical characteristics is a necessary condition for ensuring a just, sustainable, and ethically governed technological future. The uneven nature of this process presents not only a technical challenge but also a broader global crisis relating to political imbalance, social justice, and ecological sustainability, all of which demand the activation of spatial approaches to address. Studying AI geography is a crucial step toward shaping a technological future grounded in global justice, ethical standards, and sustainable development. A nuanced understanding of spatial inequalities is essential not only for identifying economic and political advantages but also for ensuring that international collaboration is founded on fairness and inclusivity. In addition to geographical and infrastructural factors, this study emphasises the significance of cultural and linguistic barriers on AI development. The multilingual adaptation of technological systems, the integration of cultural norms, and responsiveness to local needs shape how AI technologies are received at the regional level. These factors are closely intertwined with local labour market structures, educational systems, and the distribution of digital competencies, collectively contributing to the formation of a geographical map that defines the social dimensions of AI.