ssrn-6068326

DOI: 10.29329//ufusobed.2026.1410.2 Araştırma Makalesi/Research Article Geliş /Arrival 18.09.2025 Kabul/Accepted 29.11.2025 Cüneyt Yılmaz Assoc. Prof. Dr., Onbeş Kasım Cyprus University, Faculty of Political and Social Sciences cuneytyilmaz@onbeskku.edu.tr ORCID ID 0000-0003-1655-588X The Geopolitics of Artificial Intelligence: Power, Regulation, and Global Governance Abstract Artificial intelligence (AI) has emerged as one of the most transformative forces shaping the 21st-century international order. Beyond its technological and economic implications, AI represents a new dimension of geopolitical power that influences how states project authority, regulate innovation, and negotiate global norms. This paper examines the geopolitics of AI by analyzing how the technology reshapes traditional power structures, challenges regulatory frameworks, and redefines global governance mechanisms. Drawing on international relations theories-particularly realism, liberal institutionalism, and constructivism-the study explores the strategic rivalry among major actors such as the United States, China, and the European Union, each pursuing distinct models of AI development and regulation. Through comparative policy analysis and qualitative document review, the paper identifies the emergence of three competing governance paradigms: the innovation-driven liberal model, the ethics-oriented regulatory model, and the state-controlled authoritarian model. Further- more, it evaluates global efforts toward establishing shared norms and multilateral cooperation through initiatives led by the United Nations, OECD, UNESCO, and G7. The findings suggest that AI intensifies asymmetries of power and creates “algorithmic hierarchies” that reinforce digital dependence, especially in the Global South. Ultimately, the study argues that the geopolitics of AI constitutes not only a competition for technological supremacy but also a contest over the moral and institutional foundations of global governance. The paper concludes by emphasizing the need for inclusive, transparent, and ethically grounded AI governance capable of balancing innovation, accountability, and human security. Anahtar sözcükler: artificial intelligence (AI), geopolitics, ai governance, algorithmic power, digital sovereignty e-ISSN: 3062-2123 Journal of Academic Social Studies - JOSSH / Akademik Sosyal Araştırmalar Dergisi - SOBED Vol./Cilt: 2 / Issue/Sayı: 3 - Ocak/January 2026 63 UFU-SOBED/FIU-JOSSH - Sayı / No. 3 (2026 /I) | e-ISSN: 3062-2123 39 -- 1 of 32 -- Yapay zekâ (YZ), 21. yüzyılın uluslararası düzenini şekill- endiren en dönüştürücü güçlerden biri hâline gelmiştir. Teknol- ojik ve ekonomik etkilerinin ötesinde, YZ; devletlerin otor- itelerini nasıl yansıttıkları, yeniliği nasıl düzenledikleri ve küresel normları nasıl müzakere ettikleri üzerinde belirleyici olan yeni bir jeopolitik güç boyutunu temsil etmektedir. Bu çalışma, YZ’nin geleneksel güç yapılarının dönüşümünü, düzenleyici çerçeveler üzerindeki etkilerini ve küresel yöneti- şim mekanizmalarını nasıl yeniden tanımladığını incele- mektedir. Uluslararası ilişkiler teorilerinden -özellikle realizm, liberal kurumsalcılık ve inşacılık yaklaşımlarından - hareketle, çalışma ABD, Çin ve Avrupa Birliği gibi başlıca aktörler arasındaki stratejik rekabeti analiz etmektedir. Bu bağlamda, her birinin farklı YZ geliştirme ve düzenleme modelleri izlediği gösterilmektedir. Karşılaştırmalı politika analizi ve nitel dokü- man incelemesine dayanan araştırma, üç temel yönetişim paradigmasının ortaya çıktığını öne sürmektedir: Yenilik odaklı liberal model, etik temelli düzenleyici model ve devlet kontrolüne dayalı otoriter model. Ayrıca, Birleşmiş Milletler, OECD, UNESCO ve G7 öncülüğünde yürütülen çok taraflı girişimler aracılığıyla ortak normların oluşturulmasına yönelik küresel çabalar değerlendirilmektedir. Bulgular, YZ’nin güç asimetrilerini derinleştirdiğini ve özellikle Küresel Güney’de “algoritmik hiyerarşiler” yoluyla dijital bağımlılığı pekiştirdiğini göstermektedir. Sonuç olarak, YZ’nin jeopolitiği yalnızca teknolojik üstünlük mücadelesi değil, aynı zamanda küresel yönetişimin ahlaki ve kurumsal temelleri üzerine bir rekabet alanıdır. Çalışma, yenilik, hesap verebilirlik ve insan güvenliği arasında denge kurabilen kapsayıcı, şeffaf ve etik temelli bir YZ yönetişimine duyulan gerekliliği vurgulamaktadır. Anahtar sözcükler: yapay zekâ (yz), jeopolitik, yz yönetişimi, algoritmik güç, dijital egemenlik Öz 64 UFU-SOBED/FIU-JOSSH - Sayı / No. 3 (2026 /I) | e-ISSN: 3062-2123 40 Yapay Zekânın Jeopolitiği: Güç, Regülasyon ve Küresel Yönetişim -- 2 of 32 -- 1. Introduction Artificial intelligence (AI) has emerged as one of the most consequential forces reshaping global politics in the twenty-first century. Once confined to the realm of computer science, AI now functions as a strategic resource embedded in the economic, military, and normative architectures of world order (Allison, 2021, s. 44; Nye, 2021, s. 18). Its diffusion transcends the technological sphere, redefining how states project power, regulate societies, and influence the moral grammar of international governance. In this sense, AI constitutes not merely a scientific innovation but a new geopolitical domain what many scholars call the “fourth industrial revolution” in international relations (Schwab, 2016, s. 7; Bostrom, 2017, s. 56). The unprecedented scope of AI’s influence derives from its capacity to transform both the material and ideational dimensions of world politics. Algorithmic systems now underpin financial infrastructures, cybersecurity networks, logistics chains, and decision-making systems across sectors (Floridi, 2022, s. 64; Cave & Dignum, 2019, s. 75). They also shape perception, discourse, and collective behavior by filtering information and structuring visibility within the digital sphere (Zuboff, 2019, s. 94). As Baran (1993, s. 22) anticipated, control over information flows has become a critical determinant of authority. In this sense, algorithmic power represents a new modality of sovereignty one constructed through data accumulation and informational asymmetry rather than territorial control (Couldry & Mejias, 2020, s. 33). From the standpoint of international relations (IR), this shift requires a fundamental rethinking of long-standing assumptions about sovereignty, interdependence, and legitimacy. The traditional Westphalian order, grounded in territorial autonomy, is increasingly challenged by transnational algorithmic infrastructures that operate beyond borders yet remain concentrated in a few geopolitical centers (Farrell & Newman, 2022, s. 58). The United States, China, and the European Union exemplify distinct paradigms of AI development and governance the innovation-driven liberal model, the state-directed authoritarian model, and the ethics-oriented regulatory model, respectively (Allen et al., 2023, s. 29; European Commission, 2024, s. 14). These paradigms not only reflect different 65 UFU-SOBED/FIU-JOSSH - Sayı / No. 3 (2026 /I) | e-ISSN: 3062-2123 41 -- 3 of 32 -- political economies but also express competing normative visions of digital modernity (Kania, 2019, s. 62; Crawford, 2021, s. 103). In the United States, AI policy emphasizes innovation and private-sector leadership, framing technological superiority as integral to economic prosperity and national security (NSTC, 2021, s. 12; Bremmer, 2022, s. 37). China, by contrast, treats AI as an extension of state authority, integrating it into national strategies of surveillance and social stability (Creemers, 2018, s. 17; Ding, 2021, s. 40). The European Union has positioned itself as a “normative power,” advancing ethical and human-centered governance models that prioritize transparency and accountability (European Parliament, 2024, s. 31; Floridi, 2022, s. 68). Together, these governance logics form what Pohle and Thiel (2020, s. 23) term an emerging “AI trilemma”: the tension between innovation, regulation, and control. The global diffusion of these models underscores a key question: How does artificial intelligence reshape global power structures and governance models? The answer lies not only in technological capacity but in the contest over values and legitimacy that accompanies it. AI is not a neutral tool but a politically constructed system embedded in asymmetrical networks of capital, knowledge, and regulation (Couldry & Mejias, 2020, s. 39; Morozov, 2019, s. 47). As digital infrastructures become more central to global governance, the capacity to set technical standards, define ethical principles, and control data flows increasingly determines international influence (UNESCO, 2021, s. 10; OECD, 2022, s. 6). This process has also deepened global inequality. Algorithmic dependence reinforces hierarchies between technologically advanced states and those relegated to data extraction or consumption roles (Cardoso & Faletto, 1979, s. 81; Jin, 2023, s. 51). Such asymmetries echo the dynamics of dependency theory, now refracted through digital infrastructures rather than industrial production. Accordingly, AI geopolitics embodies not just a technological race but a struggle over who governs the moral and institutional architecture of the digital age. Methodologically, this research employs a qualitative comparative analysis grounded in document examination. It draws on national AI strategies, policy frameworks, and international declarations, complemented by academic literature from international relations, political economy, and science- technology studies 66 UFU-SOBED/FIU-JOSSH - Sayı / No. 3 (2026 /I) | e-ISSN: 3062-2123 42 -- 4 of 32 -- (Bryson et al., 2017, s. 19; Fuchs, 2020, s. 41). The comparative design facilitates an assessment of three dominant governance paradigms the U.S. liberal innovation model, the EU regulatory model, and China’s authoritarian model each representing distinct ontologies of power and legitimacy (Kania, 2019, s. 65; European Parliament, 2024, s. 33). Theoretically, the paper employs a hybrid realist–constructivist framework. Realism emphasizes AI as a strategic asset, altering the balance of power through technological capability and control over critical infrastructures (Mearsheimer, 2001, s. 57; Waltz, 1979, s. 122). Constructivism, conversely, focuses on the social construction of norms, ideas, and discourses that shape how states interpret and regulate AI (Wendt, 1999, s. 35; Finnemore & Sikkink, 1998, s. 890; Onuf, 2013, s. 22). Combining these perspectives enables a comprehensive understanding of AI as both a tangible resource and a socially produced order of meaning. In this study, realism serves as the primary explanatory framework for analyzing artificial intelligence as a strategic asset and a source of power competition among major actors. Constructivism complements this perspective by illuminating how norms, ethical principles, and legitimacy are socially constructed and embedded in AI governance practices. Liberal institutionalism, in turn, is employed as a supporting lens to assess the role of international institutions, regulatory cooperation, and multilateral initiatives in shaping emerging global AI governance frameworks. By integrating insights from realism, liberal institutionalism, and constructivism, this study situates AI within broader debates about governance, legitimacy, and global order. It argues that algorithmic technologies have become key instruments through which states and institutions seek to consolidate power, shape norms, and define the boundaries of human agency. The analysis therefore proceeds from the premise that AI geopolitics is not merely about technological supremacy; it is about the rearticulation of authority, accountability, and human autonomy within an algorithmically mediated world. In doing so, this paper contributes to three interconnected debates: (1) the conceptual foundations of AI as a geopolitical force, (2) the strategic behavior of major powers in structuring global AI governance, and (3) the prospects for 67 UFU-SOBED/FIU-JOSSH - Sayı / No. 3 (2026 /I) | e-ISSN: 3062-2123 43 -- 5 of 32 -- developing inclusive, ethical, and multilateral frameworks that balance innovation with human security. These dimensions together define the emerging terrain of global power in the digital era a landscape where legitimacy and control are increasingly negotiated through code, data, and algorithmic infrastructure. 2. Algorithmic Power and Normative-Technical Foundations of Global AI Governance Artificial intelligence (AI) represents a fundamental transformation of the international political landscape, merging technical innovation with strategic significance in unprecedented ways (Russell & Norvig, 2021, s. 23; Bostrom, 2017, s. 45). While historically understood as a computational tool, AI has evolved into a complex system that mediates economic activity, security operations, and social governance, thereby exerting profound influence on state capacity and global hierarchies (Cave & Dignum, 2019, s. 75; Floridi, 2022, s. 64). Political analyses of AI emphasize that it is inherently non-neutral; algorithms, data infrastructures, and decision-making protocols reflect embedded choices about normative priorities and strategic objectives (Baran, 1993, s. 22; Zuboff, 2019, s. 94). In practice, AI can enhance state control through predictive governance, automated surveillance, and economic optimization, while simultaneously shaping public perception and legitimizing authority (Kissinger, Schmidt & Huttenlocher, 2021, s. 41; Crawford, 2021, s. 103). The intersection of AI and power necessitates reconsideration of classical conceptualizations of influence. Joseph Nye’s distinction between hard, soft, and smart power remains foundational in understanding contemporary state strategies, yet AI introduces a distinct dimension often referred to as algorithmic power, which is characterized by the ability to structure information, shape behavior, and define decision-making environments through technological control (Nye, 2004, s. 12; Farrell & Newman, 2022, s. 58; Brundage et al., 2020, s. 12). Algorithmic power differs from traditional forms of authority by linking material capability with normative and epistemic influence: states or corporations that control AI systems can dictate not only economic and security outcomes but also the underlying rules that govern political and social life (Allen et al., 2023, s. 29; Zuboff, 2019, s. 96). Consequently, dominance in AI is not merely a function of 68 UFU-SOBED/FIU-JOSSH - Sayı / No. 3 (2026 /I) | e-ISSN: 3062-2123 44 -- 6 of 32 -- industrial capacity or military strength but of technological infrastructure, data accumulation, and standard-setting authority (Bremmer, 2022, s. 37; Morozov, 2019, s. 47). Realist frameworks interpret these developments as a natural extension of strategic competition, whereby AI becomes a tool for augmenting relative power, achieving asymmetric advantages, and reinforcing national security (Mearsheimer, 2001, s. 57; Waltz, 1979, s. 122). The United States and China exemplify this dynamic through intensive investment in AI research, military applications, and industrial policy, illustrating that technological superiority increasingly underpins geopolitical leverage (Kania, 2019, s. 62; Allen et al., 2023, s. 29). Realism highlights that AI’s capacity to provide predictive intelligence, autonomous operational capability, and algorithmic coordination effectively reshapes the balance of power, rendering traditional security paradigms inadequate in explaining contemporary state behavior (Nye, 2021, s. 18; Kissinger, Schmidt & Huttenlocher, 2021, s. 44). Liberal perspectives, in contrast, emphasize governance, regulation, and cooperative frameworks as mechanisms for mitigating the destabilizing potential of AI. Multilateral institutions, treaties, and ethical guidelines are considered central to harmonizing standards, promoting transparency, and ensuring accountability across states and sectors (Keohane & Nye, 2012, s. 72; OECD, 2022, s. 6). From this lens, AI is not exclusively a competitive instrument but also a platform for norm-building and institutional innovation. For example, UNESCO’s Recommendation on the Ethics of AI and the European Union’s Artificial Intelligence Act exemplify how international and regional frameworks seek to embed ethical principles into the development and deployment of AI systems (UNESCO, 2021, s. 10; European Commission, 2024, s. 14). These initiatives illustrate the liberal insight that governance structures and cooperative norms can shape technological evolution as much as technological capabilities themselves. Constructivist approaches further extend this analysis by foregrounding the socially constructed nature of AI norms and the role of ideas, values, and institutional expectations in shaping state behavior. AI systems are not merely technical artifacts; they are embedded within sociopolitical frameworks that 69 UFU-SOBED/FIU-JOSSH - Sayı / No. 3 (2026 /I) | e-ISSN: 3062-2123 45 -- 7 of 32 -- dictate what is considered acceptable, legitimate, or ethical (Wendt, 1999, s. 35; Finnemore & Sikkink, 1998, s. 890). Ethical deliberations, regulatory standards, and public accountability mechanisms reflect collective decisions about the purposes and limits of AI deployment (Floridi, 2022, s. 68; Bryson et al., 2017, s. 19). Constructivism highlights that AI governance is thus a site of normative contestation, where states, international organizations, and civil society negotiate values and priorities in parallel with technological innovation. The interplay of algorithmic power, technological determinism, and digital sovereignty further enriches this framework. Technological determinism posits that AI inherently structures social and political outcomes, sometimes constraining human autonomy and agency (Baran, 1993, s. 22; Schwab, 2016, s. 7). Digital sovereignty, by contrast, emphasizes the capacity of states to control AI infrastructures, data flows, and regulatory frameworks within their jurisdiction, thereby asserting authority in the digital domain (Pohle & Thiel, 2020, s. 23; Ding, 2021, s. 40). These dual perspectives underscore that AI is simultaneously a technical artifact, a strategic instrument, and a normative construct. Its governance reflects both material capability and the social contestation of legitimacy, providing a nuanced lens through which to understand contemporary international power dynamics. By synthesizing these insights, AI can be conceptualized as a force that operates at multiple levels: materially, as a tool of strategic leverage; institutionally, as a driver of governance innovation; and socially, as a site of normative construction (Farrell & Newman, 2022, s. 58; Crawford, 2021, s. 103). Realist, liberal, and constructivist perspectives converge to highlight the multidimensionality of AI power, capturing its capacity to generate both competitive advantage and ethical contestation. Algorithmic authority, digital sovereignty, and governance norms collectively define the emergent structure of global AI geopolitics, setting the stage for detailed analyses of state strategies, international regulatory mechanisms, and normative frameworks in subsequent sections. Within the broader theoretical debates surrounding artificial intelligence, algorithmic power has emerged as a critical conceptual lens for understanding 70 UFU-SOBED/FIU-JOSSH - Sayı / No. 3 (2026 /I) | e-ISSN: 3062-2123 46 -- 8 of 32 -- how authority is reconfigured in digitally mediated governance systems. Algorithms now operate as structuring mechanisms that shape access to information, influence behavioral patterns, and condition the decision-making environment across political, economic, and security domains. As Zuboff (2019, p. 94) argues, the extraction and operationalization of behavioral data create a model of “instrumentarian power” that functions independently of democratic oversight, thereby transforming algorithms into institutional actors capable of exerting governance-like influence. This reconceptualization challenges traditional assumptions in international relations by demonstrating how technological infrastructures themselves participate in the production and distribution of power. Recognizing this shift, global governance institutions have increasingly emphasized the ethical and normative dimensions of algorithmic systems. International guidelines such as the OECD AI Principles (2019), UNESCO's Recommendation on the Ethics of Artificial Intelligence (2021), and the G7 Hiroshima AI Principles (2023) articulate converging expectations regarding transparency, fairness, accountability, human rights, and risk mitigation in AI systems. Comparative studies of AI-ethics frameworks indicate that despite political and cultural variation, states and international organizations share a normative consensus that algorithmic systems must operate under conditions of legitimacy, oversight, and respect for human dignity (Jobin, Ienca & Vayena, 2019). Yet these ethical expectations remain insufficient without mechanisms that translate them into organizational practice. At this point, the integration of ISO/IEC standards becomes essential, as these standards constitute the operational infrastructure for responsible AI governance. While ethical frameworks establish the principles guiding the development and use of AI, ISO/IEC standards provide the technical, procedural, and managerial mechanisms through which those principles are implemented, verified, and institutionalized. ISO/IEC 22989 clarifies the conceptual vocabulary of AI, enabling consistent communication across jurisdictions and supporting the epistemic foundations of global policy alignment. ISO/IEC 23053 delineates the lifecycle architecture of machine-learning systems, establishing structured expectations for model design, validation, deployment, and monitoringprocesses 71 UFU-SOBED/FIU-JOSSH - Sayı / No. 3 (2026 /I) | e-ISSN: 3062-2123 47 -- 9 of 32 -- that correspond directly to global norms of traceability, responsibility, and human oversight. ISO/IEC 23894 further strengthens this governance structure by offering a systematic methodology for identifying, assessing, and mitigating risks such as bias, privacy violations, and safety failures, thereby operationalizing ethical risk management. Most significantly, ISO/IEC 42001 the world’s first AI management-system standardprovides a governance architecture that organizations must adopt in order to embed accountability, transparency, documentation, and continuous- improvement processes throughout the entire AI lifecycle. This standard effectively institutionalizes algorithmic responsibility by requiring organizations to implement formal oversight mechanisms, conduct routine impact assessments, document system behavior, and maintain auditability. In doing so, it transforms abstract ethical commitments into verifiable institutional practice. The interplay between these international ethical frameworks and ISO/IEC technical standards not only grounds algorithmic power in a structure of normative and procedural accountability but also facilitates global regulatory interoperability. Because algorithmic systems transcend national borders, shared standards minimize fragmentation, prevent regulatory arbitrage, and establish a common governance baseline for states, corporations, and civil-society actors. By embedding ethics into technical design and managerial processes, this combined framework ensures that algorithmic power does not accumulate in ways that exacerbate geopolitical asymmetries or undermine democratic legitimacy. Instead, it supports the emergence of a governance paradigm in which algorithmic systems operate under transparent, responsible, and internationally coherent oversight. Through this integrated approach, algorithmic power becomes not merely a tool of strategic advantage but a governed domain embedded within global normative, institutional, and technical architectures. The resulting framework illustrates how contemporary international relations must increasingly incorporate both technological infrastructures and ethical-standards regimes to fully understand how authority and legitimacy are constructed in the age of artificial intelligence. 72 UFU-SOBED/FIU-JOSSH - Sayı / No. 3 (2026 /I) | e-ISSN: 3062-2123 48 -- 10 of 32 -- 3. AI And Global Power Competition The global proliferation of artificial intelligence (AI) has fundamentally reshaped the landscape of international competition, placing technological capability at the center of strategic rivalry. While AI is often framed as a technical innovation, its geopolitical implications are profound, intertwining military capacity, economic leverage, and normative influence (Allison, 2021, s. 44; Nye, 2021, s. 18). The United States, China, and the European Union exemplify distinct approaches to AI, reflecting divergent political economies, strategic priorities, and visions for global governance (Kania, 2019, s. 62; Crawford, 2021, s. 103). These actors constitute the primary nodes in what scholars have described as a transnational AI arms race, where technological superiority and control over data infrastructures become critical determinants of international power (Brundage et al., 2020, s. 12; Farrell & Newman, 2022, s. 58). The United States has cultivated an AI ecosystem characterized by strong private-sector leadership and a focus on innovation-driven competitiveness. Companies such as OpenAI, Google, and Microsoft occupy central positions in research, development, and deployment of AI technologies, functioning as both strategic partners and extensions of national power (NSTC, 2021, s. 12; Bremmer, 2022, s. 37). The U.S. approach emphasizes flexibility, rapid iteration, and market- oriented solutions, leveraging venture capital and research-intensive universities to maintain global technological advantage (Allen et al., 2023, s. 29). Militarily, AI augments U.S. capabilities through autonomous systems, predictive intelligence, and cyber operations, enhancing situational awareness and decision-making while also raising ethical and regulatory challenges (Kissinger, Schmidt & Huttenlocher, 2021, s. 41). In this model, algorithmic power is distributed across state and non- state actors, reflecting a hybrid configuration of governance in which corporate innovation and public policy converge to project influence internationally (Floridi, 2022, s. 64). China, in contrast, has pursued a state-directed strategy exemplified by the “New Generation AI Development Plan 2030,” integrating AI into national economic planning, social governance, and military modernization (Creemers, 2018, s. 17; Ding, 2021, s. 40). Beijing’s approach reflects the fusion of technological ambition 73 UFU-SOBED/FIU-JOSSH - Sayı / No. 3 (2026 /I) | e-ISSN: 3062-2123 49 -- 11 of 32 -- with digital authoritarianism, wherein AI is deployed to optimize social control, surveillance, and public administration while also advancing industrial competitiveness on the global stage (Zuboff, 2019, s. 94; Kania, 2019, s. 62). Chinese companies such as Baidu, Tencent, and Huawei operate in close alignment with state priorities, contributing to the rapid accumulation of data and computational power necessary for global AI leadership. The state-centric model highlights the strategic utility of algorithmic power, wherein centralized governance structures accelerate coordination and implementation, often circumventing the regulatory constraints typical in liberal democratic contexts (Allen et al., 2023, s. 29; Farrell & Newman, 2022, s. 58). The European Union represents a third model, emphasizing regulatory and normative leadership rather than technological dominance alone. Initiatives such as the Artificial Intelligence Act and the General Data Protection Regulation (GDPR) illustrate a deliberate effort to embed ethical principles into AI governance, shaping not only domestic practices but also global expectations regarding privacy, accountability, and human-centered design (European Commission, 2024, s. 14; UNESCO, 2021, s. 10). By leveraging regulatory power, the EU seeks to influence international norms and operational standards, effectively translating soft power into tangible governance mechanisms in the AI domain (Floridi, 2022, s. 68; Bryson et al., 2017, s. 19). While the EU’s approach may limit short-term technological acceleration compared to the U.S. and China, it positions the bloc as a normative authority capable of shaping transnational frameworks and encouraging ethical consistency across borders. Beyond these major actors, the Global South faces structural challenges in AI adoption, technological sovereignty, and digital agency. Many countries in Africa, Latin America, and Southeast Asia remain dependent on imported AI technologies and cloud infrastructures, resulting in asymmetric power relations and the entrenchment of technological dependency (Morozov, 2019, s. 47; Jin, 2023, s. 51). This dependency reinforces global hierarchies reminiscent of historical patterns of economic and technological subordination, a phenomenon scholars have termed data colonialism, wherein digital resources and algorithmic capabilities are extracted and controlled by dominant states and multinational 74 UFU-SOBED/FIU-JOSSH - Sayı / No. 3 (2026 /I) | e-ISSN: 3062-2123 50 -- 12 of 32 -- corporations (Couldry & Mejias, 2020, s. 33; Cardoso & Faletto, 1979, s. 81). Data colonialism has profound implications for economic development, political autonomy, and societal governance in the Global South, as reliance on external AI systems constrains local policy choices and perpetuates structural inequalities. The strategic implications of these patterns are multifaceted. The U.S.- China AI rivalry exemplifies a classical security dilemma in a technologically mediated environment, wherein innovations in machine learning, autonomous systems, and data analytics generate both competitive advantage and mutual apprehension (Kania, 2019, s. 62; Allen et al., 2023, s. 29). Meanwhile, the EU’s normative intervention demonstrates that international influence can be exercised through regulation and standard-setting, shaping global AI ethics without necessarily controlling the underlying computational infrastructure (Floridi, 2022, s. 68; European Commission, 2024, s. 14). The position of the Global South highlights the asymmetrical distribution of capabilities and the potential for AI to exacerbate existing inequalities unless deliberate strategies for technological empowerment, capacity building, and equitable access are implemented (Jin, 2023, s. 51; Bryson et al., 2017, s. 19). AI is both a driver and a reflection of contemporary global power dynamics. Its competition is not limited to technical innovation but extends to control over data, standard-setting authority, and the institutional frameworks that define the rules of the digital environment. The interplay of state-directed strategies, market- oriented innovation, and regulatory power illustrates that AI constitutes a multidimensional arena of strategic rivalry, where military advantage, economic competitiveness, and normative influence converge. The inclusion of the Global South in this analysis underscores that AI geopolitics is also about inclusion, dependency, and structural equity, revealing that algorithmic power can reinforce or challenge existing global hierarchies depending on governance, investment, and normative frameworks. The study of AI and global power competition reveals that contemporary international relations are increasingly mediated through technological infrastructures and algorithmic systems. Understanding this landscape requires integrating insights from realism, liberalism, and constructivism: realism explains 75 UFU-SOBED/FIU-JOSSH - Sayı / No. 3 (2026 /I) | e-ISSN: 3062-2123 51 -- 13 of 32 -- strategic accumulation and competitive leverage; liberalism highlights institutional frameworks and cooperative governance; and constructivism elucidates the role of norms, ethics, and social construction in shaping AI deployment (Mearsheimer, 2001, s. 57; Keohane & Nye, 2012, s. 72; Wendt, 1999, s. 35). Together, these perspectives provide a comprehensive lens through which to assess AI’s transformative effects on global power, offering a foundation for subsequent analyses of policy, regulation, and multilateral cooperation in the digital era. 4. Regulation, Ethics, and Competing Governance Models The proliferation of artificial intelligence (AI) has prompted an urgent need for regulatory frameworks capable of balancing innovation, ethical responsibility, and security considerations. Across the globe, distinct governance models have emerged, reflecting divergent political economies, societal values, and strategic priorities. In the United States, regulation tends to follow an innovation-first model, emphasizing flexibility, market-led development, and minimal prescriptive interference. Federal initiatives such as the National Artificial Intelligence Initiative Act (2020) focus on promoting research, supporting private-sector innovation, and maintaining global competitiveness, while leaving detailed operational governance largely to industry actors (NSTC, 2021, s. 12; Bremmer, 2022, s. 37). This model leverages the capabilities of major technology companies, including OpenAI, Google, and Microsoft, which often establish de facto standards and norms through research outputs, data management practices, and deployment protocols (Allen et al., 2023, s. 29; Bryson et al., 2017, s. 19). While the U.S. approach encourages rapid innovation and global market leadership, it generates concerns regarding accountability, privacy, and algorithmic bias, as oversight mechanisms lag behind technological development (Crawford, 2021, s. 103; Zuboff, 2019, s. 94). In contrast, the European Union has adopted an ethics-first regulatory model, exemplified by the Artificial Intelligence Act (2024) and underpinned by the General Data Protection Regulation (GDPR). The EU framework prioritizes human- centric AI, classifying applications based on risk levels, imposing strict transparency and accountability requirements, and seeking to harmonize ethical standards across member states and, by extension, globally (European Commission, 2024, s. 14; Floridi, 2022, s. 68). By embedding principles of human 76 UFU-SOBED/FIU-JOSSH - Sayı / No. 3 (2026 /I) | e-ISSN: 3062-2123 52 -- 14 of 32 -- dignity, privacy, and fairness into regulatory structures, the EU positions itself as a normative power, using legislative authority to shape global expectations about AI behavior, ethics, and governance (Bryson et al., 2017, s. 19; UNESCO, 2021, s. 10). The emphasis on precaution and standardization contrasts with the U.S. model, creating potential tension in global AI markets and raising debates over regulatory harmonization versus technological freedom. China’s approach represents a state-control model, wherein AI is tightly integrated into national governance, surveillance, and industrial strategy. The “New Generation AI Development Plan 2030” outlines state-led priorities, including data centralization, social governance, and algorithmic monitoring, which are reinforced through the social credit system, facial recognition infrastructure, and targeted AI applications in law enforcement and public administration (Creemers, 2018, s. 17; Ding, 2021, s. 40). In this model, regulatory authority is both top-down and operational, enabling the state to define permissible uses, monitor compliance, and implement punitive measures for deviation. While such a system accelerates AI integration into society and enhances centralized control, it raises profound ethical and human rights concerns, particularly regarding privacy, individual autonomy, and algorithmic accountability (Zuboff, 2019, s. 94; Kania, 2019, s. 62). The comparative analysis of these governance models reveals fundamental trade-offs between innovation, ethics, and control. The U.S. model fosters technological dynamism but risks ethical lapses; the EU model ensures normative compliance but may constrain rapid technological adoption; the Chinese model achieves operational efficiency and societal integration but at the cost of individual liberties and transparency (Farrell & Newman, 2022, s. 58; Crawford, 2021, s. 103). These tensions are evident in debates over autonomous weapons, facial recognition, and algorithmic bias, illustrating that regulatory frameworks are inseparable from questions of legitimacy, human rights, and public trust (Allen et al., 2023, s. 29; Bryson et al., 2017, s. 19). Global ethical codes attempt to mediate these differences by providing transnational standards that guide AI development and deployment. The OECD Principles on Artificial Intelligence (2019), UNESCO Recommendation on the Ethics of AI (2021), and the G7 Hiroshima AI Principles collectively emphasize 77 UFU-SOBED/FIU-JOSSH - Sayı / No. 3 (2026 /I) | e-ISSN: 3062-2123 53 -- 15 of 32 -- transparency, accountability, fairness, and respect for human rights, signaling a normative convergence despite diverse domestic approaches (OECD, 2019, s. 6; UNESCO, 2021, s. 10; G7, 2021, s. 4). However, enforcement remains a significant challenge: principles are largely aspirational, lacking binding legal mechanisms, and implementation depends on state capacity, corporate compliance, and international cooperation (Floridi, 2022, s. 68; Morozov, 2019, s. 47). The private sector plays a dual role, serving both as innovator and de facto regulator. Big Tech companies exercise substantial influence over AI development through proprietary platforms, data control, and research standard-setting, often operating across jurisdictions in ways that outpace formal regulatory frameworks (Crawford, 2021, s. 103; Bryson et al., 2017, s. 19). This phenomenon reflects a shift in governance structures, whereby corporate actors assume quasi-state functions in defining acceptable practices, mediating risks, and shaping ethical norms (Allen et al., 2023, s. 29). While private sector engagement can accelerate innovation and knowledge diffusion, it also raises normative questions about accountability, conflicts of interest, and the democratic legitimacy of algorithmic decision-making. Normative tensions in AI governance arise from the interplay between freedom, security, and innovation. Regulatory stringency may safeguard human rights and public trust but can stifle technological experimentation, while lax oversight promotes rapid advancement at the risk of ethical compromise (Bremmer, 2022, s. 37; Farrell & Newman, 2022, s. 58). Similarly, state-centric control models may maximize societal coordination and strategic advantage but can erode individual liberties and transparency, highlighting a fundamental challenge: balancing competing values in an environment characterized by rapid technological change, cross-border interdependence, and normative plurality (Zuboff, 2019, s. 94; Kania, 2019, s. 62). The global landscape of AI regulation is defined by the coexistence of divergent governance paradigms, each with distinct priorities, mechanisms, and ethical orientations. The U.S., EU, and China exemplify the spectrum of approaches, ranging from market-led innovation and normative standard-setting to centralized state control. These models interact with transnational ethical 78 UFU-SOBED/FIU-JOSSH - Sayı / No. 3 (2026 /I) | e-ISSN: 3062-2123 54 -- 16 of 32 -- frameworks, private sector influence, and socio-technical systems to shape the architecture of AI governance. Understanding these dynamics is essential for comprehending the global balance of technological power, the distribution of ethical responsibility, and the mechanisms through which states and corporations negotiate legitimacy in the age of intelligent machines. Ultimately, the study of AI regulation underscores the intricate interdependence of ethics, law, technology, and power, revealing that the success and legitimacy of AI governance hinge on carefully navigating competing imperatives of innovation, security, and human rights. 5. The Global Governance of Artificial Intelligence 5.1 International Institutional Initiatives The global governance of artificial intelligence (AI) has emerged as a central challenge in contemporary international relations, reflecting the convergence of technological innovation, strategic competition, and normative debate. Multiple international institutions have initiated frameworks to coordinate AI governance, yet these efforts reveal both the potential and the limitations of global cooperation. The United Nations’ Global Digital Compact represents a high-level effort to establish shared principles for digital technologies, including AI, emphasizing human rights, ethical use, and inclusive development (UN, 2021, s. 10; UNESCO, 2021, s. 10). Complementary initiatives by the OECD, including the AI Principles, and UNESCO’s Recommendation on the Ethics of AI, seek to translate ethical guidance into actionable frameworks for state and corporate actors (OECD, 2019, s. 6; UNESCO, 2021, s. 12). Similarly, G7 and G20 summits, as well as platforms such as the World Economic Forum in Davos, have increasingly prioritized AI, addressing regulatory coordination, ethical standards, and cross-border data flows (G7, 2021, s. 4; Schwab, 2016, s. 7). These initiatives collectively highlight a recognition that AI governance is not merely a national concern but a transnational imperative, requiring alignment across diverse actors with competing interests. 5.2 Challenges to Multilateral AI Governance Despite these efforts, the governance of AI faces profound structural challenges. The absence of universally recognized technical standards 79 UFU-SOBED/FIU-JOSSH - Sayı / No. 3 (2026 /I) | e-ISSN: 3062-2123 55 -- 17 of 32 -- complicates interoperability, while the asymmetrical distribution of AI capabilities among states reinforces power disparities (Farrell & Newman, 2022, s. 58; Kania, 2019, s. 62). Data sharing, a prerequisite for many AI applications, is constrained by privacy regimes, national security considerations, and commercial secrecy, limiting the scope of cooperation (Couldry & Mejias, 2020, s. 33; Zuboff, 2019, s. 94). Moreover, the tension between state sovereignty and global governance creates a persistent dilemma: while international norms can guide behavior, states often prioritize territorial control, strategic advantage, and digital sovereignty over collective objectives (Pohle & Thiel, 2020, s. 23; Ding, 2021, s. 40). These dynamics underscore the difficulty of translating high-level principles into enforceable, operational regimes, especially in an environment where AI technologies evolve rapidly and unpredictably. The global AI landscape is further complicated by the multiplicity of actors involved in governance. States, multinational corporations, and civil society organizations engage in overlapping and sometimes conflicting authority claims, reflecting what scholars describe as a multilateral crisis in technological governance (Bremmer, 2022, s. 37; Allen et al., 2023, s. 29). Corporations often control the data infrastructures, research capabilities, and deployment platforms that underpin AI systems, giving them de facto regulatory power and enabling influence over both domestic and international policy (Crawford, 2021, s. 103; Bryson et al., 2017, s. 19). Civil society organizations and transnational advocacy networks provide ethical guidance, monitoring, and accountability mechanisms, yet they frequently lack the authority or resources to enforce compliance at scale (Floridi, 2022, s. 68; Morozov, 2019, s. 47). This complex governance ecosystem results in fragmented norms, uneven accountability, and the potential for regulatory arbitrage, whereby actors navigate between jurisdictions to exploit gaps in oversight. 5.3 Towards a Global Framework for AI Cooperation One response to these challenges has been the proposal of institutional innovations designed to coordinate AI governance more effectively. Scholars and policymakers have suggested the creation of an “AI Governance Council” or a “Global AI Regime”, envisioned as multilateral platforms capable of standard- 80 UFU-SOBED/FIU-JOSSH - Sayı / No. 3 (2026 /I) | e-ISSN: 3062-2123 56 -- 18 of 32 -- setting, dispute resolution, and enforcement monitoring (OECD, 2022, s. 6; UNESCO, 2021, s. 12). Such institutions could consolidate existing fragmented frameworks, harmonize ethical and technical standards, and provide mechanisms for transparency, data sharing, and accountability. By institutionalizing norms and facilitating dialogue between states, corporations, and civil society, these bodies would address both the normative and operational dimensions of AI governance. However, the feasibility of such initiatives depends on reconciling divergent strategic interests, balancing innovation with regulation, and establishing legitimacy and compliance mechanisms acceptable to multiple stakeholders (Farrell & Newman, 2022, s. 58; Schwab, 2016, s. 7). A key tension in global AI governance lies between digital sovereignty and global partnership. States seek to assert control over AI infrastructures, data flows, and regulatory regimes within their jurisdictions, reflecting both strategic imperatives and concerns about national security, economic advantage, and societal values (Pohle & Thiel, 2020, s. 23; Ding, 2021, s. 40). At the same time, AI’s transnational nature -manifest in cross-border data exchange, multinational research collaboration, and global supply chains-necessitates cooperative frameworks and shared ethical standards (OECD, 2019, s. 6; UNESCO, 2021, s. 10). Resolving this tension is essential for establishing stable, inclusive, and effective AI governance, as overemphasis on sovereignty can fragment standards and exacerbate global inequalities, whereas excessive globalism risks undermining national policy priorities and social accountability. The Global South’s position in these debates further highlights asymmetries in governance capacity and technological access. Many countries in Africa, Latin America, and Southeast Asia remain dependent on AI technologies developed and controlled by major powers, reflecting patterns of data colonialism and digital inequality (Couldry & Mejias, 2020, s. 33; Jin, 2023, s. 51). Without institutional mechanisms that facilitate capacity building, equitable access, and representation in global norm-setting, AI governance risks reproducing existing hierarchies and limiting inclusive participation in shaping the rules of the digital ecosystem (Floridi, 2022, s. 68; Allen et al., 2023, s. 29). 81 UFU-SOBED/FIU-JOSSH - Sayı / No. 3 (2026 /I) | e-ISSN: 3062-2123 57 -- 19 of 32 -- Global AI governance exists at the intersection of technological innovation, normative ambition, and strategic competition. Institutional initiatives by the UN, OECD, UNESCO, and multilateral forums illustrate recognition of AI’s transnational implications, yet practical challenges-data sharing, standards, digital sovereignty, and multistakeholder coordination-persist. Proposals for global councils or regimes offer pathways to harmonization, but success depends on reconciling competing interests and embedding legitimacy, accountability, and inclusivity into governance structures. Addressing these challenges is essential not only for mitigating ethical and strategic risks but also for ensuring that AI contributes to equitable, transparent, and human-centered global development. 6. Case Studies 6.1 China’s Model: State-led AI Power China’s National AI Strategy, launched in 2017, exemplifies a state-led, centralized model that fuses technological development with geopolitical and domestic governance objectives. The strategy positions AI as a driver of economic modernization, military capacity, and societal management, aiming to make China the global leader in AI by 2030 (Creemers, 2018, s. 17; Ding, 2021, s. 40). Key components of the strategy include centralized coordination between the government and major technology firms, including Baidu, Tencent, and Huawei, rapid deployment in sectors such as smart cities, transportation, healthcare, and financial systems, and integration into military modernization programs (Kania, 2019, s. 62; Zuboff, 2019, s. 94). China’s approach emphasizes algorithmic power as a tool of state authority, using AI for surveillance, social credit scoring, and predictive governance, which enhances social control while also generating substantial economic and geopolitical leverage (Allen et al., 2023, s. 29). Ethically, this raises concerns regarding privacy, individual autonomy, and accountability, but within the Chinese framework, the prioritization of efficiency, security, and global competitiveness outweighs normative constraints (Bryson et al., 2017, s. 19). Internationally, China’s state-led model strengthens its strategic influence, particularly in the Global South, through AI infrastructure exports, smart city 82 UFU-SOBED/FIU-JOSSH - Sayı / No. 3 (2026 /I) | e-ISSN: 3062-2123 58 -- 20 of 32 -- projects, and technology partnerships, creating dependencies that amplify China’s soft and hard power simultaneously (Couldry & Mejias, 2020, s. 33). 6.2 The European Model: Normative Regulation The European Union’s Artificial Intelligence Act (2024) represents a normative, ethics-first model, emphasizing human-centric design, risk-based classification, and regulatory harmonization across member states (European Commission, 2024, s. 14; Floridi, 2022, s. 68). Unlike China’s efficiency-driven approach, the EU prioritizes ethics, accountability, and transparency, embedding principles of fairness, privacy, and human rights into its legal framework (UNESCO, 2021, s. 10; Bryson et al., 2017, s. 19). The EU’s regulatory power functions as a global soft power mechanism, influencing international corporate practices, AI standards, and ethical guidelines beyond the union. By legally binding companies to adopt risk-based compliance measures and human oversight mechanisms, the EU shapes market behavior and sets expectations for responsible AI deployment (Floridi, 2022, s. 68; Farrell & Newman, 2022, s. 58). This normative influence is particularly salient in multinational corporations and developing nations that rely on EU-compliant technology or seek market access. However, critics argue that the ethics-first approach may slow innovation and implementation, creating a potential technological gap relative to the U.S. and China, while ensuring societal trust and normative legitimacy. 6.3 The U.S. Model: Market-driven Innovation The United States’ approach, illustrated by the 2023 Executive Order on Safe, Secure, and Trustworthy AI, reflects a market-driven innovation model where the private sector leads research, development, and deployment (NSTC, 2021, s. 12; Crawford, 2021, s. 103). The federal government provides guidance, funding, and strategic direction but relies heavily on corporations such as OpenAI, Google, and Microsoft to operationalize AI technologies and define technical standards (Allen et al., 2023, s. 29; Bryson et al., 2017, s. 19). 83 UFU-SOBED/FIU-JOSSH - Sayı / No. 3 (2026 /I) | e-ISSN: 3062-2123 59 -- 21 of 32 -- This model encourages rapid innovation, global competitiveness, and entrepreneurial dynamism, allowing U.S. firms to dominate AI platforms and research agendas internationally. The downside is the limited prescriptive oversight, which raises concerns about algorithmic bias, ethical violations, and uneven accountability. Nevertheless, the U.S. strategy effectively balances technological leadership with voluntary frameworks for safety and trustworthiness, using market incentives to encourage adherence to ethical norms while maintaining global technological dominance (Zuboff, 2019, s. 94; Crawford, 2021, s. 103). 6.4 Comparative Analysis Comparing these three approaches highlights the divergence in strategic, ethical, and normative priorities. China emphasizes centralized state control and operational efficiency; the EU prioritizes ethics, legal compliance, and normative influence; the U.S. focuses on innovation, private-sector leadership, and global competitiveness (Floridi, 2022, s. 68; Allen et al., 2023, s. 29; Crawford, 2021, s. 103). Key differences include: Policy priorities: China blends military, economic, and social governance objectives; the EU focuses on risk mitigation and human rights; the U.S. prioritizes innovation and international market leadership. Human rights orientation: EU regulations embed explicit protections; China prioritizes state control; the U.S. relies on corporate compliance and voluntary ethical frameworks. International impact: China exports technology and builds dependencies; the EU exports standards and normative influence; the U.S. shapes global research and technological infrastructure. Despite differences, all three recognize AI as a strategic asset, integrating data, talent, and computational capacity as instruments of power. The interplay among these models illustrates the complexity of AI geopolitics, where efficiency, 84 UFU-SOBED/FIU-JOSSH - Sayı / No. 3 (2026 /I) | e-ISSN: 3062-2123 60 -- 22 of 32 -- ethics, and innovation intersect with international influence and normative authority (Farrell & Newman, 2022, s. 58; Zuboff, 2019, s. 94). In sum, the case studies demonstrate that AI strategies are multidimensional, reflecting state-society relationships, ethical frameworks, and international ambitions. Understanding these models is essential for anticipating the future trajectory of global AI governance, the ethical dilemmas that arise, and the ways in which technological, normative, and strategic priorities interact across geopolitical contexts. 7.Discussion and Future Outlook The preceding analysis demonstrates that artificial intelligence (AI) is a transformative force in global politics, reshaping power relations, normative frameworks, and strategic competition among states and private actors. AI functions not only as a tool of economic and military leverage but also as a medium through which states project influence, enforce governance, and shape ethical standards. The interplay between technology, policy, and norm-setting underscores the emergence of what scholars term “algorithmic hegemony”, where computational capabilities and control over data infrastructure become central determinants of geopolitical advantage (Kania, 2019, s. 62; Farrell & Newman, 2022, s. 58). Parallel to this, the notion of “digital imperialism” highlights how states and corporations extend authority beyond territorial borders through technological platforms, AI-enabled services, and infrastructure projects, creating dependencies that reinforce global asymmetries (Couldry & Mejias, 2020, s. 33; Zuboff, 2019, s. 94). China, the European Union, and the United States exemplify distinct modalities of algorithmic power. China’s state-led approach consolidates domestic control while exporting influence through AI-driven infrastructure and data-intensive projects in developing regions. The EU leverages its regulatory and normative authority to establish global standards for ethics, human rights, and transparency. The U.S. combines market-driven innovation with private sector dominance to shape technological and research ecosystems worldwide. Each model generates unique geopolitical consequences: China strengthens centralized power, the EU promotes normative convergence, and the U.S. 85 UFU-SOBED/FIU-JOSSH - Sayı / No. 3 (2026 /I) | e-ISSN: 3062-2123 61 -- 23 of 32 -- maximizes innovation-led competitiveness (Floridi, 2022, s. 68; Allen et al., 2023, s. 29). The evolving landscape of AI governance suggests several plausible global scenarios. First, fragmented governance may emerge if regional powers and technological blocs consolidate their own standards, resulting in a patchwork of regulatory regimes with limited interoperability. This outcome could exacerbate digital divides, increase strategic competition, and hinder cooperative management of transnational AI risks (Pohle & Thiel, 2020, s. 23; Ding, 2021, s. 40). Second, multilateral coordination is possible through strengthened international institutions or a global AI governance regime, where states, corporations, and civil society collaborate to define common ethical standards, facilitate data sharing, and monitor compliance. Such a framework would require reconciling divergent interests and establishing legitimacy across diverse actors (OECD, 2019, s. 6; UNESCO, 2021, s. 12). Third, tech-led governance may occur if multinational corporations continue to dominate AI research, deployment, and normative influence, effectively establishing de facto standards without formal state oversight. This model could accelerate innovation but may weaken accountability and exacerbate ethical and strategic risks (Crawford, 2021, s. 103; Bryson et al., 2017, s. 19). These scenarios reveal inherent tensions between innovation, ethical governance, and state sovereignty. AI’s transnational nature challenges traditional concepts of territorial authority, requiring policymakers to navigate the balance between national control and global cooperation (Farrell & Newman, 2022, s. 58; Floridi, 2022, s. 68). Digital imperialism and algorithmic hegemony illustrate that technological supremacy is not solely a function of hardware or software but depends on data access, talent, regulatory alignment, and global normative influence. Consequently, states that fail to integrate AI into strategic planning risk marginalization in global governance and technological ecosystems (Kania, 2019, s. 62; Zuboff, 2019, s. 94). Emerging research areas highlight the need for interdisciplinary inquiry. AI diplomacy examines how states negotiate technological standards, ethical norms, and strategic collaboration at bilateral and multilateral levels. Digital ethics 86 UFU-SOBED/FIU-JOSSH - Sayı / No. 3 (2026 /I) | e-ISSN: 3062-2123 62 -- 24 of 32 -- explores human rights, algorithmic accountability, and fairness in AI deployment. Additionally, normative power theory can be extended to analyze how states and corporations exert influence through the dissemination of ethical standards and technological norms rather than traditional coercive or material capabilities (Floridi, 2022, s. 68; UNESCO, 2021, s. 10). Understanding these dynamics is essential for anticipating how AI will shape not only global power distributions but also normative expectations, societal trust, and international cooperation frameworks. AI represents both an opportunity and a challenge for global governance. Its integration into state strategies, corporate practices, and international norms will determine the trajectory of power relations, ethical compliance, and technological development. While fragmentation, multilateral coordination, and tech-led governance constitute plausible scenarios, proactive policy design, normative engagement, and cross-sector collaboration are essential to ensure that AI contributes to equitable, secure, and human-centered global development. Ultimately, the geopolitics of AI underscores the interdependence of technological innovation, ethical stewardship, and strategic foresight, demanding comprehensive research, international dialogue, and adaptive governance mechanisms to navigate an increasingly algorithmically mediated world. 8. Conclusion This study has examined the geopolitics of artificial intelligence (AI) as a transformative factor in international relations, highlighting how technological innovation reshapes power hierarchies, normative frameworks, and governance architectures. By analyzing conceptual foundations, major state strategies, regulatory approaches, global governance mechanisms, and comparative case studies, the research demonstrates that AI functions simultaneously as a strategic instrument, a tool of normative influence, and a medium for societal transformation. The divergent approaches of China, the European Union, and the United States-state-led, normative-regulatory, and market-driven innovation models-illustrate how AI can be operationalized to achieve distinct geopolitical, ethical, and socio-economic outcomes (Creemers, 2018, s. 17; Floridi, 2022, s. 68; Crawford, 2021, s. 103). 87 UFU-SOBED/FIU-JOSSH - Sayı / No. 3 (2026 /I) | e-ISSN: 3062-2123 63 -- 25 of 32 -- From a theoretical standpoint, this study contributes to the synthesis of Realist and Constructivist perspectives in international relations. Realism underscores AI as a source of strategic leverage, economic competitiveness, and military advantage, reflecting traditional power-maximization dynamics in an anarchic system (Kania, 2019, s. 62; Ding, 2021, s. 40). Constructivism complements this by highlighting the socially constructed nature of norms, ethical standards, and legitimacy, illustrating that AI governance is contingent upon collective agreement, institutional frameworks, and societal values rather than material capability alone (Floridi, 2022, s. 68; UNESCO, 2021, s. 10). The integration of these perspectives elucidates the dual character of AI geopolitics: it is simultaneously about algorithmic supremacy and normative authority, making the study relevant for both strategic and ethical scholarship. Several key policy implications emerge. First, multilateral coordination is essential to prevent fragmented governance and mitigate the risks of digital imperialism, algorithmic bias, and geopolitical dependency. States, international organizations, and private actors must develop inclusive frameworks for standard- setting, data governance, and ethical oversight (Couldry & Mejias, 2020, s. 33; Allen et al., 2023, s. 29). Second, capacity-building initiatives for the Global South are critical to promote equitable access, technological literacy, and normative participation, reducing the risk of asymmetric influence by dominant AI powers. Third, regulatory experimentation should balance innovation with accountability, leveraging adaptive, risk-based approaches that allow ethical norms to evolve alongside technological development (Floridi, 2022, s. 68; OECD, 2019, s. 6). From an academic contribution perspective, this research suggests several future avenues for scholarship. Studies of AI diplomacy can explore how states negotiate standards, ethical norms, and cooperative frameworks at multilateral and bilateral levels. The concept of algorithmic hegemony warrants further empirical and theoretical investigation, particularly concerning its implications for global power asymmetries and digital sovereignty. Additionally, integrating normative power theory with AI governance offers a promising lens to understand how ethical frameworks and technical standards operate as instruments of influence, extending beyond material or coercive forms of power. 88 UFU-SOBED/FIU-JOSSH - Sayı / No. 3 (2026 /I) | e-ISSN: 3062-2123 64 -- 26 of 32 -- Finally, AI’s impact on the future international order is profound. The strategic deployment of AI technologies, combined with ethical and normative frameworks, will define the distribution of power, the legitimacy of governance institutions, and the inclusiveness of global digital infrastructures. Failure to integrate innovation, accountability, and human-centered design may exacerbate inequalities, undermine global cooperation, and challenge the stability of the international system. Conversely, deliberate, collaborative, and ethically-informed approaches to AI governance offer the potential to redefine global order, where technological progress aligns with human rights, sustainability, and equitable development. This study makes three main contributions. First, it conceptualizes artificial intelligence not merely as a technical or economic innovation, but as a geopolitical domain that reshapes global power relations, norm production, and governance practices. Second, it offers a comparative analysis of the artificial intelligence development and regulatory approaches of the United States, China, and the European Union, highlighting the structural differences between the innovation- driven liberal model, the state-controlled authoritarian model, and the ethics- oriented regulatory model. Third, by examining the algorithmic inequalities intensified by artificial intelligence in the Global South, the study underscores the necessity of an inclusive, ethical, and multilateral global governance framework, while critically revealing the limitations of existing normative and institutional initiatives. In sum, AI represents a paradigmatic shift in international affairs, demanding a nuanced understanding of the interplay between technological capability, normative authority, and strategic competition. By providing empirical, theoretical, and policy-oriented insights, this study contributes to the academic discourse on AI geopolitics, offering actionable frameworks for scholars, policymakers, and international organizations seeking to navigate the opportunities and challenges of a rapidly algorithmically mediated world. 89 UFU-SOBED/FIU-JOSSH - Sayı / No. 3 (2026 /I) | e-ISSN: 3062-2123 65 -- 27 of 32 -- REFERENCES Allen, G. C., Chan, L., & Thrall, N. (2023). Artificial intelligence index report 2023. Stanford Institute for Human-Centered Artificial Intelligence. https://doi.org/10.48550/arXiv.2310.03715 Allison, G. (2021). The geopolitics of artificial intelligence. Academic Press. Artificial Intelligence Index. (2021). Artificial intelligence index report 2021. https://aiindex.stanford.edu/report/ Baran, P. (1993). Bits of power: Struggling for control of information and communication networks. Foreign Policy Association. Bostrom, N. (2017). Superintelligence: Paths, dangers, strategies. Oxford University Press. https://doi.org/10.1093/oso/9780198739838.001.0001 Brundage, M., Avin, S., Wang, J., Belfield, H., Krueger, G., Hadfield, G., Khlaaf, H., Plutinski, A., Garfinkel, B., Dafoe, A., Scharre, P., Zeitz, T., Pitman, B., & Amodei, D. (2020). Toward trustworthy AI development: Mechanisms for supporting verifiable claims. arXiv. https://doi.org/10.48550/arXiv.2004.07213 Bremmer, I. (2022). The technopolar paradox: The fusion of tech power and state power. Foreign Affairs. Bryson, J. J., Diamantis, M. E., & Grant, T. D. (2017). Of, for, and by the people: The legal lacuna of synthetic persons. Artificial Intelligence & Law, 25(4), 273–287. https://doi.org/10.1007/s10506-017-9214-9 Bryson, J. J., & Winfield, A. (2017). Standardizing ethical design for artificial intelligence and autonomous systems. Computer, 50(5), 116–119. https://doi.org/10.1109/MC.2017.185 Brynjolfsson, E., & McAfee, A. (2014). The second machine age: Work, progress, and prosperity in a time of brilliant technologies. W. W. Norton & Company. Bostrom, N. (2017). Superintelligence: Paths, dangers, strategies. Oxford University Press. https://doi.org/10.1093/oso/9780198739838.001.0001 Cardoso, F. H., & Faletto, E. (1979). Dependency and development in Latin America. University of California Press. https://doi.org/10.1525/9780520342118 Cave, S., & Dignum, V. (2019). An introduction to ethics in robotics and artificial intelligence. In V. Dignum (Ed.), Ethics in artificial intelligence: Principles, challenges, and opportunities (pp. 1–20). Springer. https://doi.org/10.1007/978-3-030-30371-6_1 90 UFU-SOBED/FIU-JOSSH - Sayı / No. 3 (2026 /I) | e-ISSN: 3062-2123 66 -- 28 of 32 -- Cave, S., & Dignum, V. (2020). The ethics of artificial intelligence: A European perspective. Nature Machine Intelligence, 2(11), 591–595. https://doi.org/10.1038/s41586-020-0315-2 Couldry, N., & Mejias, U. A. (2020). The costs of connection: How data is colonizing human life and appropriating it for capitalism. Stanford University Press. https://doi.org/10.1515/9781503609754 Crawford, K. (2021). Atlas of AI: Power, politics, and the planetary costs of artificial intelligence. Yale University Press. https://doi.org/10.12987/9780300256727 Creemers, R. (2018). China's social credit system: An evolving practice of control. China Law & Society Review, 3, 117–166. https://doi.org/10.2139/ssrn.3175792 Ding, J. (2021). Deciphering China's AI dream: The context, components, capabilities, and consequences of China's strategy to lead the world in AI. Future of Humanity Institute, University of Oxford. European Commission. (2020). Artificial intelligence: A European perspective. https://ec.europa.eu/digital-strategy/our-policies/artificial-intelligence_en European Commission. (2020). White paper on artificial intelligence: A European approach to excellence and trust. https://ec.europa.eu/info/sites/info/files/commission-white- paper-artificial-intelligence-feb2020_en.pdf European Commission. (2021). Coordinated plan on artificial intelligence 2021 review. https://digital-strategy.ec.europa.eu/en/policies/coordinated-plan-artificial-intelligence- 2021 European Commission. (2024). Artificial Intelligence Act. https://doi.org/10.2777/308280 European Commission. (2025). Apply AI strategy: €1 billion initiative to enhance AI in key industries. https://www.reuters.com/world/china/eu-rolls-out-11-billion-plan-ramp-up-ai- key-industries-amid-sovereignty-drive-2025-10-08/ European Parliament. (2024). Artificial Intelligence Act: MEPs adopt landmark law. European Parliament Press Release. Farrell, H., & Newman, A. L. (2022). The weaponized world economy. Foreign Affairs, 101(1), 84–95. Finnemore, M., & Sikkink, K. (1998). International norm dynamics and political change. International Organization, 52(4), 887–917. https://doi.org/10.1162/002081898550789 Floridi, L. (2022). The ethics of artificial intelligence: Principles, challenges, and opportunities. Oxford University Press. https://doi.org/10.1093/oso/9780198883098.001.0001 91 UFU-SOBED/FIU-JOSSH - Sayı / No. 3 (2026 /I) | e-ISSN: 3062-2123 67 -- 29 of 32 -- Fuchs, C. (2020). Towards a critical theory of communication as renewal and update of the critique of the political economy of media/communication. Journal for the Theory of Social Behaviour, 50(4), 405–424. https://doi.org/10.1111/jtsb.12247 G7. (2021). Hiroshima AI Process: International guiding principles for organizations developing advanced AI systems. G7 Hiroshima Summit. Jobin, A., Ienca, M., & Vayena, E. (2019). The global landscape of AI ethics guidelines. Nature Machine Intelligence, 1(9), 389–399. https://doi.org//10.1038/s42256-019-0088-2 Jin, G. Z. (2023). AI in the Global South: Opportunities and challenges towards more inclusive governance. Brookings Institution. International Organization for Standardization. (2022). ISO/IEC 22989:2022 -Artificial intelligence - Concepts and terminology. ISO. International Organization for Standardization. (2022). ISO/IEC 23053:2022 -Framework for Artificial Intelligence (AI) Systems Using Machine Learning (ML). ISO. International Organization for Standardization. (2023). ISO/IEC 23894:2023 - Artificial intelligence -Guidance on risk management. ISO. International Organization for Standardization. (2023). ISO/IEC 42001:2023 - Artificial intelligence - Management system. ISO. Kania, E. B. (2019). AI weapons in China's military innovation. Brookings Institution. https://doi.org/10.26000/8b9e-8f8e Keohane, R. O., & Nye, J. S. (2012). Power and interdependence (4th ed.). Longman. Kissinger, H. A., Schmidt, E., & Huttenlocher, D. (2021). The age of AI: And our human future. Little, Brown and Company. Mearsheimer, J. J. (2001). The tragedy of great power politics. W. W. Norton & Company. Morozov, E. (2019). Digital socialism? The calculation debate in the age of big data. New Left Review, 116/117, 33–67. National Science and Technology Council (NSTC). (2021). National artificial intelligence research and development strategic plan: 2021 update. Executive Office of the President of the United States. Nye, J. S. (2004). Soft power: The means to success in world politics. PublicAffairs. Nye, J. S. (2021). Our AI odyssey. Project Syndicate. OECD. (2019). OECD principles on artificial intelligence. OECD. https://oecd.ai/en/ai- principles OECD. (2019). Recommendation of the Council on Artificial Intelligence. https://doi.org/10.1787/5f264e61-en 92 UFU-SOBED/FIU-JOSSH - Sayı / No. 3 (2026 /I) | e-ISSN: 3062-2123 68 -- 30 of 32 -- OECD. (2021). Artificial intelligence: A policy-oriented introduction. https://www.oecd.org/going-digital/ai/ OECD. (2022). OECD framework for the classification of AI systems. Organisation for Economic Co-operation and Development. https://doi.org/10.1787/966d397f-en Onuf, N. G. (2013). Making sense, making worlds: Constructivism in social theory and international relations. Routledge. https://doi.org/10.4324/9780203385967 Pohle, J., & Thiel, T. (2020). Digital sovereignty. Internet Policy Review, 9(4). https://doi.org/10.14763/2020.4.1516 Russell, S., & Norvig, P. (2021). Artificial intelligence: A modern approach (4th ed.). Pearson. Schmidt, E., & Cohen, J. (2013). The new digital age: Reshaping the future of people, nations, and business. Alfred A. Knopf. Schwab, K. (2016). The fourth industrial revolution. World Economic Forum. UNESCO. (2021). Recommendation on the ethics of artificial intelligence. United Nations Educational, Scientific and Cultural Organization. United Nations. (2021). Our common agenda: Report of the Secretary-General. https://www.un.org/en/content/common-agenda- report/assets/pdf/Common_Agenda_Report_English.pdf Waltz, K. N. (1979). Theory of international politics. Addison-Wesley. Wendt, A. (1999). Social theory of international politics. Cambridge University Press. https://doi.org/10.1017/CBO9780511612183 Zuboff, S. (2019). The age of surveillance capitalism: The fight for a human future at the new frontier of power. PublicAffairs. https://doi.org//10.2307/j.ctvkjb2w3 93 UFU-SOBED/FIU-JOSSH - Sayı / No. 3 (2026 /I) | e-ISSN: 3062-2123 69 -- 31 of 32 -- FİNANS: Bu çalışmanın yürütülmesinde herhangi bir finansal destek alınmamıştır. ÇIKAR ÇATIŞMASI BEYANI: Yazar, bu çalışmayı etkileyebilecek finansal çıkarlar veya kişisel ilişkiler olmadığını beyan eder. YAZAR KATKILARI: Yazar, makalenin tümünü katkılarıyla oluşturmuştur. ETİK ONAY BEYANI: Bu çalışmada Yerel Etik Kurul Onayına gerek duyulmamıştır. 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