Artificial intelligence has emerged as the 21st century’s most potent strategic currency, redefining the contours of economic competitiveness, national security, and diplomatic influence. Nations no longer measure their technological strength solely by industrial output or military hardware; the decisive edge now lies in the capacity to harness data, develop learning systems, and integrate intelligent technologies into every sphere of governance and commerce. This transformation is altering the very architecture of global power, for AI is not merely a tool, it is a force multiplier that accelerates all other capabilities and everyone wants to win the race or rather lead the race.
As in past eras of great power rivalry, the struggle for technological supremacy is shaping alliances, trade regimes, and even cultural narratives. Yet unlike the Cold War of the mid-twentieth century, this contest is fought not with nuclear arsenals and proxy conflicts, but through algorithms, cloud infrastructure, and control over the emerging rules of digital engagement. The stakes are no less consequential: whoever sets the standards today will, in effect, define the parameters of economic opportunity, information sovereignty, and even permissible thought for decades to come.
In this evolving theatre, two major actors stand at the forefront. The United States and China represent the two dominant poles, each seeking to embed its governance model, ethical codes, and societal vision into the architecture of AI. This discourse aims to understand the intricacies within AI governance policies presented by two economic giants and the domino effect it undertakes in the international arena, policy making, technological industries and political alignment.
To begin with, where others lean toward top-down regulation or values-based diplomacy, Washington is wagering on its ability to dominate AI regulation and technological advancement. Its deregulation gambit is rooted in the belief that by minimizing bureaucratic constraints, it can unleash the creative capacity of its private sector, allowing market forces to dictate the pace and direction of AI advancement. This approach, bold as it is, carries profound implications not only for the balance of power between the superpowers but also for the very nature of the AI order that will emerge.
It is here—at the intersection of strategic intent and economic philosophy—that a contemporary cold war begins.
United States and Market Driven Innovation
In this era defined by accelerating competition for artificial intelligence supremacy, the United States has made a deliberate and assertive policy shift: trading regulatory caution for market velocity. At the heart of this transformation lies America’s AI Action Plan, unveiled on 23 July 2025, an ambitious, 28-page strategy underpinned by three pillars: accelerating innovation, building AI infrastructure, and leading in international AI diplomacy and security (White House, 2025a).
This plan follows the sweeping reversal of Executive Order 14110—the 2023 Biden-era directive aimed at ensuring “safe and trustworthy AI development” which the Trump administration rescinded upon taking office. In its place, Executive Order 14179, “Removing Barriers to American Leadership in Artificial Intelligence,” was signed in January 2025, launching a review of regulations perceived to obstruct innovation and mandating the creation of a national AI roadmap within 180 days (White House, 2025b).
The Action Plan operationalizes this shift through a trio of executive orders that fast-tracking of federal permits for AI infrastructure, promoting the export of U.S. AI technologies, and restricting federal procurement of AI systems deemed ideologically biased (Politico, 2025). Federal agencies are directed to repeal or modify procurement rules and compliance requirements that could slow deployment, with the Office of Science and Technology Policy and the Office of Management and Budget leading the process (Reuters, 2025). Furthermore, to counter regulatory fragmentation, the administration has warned that federal funding could be withheld from states enacting stringent AI laws (Barron’s, 2025).
On the international stage, the United States is positioning itself to embed its vision in the global AI ecosystem by exporting “full-stack AI solutions”—spanning hardware, software, models, and standards—to allied nations, thereby extending not only technological reach but also normative influence (White House, 2025a).
The business community has embraced this deregulatory posture. The U.S. Chamber of Commerce, whose earlier policy recommendations align closely with the plan, has hailed it as a decisive step in ensuring America remains “the gold standard in Artificial Intelligence” (U.S. Chamber of Commerce, 2025). Industry leaders, including IBM’s Arvind Krishna, have praised the initiative’s focus on open innovation, market incentives, and infrastructure investment (White House, 2025c). Still, Washington’s bet is clear: by unleashing the private sector and reducing bureaucratic friction, it seeks to outpace China in both technological capacity and global influence. The deregulation gambit is, at once, a domestic economic strategy and a geopolitical maneuver, one that could define the rules of the AI era before its competitors have a chance to write them.
China’s Soft Power Strategy
On the other hand, the People’s Republic of China has adopted a more gradual yet equally calculated approach, using soft power as a primary lever to expand its AI influence, particularly across the Global South. This strategy is rooted in its belief that long-term technological leadership will depend as much on norm-setting and governance alliances as on raw innovation (China–US Focus, 2025).
China’s AI policy integrates industrial capacity with diplomatic outreach, positioning its model as an alternative to what it frames as Western techno-hegemony. Rather than promoting open innovation without constraint, Beijing advances the concept of state-guided AI development, underpinned by principles of sovereignty, political stability, and developmental equity. Its initiatives emphasize AI for development, offering infrastructure investment, technology transfer, and policy coordination to emerging economies, a proposition that resonates strongly with nations seeking digital modernization without ceding governance autonomy (Springer, 2024).
Key to this effort is China’s Global AI Governance Initiative, which calls for cooperative frameworks in standards-setting and the ethical use of AI. This platform is designed not only to shape multilateral discourse but to institutionalize China’s leadership role in drafting the rules of the AI era (China–US Focus, 2025). Through forums, training programs, and low-cost technology exports, Chinese firms such as Huawei, Baidu, and SenseTime extend Beijing’s reach into regions from Sub-Saharan Africa to Southeast Asia, embedding Chinese technical standards and governance philosophies into partner states’ digital ecosystems (Springer, 2024). From an international relations perspective, this is not simply about market penetration; it is a deliberate attempt to shift the balance of autonomic authority in global technology governance. By aligning itself with the aspirations of the Global South, China is building a coalition that challenges the Western model of AI oversight, arguing that technology should adapt to local political systems rather than be molded by universalized, Western-centric values (China–US Focus, 2025).
Rules of the Road: Competing Governance Models
Thus, while Washington aims to win the AI race through velocity, Beijing seeks to win the rules by cultivating goodwill, interoperability, and a governance framework sympathetic to its political economy. In the longer term, this soft power play may prove equally, if not more, decisive in shaping the contours of the AI order. However, China’s inclusive and non-conditional approach to the governance policy is truly contradictory to its domestic policies considering the censorship regulations the government has implemented throughout the years, maintaining strict control over the flow of content and media internally. The Chinese are using a language of inclusivity in their global posturing in terms of artificial intelligence and related technologies.
One can infer from current affairs, daily intricacies and academic discussions that artificial intelligence has quickly evolved from a mere technological advancement to a geopolitical weapon wielded by the United States and China in their fight for global dominance. Nations that once measured power by military might or economic influence are now placing their bets on who controls the data, algorithms, and AI infrastructure. As this battle escalates, it is the Global South—home to over 5 billion people—that finds itself caught between two giants. The choice is no longer about choosing sides; it’s about figuring out how to navigate the AI crossfire and avoid becoming pawns in a digital war.
AI as a Geopolitical Tool: Power, Leverage, and Influence
AI is now an ultimate tool for geopolitical leverage. Washington isn’t just betting on innovation; it is also placing strategic barriers in the form of export controls, particularly with semiconductor technology, to maintain a clear edge over China (White House, 2025a). This control over critical infrastructure is not just a matter of technology, it appears to be creating dominance over this industry and ensuring its persistence for decades to come. On the flip side, China’s model is far more centralized, focusing on state-controlled AI innovation while embedding its governance models into the digital infrastructure of developing nations. Through projects like the Belt and Road Initiative, China isn’t just offering AI solutions; it is exporting values-based governance, setting standards and defining rules for the AI-powered future (Springer, 2024). Countries that accept Chinese AI models often find themselves intertwined with Beijing’s technological ecosystem, subject to its norms of control, censorship, and surveillance. This digital hegemony isn’t just about technology; it’s a political alignment.
Hedging Strategies and Strategic Autonomy in the Global South
For the Global South, this raises a particularly difficult question, should they pick a side or to possibly hedge? Aligning with one superpower does come with its benefits, – technological transfer, critical decision-making involvement, infrastructure and economic benefits. But the downside is equally significant. Strategic autonomy is at risk as these nations become dependent on one model, which could dictate their future paths. Countries like India, Brazil, and South Africa may find themselves walking a fine line, hedging between the U.S. and China, hoping to extract benefits from both sides while maintaining political independence. However, one must understand that the dilemma faced in the Global South is not new, it’s the same old question: how to play the game without being played, to go across the finish line without having to race at all. Countries in Africa, Southeast Asia, and Latin America find themselves caught between two tech giants, trying to find ways to benefit from both without sacrificing their sovereignty. Hedging, or balancing between both U.S. and Chinese AI models, may emerge as the default strategy.
Economic and Industrial Implications: Supply Chains and Market Power
Nations that engage with the U.S.-backed tech firms benefit from the promise of open markets and private-sector-driven innovation, but they also run the risk of becoming entangled in U.S. digital wars, from sanctions to export bans. In contrast, countries embracing China’s state-guided model gain access to affordable AI technology and infrastructural support, but with the cost of surrendering digital sovereignty and aligning with authoritarian values (China–US Focus, 2025). India, for example, has positioned itself as a values-driven leader in AI, championing ethical standards while engaging with both the U.S. and China. The idea is to maintain leverage not just by consuming AI technologies but by shaping how they are governed and deployed, without falling into the trap of digital dependency (PIB, 2025).
However, this strategy of hedging brings its own risks. The more countries engage with both superpowers, the more they risk becoming caught in a tug of war for influence. The result could be the rise of AI blocs. Some countries like India may decide not to join any formal alliance but align with a cluster of countries to establish its digital model. At the heart of the U.S.-China rivalry lies a struggle not just for technology, but for who defines the rules of AI governance. The Washington approach is simple: speed over structure. The U.S. believes that deregulation is the key to unleashing innovation, allowing the private sector to lead and letting the market dictate the future of AI development. However, this approach also means that the rules are often shaped by Silicon Valley and corporate behemoths, and not necessarily aligned with broader public welfare (Politico, 2025). One could say that the US Model is realist in nature. In contrast, China’s governance strategy is more about centralized control and global influence. Through frameworks like the Global AI Governance Initiative, China seeks to embed its values such as political stability and state-driven oversight into the digital infrastructure of countries around the world (China–US Focus, 2025). It’s a model that aims to not only shape AI applications but also set global standards and norms, including how AI is regulated and monitored, making it quite constructivist in nature.
These trade and political dilemmas are determinants of future economic power and ability of each nation involved in the technological race. The U.S. maintains a leading position in high-end semiconductor production, which is critical for AI development, particularly in data centers, autonomous systems, and military applications (White House, 2025b). In recent times, the US has moved to restrict China’s access to advanced chips, the U.S. effectively limits China’s ability to develop AI technologies, maintaining a competitive advantage. However, it won’t take long for Chinese manufacturing prowess to figure out a way to develop such chips on their own, making it difficult for the US to compete unless they maintain a healthy technological transfer through a multilateral relationship with other nations in the Global South, such as India, which functions as a producer of the world. Through initiatives like the Belt and Road Initiative, China is exporting digital infrastructure, effectively locking in local economies to its AI-driven model.
Ethics, Privacy, and Ideological Footprints in AI
Lastly, one has to consider the ethical dimension to the AI discussion in global politics. Ethics in AI encompasses much more than compliance with regulations or technical safeguards; it involves privacy, trust, bias mitigation and the protection of individual rights. At its core, AI governance is about whose values are embedded into the algorithms and who gets to decide what constitutes “acceptable” behavior in a society increasingly governed by digital decision-making.
In the United States, the dominant values are the protection of democracy where the frames of democracy are formed around innovation and market efficiency embedded in its capitalistic nature. It treats privacy and social safeguards at the same level however there are questions of bias, trust and equitable access largely in the hands of the private sector (White House, 2025a.) U.S. companies, operating in a largely deregulated environment, often determine for themselves what constitutes responsible AI, with federal oversight limited to export controls, liability, and selective sectoral regulation. However, this turns a risk of an unchecked algorithmic bias, differential access to technology and uneven protection of privacy across platforms.
China, on the other hand, foregrounds social responsibility as a part of its 14-point Ai governance strategy. This includes commitments to AI safety, fairness, and alignment with state priorities (China–US Focus, 2025). However, the state-driven model prioritizes political and social stability over individual rights, meaning that privacy, freedom of expression, and dissent are subordinated to state interests. Censorship, content moderation, and surveillance are embedded into the AI ecosystem, shaping trust and behavior according to state-defined norms. In China, ethical AI is less about individual autonomy and more about ensuring societal cohesion and the legitimacy of the government’s control over digital spaces. This creates a distinctive ideological footprint, where algorithms are not neutral tools but instruments of governance.
For nations in the Global South, these ethical divergences are consequential. Choosing alignment with either superpower determines which values will dominate domestic AI governance: liberal-market ethics emphasizing choice and innovation (United States.) or state-guided social responsibility emphasizing control and collective welfare (China). Countries that prioritize privacy, free expression, and democratic oversight must navigate this landscape carefully. They risk importing biases embedded in foreign AI systems or compromising sovereignty by adopting governance frameworks that conflict with domestic values.
Alternatively, India presents an ethics-centered approach. By emphasizing inclusive growth, data protection and democratic oversight, India seeks to integrate privacy safeguards, fairness and transparency into its AI system (PIB, 2025; Digital Watch, n.d.). Unlike China, India places individual rights alongside social responsibility, and unlike the U.S., it embeds ethical principles into governance frameworks rather than leaving them entirely to the market, treading the line of the best of both worlds. Furthermore, bias, trust, and privacy are central to the discussion. Algorithms trained on incomplete or skewed data reproduce social inequalities, reinforce stereotypes, or create discriminatory outcomes. Trust in AI systems is directly linked to transparency; who built the algorithm, how data is collected, and who is accountable for decisions. Privacy, meanwhile, is a contested concept: in the U.S., it is often framed as an individual responsibility; in China, it is subordinated to state control; countries have to determine which pathway to follow, since the grass always appears to be greener on the other side.
The systems built using AI are increasingly value-laden: every model, every protocol carries implicit assumptions about acceptability. Nations aligning with different superpowers effectively import these ideological footprints, shaping civil liberties, social norms and fairness. Essentially, ethics in AI is multi-dimensional, it is about privacy, fairness, security, ideological influence, and the protection of human rights. Which aspects are prioritized depends on who governs the technology and whose interests the system serves. As AI becomes central to governance, trade, and social infrastructure, nations must ask: whose values will guide the algorithms that shape our societies? The answer to this question will determine not only the ethical integrity of AI systems but also the geopolitical and ideological landscape of the future.
The world now stands at a crossroads, staring into a bifurcated future of AI. On one side lies the U.S.-led deregulated, market-driven model, promising speed, innovation, and global reach, yet often at the expense of privacy and social safeguards. On the other lies China’s, state-guided framework, emphasizing social responsibility and stability, but subordinating individual freedoms to the priorities of the state. For nations in the Global South, this duality is not merely theoretical, it carries immediate implications for sovereignty, economic growth, and the very values embedded into their societies. The stakes are clear: alignment determines access, standards, and influence, but the question of autonomy remains unresolved. Can countries navigate between these competing hegemonies without becoming pawns? Can they safeguard privacy, uphold ethical standards, and still participate in the AI-driven global economy? The choices are as consequential as they are complex.
As policymakers, technologists, and citizens grapple with these questions, one overarching query emerges: what kind of AI future do we truly want? Do we accept a world defined by superpower rivalry, where the rules are dictated externally, or is there room for a third path, an approach that prioritizes ethics, inclusivity, and strategic autonomy without succumbing entirely to one hegemon’s vision? This is not merely an academic debate. The answers will shape the next decade of innovation, governance, and global influence. And as the AI Cold War heats up, the question lingers: is there a way to build a future where AI serves everyone, not just the fastest or the strongest? Perhaps the next chapter will tell us whether the Global South can step out of the crossfire and chart its own course in this high-stakes digital race. Is there a third path?
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