Geopolitics & Global Power: Long-term (2033-2046)

Current State

The long-term horizon for AI geopolitics extends into profoundly uncertain territory. By 2033, the foundational dynamics established in the 2024-2032 period -- US-China bifurcation, European regulatory leadership without market dominance, and Global South fragmentation -- will have had a decade to compound. The long-term question is no longer whether AI reshapes the global order, but what kind of order emerges: a new bipolarity organized around competing AI ecosystems, a fragmented multipolar landscape, or -- in the most optimistic scenario -- a managed convergence toward shared governance of increasingly powerful AI systems.

This section projects from the medium-term trajectories described in the 2028-2033 analysis, extending to 2046 -- a full generation into the AI era. Projections at this range are necessarily more speculative, but the structural forces driving them are already visible.

Key Drivers

1. The approach of artificial general intelligence (AGI) or transformative AI. The most consequential long-term geopolitical variable is the trajectory of AI capabilities themselves. If AI systems achieve or approach general intelligence -- the ability to perform any intellectual task that a human can -- the geopolitical implications are unprecedented. The nation or bloc that first develops AGI (or the closest approximation) would possess a strategic advantage potentially greater than nuclear weapons. Even short of AGI, AI systems that can autonomously conduct scientific research, design new technologies, and optimize complex systems will dramatically accelerate the innovation cycles of the nations that control them, creating compounding strategic advantages.

2. AI-driven economic restructuring reaches maturity. By the mid-2030s, AI will have fundamentally restructured major economies. PwC estimated that AI could contribute up to $15.7 trillion to the global economy by 2030; by 2040, the figure could be substantially higher. The distribution of this value, however, will determine geopolitical power. Nations that have successfully integrated AI into their economies will see sustained productivity growth; those that have not will experience relative and potentially absolute decline. The economic foundations of national power -- GDP, tax revenue, military spending capacity, technological investment -- will increasingly correlate with AI adoption and capability.

3. Climate change and AI as intertwined geopolitical forces. By the 2030s and 2040s, the intersection of climate change and AI will be a defining geopolitical dynamic. AI will be essential for climate adaptation (predictive modeling, resource optimization, disaster response) and potentially for mitigation (materials science, energy grid optimization, carbon capture). But AI's own energy demands will be enormous. The geopolitics of energy -- who has clean energy surpluses, who faces energy poverty, who controls the rare minerals needed for both AI hardware and renewable energy infrastructure -- will merge with AI geopolitics into a single complex system.

4. Demographic shifts interact with AI capabilities. Aging populations in China, Japan, South Korea, and Europe will create economic pressure that AI may partially alleviate through productivity enhancement and automation of care work. Meanwhile, the young, growing populations of sub-Saharan Africa and South Asia represent both an enormous potential workforce and a massive risk of unemployability if AI eliminates the traditional development pathways (manufacturing, services outsourcing) that previous generations used to enter the global middle class. By 2040, Africa's working-age population is projected to exceed 1 billion -- the question of whether AI opens or closes economic pathways for this generation is among the most consequential on Earth.

5. The governance of superintelligent or near-superintelligent systems. As AI capabilities increase, the governance challenge transitions from regulating applications to governing systems whose capabilities may exceed human understanding and control. This is not science fiction -- it is the explicit concern of leading AI researchers and the rationale behind the AI safety movement. The geopolitical dimension is stark: if advanced AI systems pose existential or catastrophic risk, unilateral national development without international oversight could endanger all of humanity. But the competitive dynamics between the US and China create powerful incentives to prioritize speed over safety.

Projections

2033-2036: The consolidation of AI blocs. The world will have organized into roughly three AI spheres, each with its own standards, platforms, data governance regimes, and security architectures:

The US-led sphere encompasses North America, the UK, Australia, Japan, South Korea, and much of Western Europe (for commercial AI). Built around American cloud platforms (AWS, Azure, GCP), NVIDIA/AMD/Intel hardware, and US-origin foundation models. Governed by a mix of market self-regulation, sector-specific rules, and evolving federal legislation.
The China-led sphere encompasses mainland China, much of Southeast Asia, Central Asia, significant parts of Africa, and portions of the Middle East and Latin America. Built around Huawei/Chinese domestic hardware, Chinese cloud platforms, and Chinese foundation models. Governed by state-directed regulation emphasizing social stability and Party control.
The European regulatory sphere overlaps commercially with the US sphere but maintains distinct governance standards through the EU AI Act and its successors. It influences regulation globally but lacks autonomous commercial AI platforms of comparable scale.

A fourth grouping -- non-aligned AI nations including India, Brazil, Indonesia, Saudi Arabia, Turkey, and others -- will attempt to operate across blocs, adopting technology from both while pursuing domestic capabilities. India's trajectory is particularly critical: by the mid-2030s, India could be the world's third-largest AI economy, with the scale and talent to sustain a partially independent AI ecosystem.

2035-2040: The military AI transformation. AI will have transformed military affairs as fundamentally as the introduction of aviation or nuclear weapons. Specific developments:

Autonomous weapons systems will be operational across air, land, sea, and cyber domains. Drone swarms capable of autonomous target identification and engagement will be standard in advanced militaries. The ethical and legal frameworks for their use will remain contested and incomplete.
AI-enabled nuclear command and control will introduce new instabilities. SIPRI and other arms control organizations have warned that AI in nuclear early-warning systems could reduce decision timelines from minutes to seconds, increasing the risk of inadvertent escalation. The introduction of AI into nuclear posture decisions -- even in advisory roles -- changes the calculus of deterrence in ways that are not yet fully understood.
Cyber warfare becomes AI-native. Offensive and defensive cyber operations will be conducted primarily by AI systems operating at machine speed. Human operators will set objectives and constraints but will be unable to intervene in real-time execution. This creates risks of AI-on-AI escalation cycles that could damage critical infrastructure before human decision-makers can respond.
Space-based AI systems for surveillance, communications, and potentially weapons guidance will be contested assets, adding a new domain to great-power military competition.

2036-2042: The AGI governance crisis. If progress toward AGI or highly general AI systems continues (and the trajectory as of 2026 suggests it will, though timelines are deeply uncertain), the world will face a governance challenge without historical precedent. Key scenarios:

Unilateral AGI development: One nation achieves a decisive AGI capability first, creating a strategic advantage so large that it fundamentally disrupts the balance of power. This is the scenario most feared by strategists on all sides, as it creates extreme temptation for preemptive action by rivals who fear permanent strategic subordination.
Parallel AGI development: Multiple nations achieve AGI capabilities within a relatively short window, creating a "mutual AGI deterrence" dynamic analogous to mutual assured destruction. This scenario is more stable but still extremely dangerous, as the parties must negotiate governance arrangements for systems whose capabilities are difficult to verify or limit.
Managed AGI development: An international framework -- perhaps modeled on the IAEA for nuclear energy -- is established to oversee and constrain AGI development, with inspection, verification, and enforcement mechanisms. This is the most desirable scenario but also the hardest to achieve, given the competitive dynamics and the difficulty of verifying AI capabilities compared to nuclear materials.

2040-2046: The new world order. By the mid-2040s, AI will have been a transformative force for roughly two decades. The geopolitical landscape will reflect the cumulative choices made in the 2024-2040 period:

Best case: International cooperation on AI governance has produced functional institutions, military AI is constrained by binding agreements, the worst excesses of digital colonialism have been moderated by Global South agency and international norm-setting, and AI-driven productivity gains have been broadly (if imperfectly) shared across nations.
Moderate case: The world operates in a "Cold War 2.0" stable competition between US-led and China-led AI blocs, with managed tensions, limited cooperation on shared risks (AI safety, climate), and a Global South that is divided but not entirely excluded. Major AI crises have occurred but have been managed without catastrophic escalation.
Worst case: Uncontrolled AI competition has produced a major AI-related conflict or catastrophe, digital colonialism has entrenched a new form of global inequality more rigid than its predecessors, autonomous weapons have been used in combat with devastating consequences, and the absence of governance has allowed AI systems to cause systemic harm (financial collapse, infrastructure failure, mass disinformation) without effective accountability.

Impact Assessment

Structural shifts in global power:

The concept of national power is redefined. Traditional measures -- GDP, military spending, population, territory -- are supplemented or supplanted by AI-centric measures: compute capacity, data assets, AI talent density, algorithmic sophistication, and AI governance maturity. Small nations with exceptional AI capabilities (Singapore, Israel, the UAE, possibly Estonia or Finland) may wield influence disproportionate to their traditional power measures.
The nation-state faces competition from AI-empowered non-state actors. Major technology corporations controlling frontier AI systems will have capabilities -- in intelligence, economic leverage, and potentially coercive power -- that rival or exceed those of most nation-states. The governance of the relationship between sovereign states and AI-empowered corporations becomes a central political question.
Nuclear-era institutions prove inadequate. The UN Security Council, the NPT regime, and other post-WWII international institutions were designed for a world of nation-state competition with nuclear weapons as the ultimate arbiter. AI disrupts this framework: it is dual-use in ways that make non-proliferation nearly impossible, it empowers non-state actors, and it operates at speeds that exceed human decision-making. New institutions are needed but may not emerge without a catalyzing crisis.

The Global South in 2046:

The bifurcation within the developing world becomes permanent. Countries that invested in AI capacity in the 2026-2035 window -- India, Brazil, Indonesia, Nigeria, Kenya, Vietnam, and a few others -- will have established self-reinforcing AI ecosystems. Those that did not will face structural exclusion from the AI economy, analogous to countries that never industrialized in the 20th century but with potentially more severe consequences, as AI affects not just manufacturing but all cognitive economic activity.
Digital colonialism has concrete institutional form. In countries dependent on foreign AI systems for governance, financial services, healthcare, and education, sovereignty is functionally compromised. Decisions about credit allocation, resource distribution, criminal justice risk assessment, and even curriculum content are made by algorithms designed, trained, and controlled elsewhere. Resistance movements -- demanding AI sovereignty, data repatriation, and algorithmic self-determination -- will be a defining political force in the Global South.
The "AI development ladder" question is resolved. Either AI has opened new pathways for economic development (AI-enabled services, AI-optimized agriculture, AI-driven leapfrog in healthcare and education) or it has permanently closed the traditional pathways without providing viable alternatives. The evidence as of 2026 points toward a mixed outcome: AI opens some doors while closing others, but the net effect depends enormously on domestic policy, international cooperation, and the specific choices of the dominant AI powers.

Cross-Dimensional Effects

Security and conflict (Dimension): By the long-term horizon, AI will have changed the nature of warfare as fundamentally as gunpowder or nuclear weapons. The critical question is whether international norms and institutions emerge to manage military AI before a catastrophic failure forces their creation. The analogy to nuclear weapons governance is instructive but imperfect: nuclear weapons are discrete, countable, and inspectable; AI capabilities are diffuse, dual-use, and difficult to verify. Arms control for AI will require fundamentally new verification and enforcement mechanisms.

Digital divide (Dimension): The long-term digital divide is not just a gap in access to technology but a gap in agency -- the ability to shape, govern, and benefit from AI systems. By 2046, this divide could be the defining axis of global inequality, surpassing income, wealth, and health disparities in its consequences for human capability and freedom. The divide will run not only between nations but within them, as AI-augmented elites in every country pull further ahead of those without AI access or literacy.

Ethics and regulation (Dimension): The long-term governance challenge is managing AI systems whose capabilities approach or exceed human-level intelligence. Existing ethical frameworks -- whether utilitarian, deontological, or rights-based -- were developed for human decision-making. Applying them to AI systems that operate at superhuman speed and scale, across jurisdictions, and with emergent capabilities not anticipated by their designers, requires fundamental philosophical and institutional innovation. The geopolitical dimension is that different civilizations may arrive at fundamentally different ethical frameworks for AI, creating not just regulatory divergence but value divergence.

Economic models (Dimension): If AI automates a large fraction of cognitive labor by the 2040s, the relationship between labor, capital, and economic value will have been transformed in ways that challenge the foundational assumptions of both capitalism and socialism. The geopolitical implications are profound: national economic models that cannot adapt to post-labor economics will face internal instability that constrains their external power. The countries that solve the political economy of AI abundance -- distributing AI-generated wealth in ways that maintain social cohesion and political legitimacy -- will be the stable powers of the mid-21st century.

Education and training (Dimension): By the long-term horizon, the concept of "education for employment" may have been transformed beyond recognition. If AI performs most cognitive tasks, human education becomes less about skill acquisition and more about judgment, creativity, meaning-making, and the ability to govern AI systems. Countries that make this transition in their educational systems will produce citizens capable of thriving in an AI-saturated world; those that cling to industrial-era educational models will produce citizens who are neither employable by traditional measures nor equipped to exercise agency in an AI-mediated society.

Actionable Insights

For long-term strategic planning:

Treat AI geopolitics as a 30-year structural force, not a policy cycle issue. The decisions made in 2026-2030 about AI governance, compute infrastructure, talent development, and international cooperation will determine geopolitical outcomes through mid-century. Strategic planning horizons must extend accordingly.
Plan for AI capability trajectories that include discontinuous jumps. Linear extrapolation of current capabilities is almost certainly wrong; the question is whether surprises come faster or slower than expected.

For international governance:

Begin building the institutional architecture for AGI governance now, before the technology arrives. Waiting until AGI is imminent (or achieved) will be too late -- the competitive pressures at that point will overwhelm cooperative instincts.
Create international AI safety research institutions with genuine multilateral participation, including China. The Bletchley/Seoul/Paris summit process is a beginning, but it must evolve into standing institutions with technical capacity, not just political declarations.
Develop AI arms control frameworks that address the unique verification challenges of software-based capabilities. Novel approaches -- algorithmic auditing, compute monitoring, mandatory safety testing for frontier systems -- need to be explored and piloted now.

For the Global South:

The long-term strategy must focus on AI agency, not just AI access. Having access to AI tools is necessary but insufficient; what matters is the ability to shape AI development priorities, govern AI deployment, and capture economic value from AI applications.
Invest in the institutions of AI governance: regulatory bodies, standards organizations, research ethics committees, and judicial capacity to adjudicate AI-related disputes. These institutional capabilities take decades to build and cannot be imported or outsourced.
Pursue "AI leapfrog" strategies in sectors where traditional infrastructure is absent. Just as some African nations leapfrogged landline telecommunications with mobile phones, AI may enable leapfrogs in healthcare (AI diagnostics where doctors are scarce), education (AI tutoring where teachers are scarce), agriculture (precision agriculture where extension services are scarce), and governance (AI-assisted administration where bureaucratic capacity is limited).

For individuals and civil society:

Engage with AI governance as a democratic imperative. The decisions being made about AI -- who builds it, who governs it, who benefits, who bears the risks -- are among the most consequential of the 21st century. They should not be left to technologists and governments alone.
Build AI literacy as a form of civic competence. Understanding how AI systems work, what they can and cannot do, and how they affect your life is becoming as essential as basic literacy and numeracy.
Support international cooperation on AI governance. The alternative -- uncontrolled AI competition between great powers, with everyone else as collateral -- is in no one's interest except those who believe they will win the race. And the consequences of losing may extend far beyond national borders.

Sources & Evidence

RAND Corporation -- Long-range assessments of AI and national security, autonomous systems governance, and great-power competition dynamics. rand.org
IISS -- "AI and the Future of Warfare" -- analysis of how AI transforms military capabilities and strategic stability. iiss.org
SIPRI -- "Artificial Intelligence, Nuclear Risk, and International Security" -- research on AI's impact on nuclear command and control and strategic stability. sipri.org
Carnegie Endowment -- Analysis of AI's impact on the Global South, digital colonialism, and surveillance technology exports. carnegieendowment.org
Foreign Affairs -- "Artificial Intelligence and World Order" -- assessment of how AI restructures international power dynamics. foreignaffairs.com
Brookings Institution -- Long-term analysis of digital sovereignty and AI governance architectures. brookings.edu
UN AI Advisory Body -- Recommendations for international governance of advanced AI systems. un.org
IMF -- Projections of AI's differential economic impact across country income levels through 2040. imf.org
Chatham House -- "AI, Geopolitics and Global Governance" -- frameworks for managing AI in the international system. chathamhouse.org
Oxford Martin School -- Long-range research on AI's impact on employment, economic structure, and societal transformation. oxfordmartin.ox.ac.uk
CFR -- Background on US-China technology competition and long-term trajectory. cfr.org
WEF Future of Jobs Report 2025 -- Projections on AI's impact on global employment and economic models. weforum.org