More from this creator
Other episodes by Kitty Cat.
More like this
If you liked this, try these.
Transcript
The full episode, in writing.
Artificial intelligence is driving some of the most consequential shifts in global politics and society in 2026. The Atlantic Council identifies eight distinct ways that AI is actively shaping the world order, influencing power dynamics, economic competition, information flows, and even the nature of international conflict.
First, AI is accelerating the global technology race among major powers. In 2026, countries with robust AI research ecosystems and large pools of training data are pulling ahead in economic and military competitiveness. The ability to train large language models now hinges on access to advanced semiconductor chips, such as 5-nanometer and 3-nanometer nodes, which are produced by a handful of firms in East Asia. These chips power the world’s top AI systems, and the countries that control them have outsized influence on global supply chains. The U.S., China, South Korea, and Taiwan are central in this rivalry, because their companies dominate both the design and fabrication of leading-edge chips.
Second, AI is fundamentally changing the nature of military power and strategy. As of 2026, militaries are deploying autonomous drones and swarms that can coordinate attacks without human intervention. These systems can analyze battlefield data, make split-second targeting decisions, and adapt their tactics in real time. In recent exercises, simulated drone swarms have outmaneuvered traditional air defenses by overwhelming them with sheer numbers and unpredictable flight paths. The adoption of AI-driven targeting systems also means that decision timelines are shrinking from hours to mere seconds, forcing military planners to rethink entire command structures. This technological leap is increasing instability because it raises the risk of accidental escalation: once an automated system detects a threat, it may respond faster than humans can intervene to de-escalate.
Third, AI is transforming global information environments, making disinformation more powerful and harder to detect. Generative AI systems can produce text, audio, and video that mimic the voices and faces of world leaders with near-perfect accuracy. In 2026, this capability is being weaponized in influence operations that target elections and crisis situations. “Deepfake” videos, for example, have already been used to impersonate government officials and spread false information about troop movements or peace negotiations. Because generative AI can adapt to local languages and cultural nuances, these campaigns are increasingly difficult for both governments and tech platforms to counter. The scale is massive: a single actor can now automate the creation of millions of tailored social media messages or fake news videos in a single day.
Fourth, AI is reshaping the global labor market and economic power, amplifying both productivity and economic disruption. As AI systems automate tasks in logistics, manufacturing, and service industries, countries with agile workforces and strong retraining programs are benefiting, while those without are seeing unemployment rise. For context, estimates from recent years have projected that up to 300 million full-time jobs across OECD countries could be affected by large-scale AI automation by the end of the decade. This economic divide is feeding into geopolitical resentment: nations left behind by the AI revolution are seeking new alliances and trade agreements to offset their disadvantages, while those at the frontier are investing billions in workforce transformation funds and digital infrastructure.
Fifth, AI is introducing new vulnerabilities into critical infrastructure, including the power grid, water systems, and transportation networks. In 2026, governments are reporting an increase in cyberattacks targeting the software that manages these essential services. Many of these attacks exploit machine learning algorithms that control real-time responses to changing conditions. For example, an adversary can now deploy AI-based malware that learns the operational patterns of a city’s power grid and then launches a coordinated attack to cause blackouts at moments of maximum disruption. Because these systems are increasingly automated, there’s often no human in the loop to catch subtle manipulations until after significant damage has been done.
Sixth, the governance of AI is becoming a new axis of international diplomacy and competition. As of 2026, countries are proposing competing models for AI regulation, ethics, and data governance. The European Union, for instance, is advocating for a rules-based approach centered on privacy, transparency, and human rights, with legislation mandating that high-risk AI systems undergo independent audits and registration. Meanwhile, other countries are prioritizing innovation and economic growth over regulatory safeguards, arguing that excessive red tape will slow technological progress and cede ground to rivals. In multilateral forums, these competing visions are leading to diplomatic standoffs, as nations try to set global norms that will favor their own companies and strategic interests.
Seventh, the rise of AI is changing the calculus of sanctions, export controls, and economic statecraft. In 2026, governments are using targeted restrictions on AI-related technology and data flows to hinder their adversaries’ military and economic capabilities. For example, the United States and its allies have implemented export bans on advanced graphics processing units (GPUs) and AI chips to slow the development of military AI in rival states. These restrictions extend not just to hardware, but also to collaboration on AI research, access to software libraries, and even the sharing of large training datasets. Because AI development depends on the global movement of talent, these controls are also affecting immigration policy, as skilled researchers are increasingly treated as strategic assets.
Eighth, AI is transforming global development and the balance of power between the Global North and Global South. As lower-income countries gain access to open-source AI models and cloud-based tools, they’re leapfrogging traditional stages of development, deploying AI in healthcare, agriculture, and education at a scale that was impossible even five years ago. In some African and South Asian countries, AI-powered diagnostic systems are reaching remote rural clinics where no doctors are available, enabling early detection of diseases and improving health outcomes for millions. At the same time, these advances create dependency on cloud infrastructure and software controlled by a handful of multinational companies, raising new questions of digital sovereignty and the risk of “AI colonialism.”
The technology race sparked by AI is driving not just economic rivalry but also fundamental shifts in diplomatic alliances. Countries are forming new blocs around shared approaches to data governance, semiconductor supply chain security, and AI research collaboration. For instance, coalitions have formed to finance alternative chip fabrication plants outside traditional hotspots like Taiwan and South Korea, aiming to reduce the risk of single points of failure. These alliances are also pooling resources for AI safety research and building cross-border data-sharing agreements, but their effectiveness is limited by divergent national interests and regulatory philosophies.
AI’s impact on military power is also forcing NATO, the Shanghai Cooperation Organization, and other security alliances to rethink their doctrines. War games in recent years have highlighted that traditional defense measures — like centralized command centers and fixed radar installations — are increasingly vulnerable to autonomous attack systems. The speed at which AI-enabled weapons operate is compressing the “decision loop,” meaning that commanders may have mere seconds to authorize or abort a retaliatory strike. This technological compression is prompting militaries to explore “human-on-the-loop” models, where AI proposes options but a human retains the final say, though there are concerns that this safeguard erodes under pressure.
Disinformation powered by AI is disrupting elections not just in major economies but in smaller states as well. In recent cycles, election commissions in countries such as Estonia and Kenya have documented coordinated AI-driven influence operations that target specific ethnic groups, generate fake endorsements, or spread conspiracy theories at critical moments. Because AI can generate content in dozens of languages and dialects, these attacks are bypassing traditional content moderation tools and overwhelming fact-checkers. In one documented incident, a deepfake video featuring a high-profile candidate purportedly conceding defeat was released hours before polls closed, prompting confusion and unrest before it could be debunked.
AI’s economic impact is visible in trade negotiations and supply chain relocations. Countries that have invested heavily in AI-driven logistics and manufacturing automation are reshaping global trade routes and the flow of goods. For example, port authorities in Singapore and Rotterdam are using AI to optimize container movement and customs processing, reducing turnaround times by more than 30 percent compared to 2020 levels. This efficiency is pressuring ports in developing economies to automate or risk being bypassed. As a result, governments are launching billion-dollar incentive programs to attract foreign investment in AI-powered infrastructure.
The vulnerability of critical infrastructure to AI-driven cyberattacks has triggered new international agreements on cyber norms and “red lines.” In 2026, several G20 members have signed memoranda of understanding that pledge not to target each other’s hospitals or emergency response systems with AI-enabled cyber tools. These agreements are fragile, however, because attribution is difficult: many attacks route through compromised third-party servers and use AI to mimic the tactics of local criminal groups. As a result, even well-intentioned rules are challenging to enforce in practice, and some countries are suspected of using proxies to skirt treaty obligations.
When it comes to AI governance, the tension between open-source and proprietary models is fueling diplomatic friction. OpenAI’s decision to restrict access to its latest model weights — citing national security concerns — has led other countries to double down on their own sovereign AI projects. Meanwhile, the European Union’s “AI Act” is being cited by advocacy groups as a template for global regulation, though its requirements for transparency and bias mitigation are facing pushback from multinational tech giants. In the absence of global consensus, countries like India and Brazil are piloting homegrown AI regulations that blend elements from both sides, creating a patchwork of local rules that complicate cross-border business.
The use of AI in economic statecraft is producing a ripple effect across multiple sectors. Sanctioned states are responding to export controls by building parallel technology ecosystems, investing heavily in indigenous chip manufacturing, and launching clandestine efforts to recruit foreign AI talent. In one reported case, a state-backed entity attempted to poach an entire research team from a leading AI lab by offering salaries three times the European average. This scramble for talent is also creating ethical dilemmas for universities, which are being pressured to screen research partnerships for national security risks.
AI’s effect on international development is visible in the rapid adoption of precision agriculture in Southeast Asia. Governments are using AI-powered sensors and drones to monitor crop health across tens of thousands of square kilometers, allowing for real-time intervention that boosts yields and reduces water usage. The Food and Agriculture Organization has documented pilot projects where rice harvests have increased by 15 percent compared to fields managed with older methods. These projects are often financed by public-private partnerships that include Chinese, European, and American tech firms, raising questions about data ownership and the long-term sustainability of these arrangements.
AI is also heightening the risk of “splinternet” fragmentation, as countries impose data localization laws and mandate the use of domestically-developed AI models for sensitive applications. In 2026, at least 40 nations have enacted legal requirements that critical data generated within their borders must be stored and processed locally. This is leading to the proliferation of incompatible technical standards and “walled garden” ecosystems, complicating global commerce and cross-border research. Major cloud providers are responding by building regional data centers and negotiating special access arrangements with national regulators.
The arms race in AI is spurring a wave of investment in STEM education and talent development. Governments are pouring money into university partnerships, scholarship programs, and national centers of excellence for AI research. One East Asian country has announced a plan to quadruple its annual output of computer science graduates by 2030, aiming to train 100,000 new specialists per year.
AI is changing the rules of humanitarian intervention and disaster response. During severe flooding events in South Asia, AI-powered satellite analysis is being used to map affected areas, direct relief supplies, and predict the movement of displaced populations. These tools are becoming a new lever of soft power: countries and companies that can provide cutting-edge AI for disaster relief are gaining diplomatic influence in vulnerable regions.