By Zubina Ahmed · Contributing Journalist · Gulf & Asia
Nations now treat artificial intelligence the way they once treated oil. A field guide to the sovereign-AI race — who leads, who is catching up, and what “AI independence” now means for capital, security and the global balance of power.
AI is likely to be one of the more important technologies of the 21st century, and nations are coming to see AI system technologies the way they came to see oil in the 20th century, industrial manufacturing in the 19th, and the internet in the early digital age. Embedded AI systems are becoming a critical technology in multiple fields, and nations are learning that dependency on foreign AI systems can be a growing security risk. For this reason, a growing number of countries are devising the means to develop, adopt, manage and exercise control of AI systems on their own terms in their own countries.
This has resulted in an AI independence global competition that has become a strategic investment race for countries in their computing, semiconductor and data infrastructures, workforce and regulatory frameworks. Countries are likely to be investing to secure lasting strategic advantages in a world increasingly dominated by AI, and are likely to be doing so simply to maintain technological parity with their competition. This has become a rapidly evolving and critical driver of international relations and industrial policy, and is redefining a nation’s competitiveness.
Understanding Sovereign AI
Sovereign AI means the ability of a country to have the power to control the creation and use of AI technologies within a country. This means more than just having AI models. The real AI sovereignty means having the means for computing, developing the expertise, having a secure data ecosystem, having the ability to regulate it, and having the technology to do it.
This idea started developing out of the worry that the AI field is controlled by a small number of countries and tech companies. Currently, most of the world's advanced AI systems are located in the United States, while the most important semiconductor fabrication relies on Taiwan, South Korea, and a small number of companies.
Because of this concentration, many other countries began to consider the consequences of AI technologies being controlled by a small number of countries, and the potential trade and geopolitical conflicts. This concern of reliance on other states for AI systems has made many countries prioritize developing sovereign AI systems. Nations are seeking sovereign AI to strengthen their domestic economies, protect national security, mitigate geopolitical shocks, and reflect national values.
Why AI Sovereignty Matters?
National Security
Modern armies utilize AI for many areas like processing intelligence, surveillance, logistics, and cyber operations. Many systems perform fully or partially autonomously. Nations could become strategically vulnerable if they rely on third party AI tools. Because of this, many governments see AI as a necessary part of defense.
Military strategists think that many future wars will involve AI systems making decisions and acting without human intervention. Countries that do not have national AI capabilities may be at a significant disadvantage in traditional and cyber warfare.
Economic Competitiveness
According to the World Economic Forum in the upcoming decades the AI industry will generate trillions of dollars and flow large amounts of revenue to various nations. Experts at WEF say the value of the work that could be performed by AI constitutes $4.5 trillion in the US today. In other words, AI capability has developed so rapidly, countries that cultivate their own AI ecosystems will likely reap reward from new innovative products and services and improved productivity.
High sensitivity use cases
According to Deloitte Canada, National security applications, population-scale health data, and systems affecting democratic and electoral processes warrant heightened sovereignty requirements or even sovereign ownership where capability gaps exist. The policy rationale is likely sufficiently compelling to accept competitiveness trade-offs.
As per the same Deloitte report, Energy grids, telecommunications networks, satellites, financial systems and government operations increasingly depend on AI for operations and optimization. Ensuring these systems can function under adversarial conditions—including supply chain disruptions or foreign disputes—are areas of legitimate sovereignty concern and may benefit from additional requirements.
Data Privacy
According to experts from Carbon60, it is about keeping data in the right geographical location, managing cross-border transfers, and complying with regulators. Data privacy serves as the fuel for modern AI systems. Governments increasingly seek to ensure that sensitive national, commercial, and citizen data remains under domestic legal and regulatory control. Concerns about privacy, cybersecurity, and foreign surveillance have led many countries to adopt stricter data localization policies. Sovereign AI strategies frequently include requirements that critical datasets be stored and processed within national borders.
Technological Resilience
Recent disruptions to global supply chains highlighted the risks of excessive dependence on foreign technology providers. The COVID-19 pandemic, semiconductor shortages, and geopolitical tensions demonstrated how quickly access to critical technologies can become constrained.
AI sovereignty is therefore viewed as a form of technological insurance, helping nations maintain continuity and resilience during periods of uncertainty.
How AI Competition Could Reshape Global Power and Cooperation
The United States and China currently lead the global AI race, but other nations such as India, members of the European Union, Singapore, and the United Arab Emirates are also developing strong AI capabilities. This competition is driving investments in semiconductors, computing infrastructure, data systems, and AI talent.
The United States
The United States remains the dominant force in the global AI ecosystem. It hosts many of the world's leading AI companies, research institutions, cloud computing providers, and venture capital networks. "Big Tech" hyperscalers—such as Microsoft, Google, Amazon, and Meta—are expected to spend billions on AI infrastructure, vastly outpacing competitors.
According to the Atlantic Council, the U.S. currently controls approximately 75% of global AI computing power and, per Morgan Stanley, is leading the build-out of the massive data centers required to train frontier models. America retains the world's leading startup and venture capital ecosystems. American universities and private tech conglomerates continue to draw international talent, solidifying the U.S. as the home base for frontier models developed by organizations like OpenAI and Anthropic.
American firms have played a central role in developing foundational AI models and infrastructure. Massive private-sector investment, combined with strong university research programs, has created a powerful innovation ecosystem that continues to attract global talent.
Last year, for instance, kicked off with Trump’s announcement of Stargate, with the aim of investing $500 billion in AI infrastructure over five years. The principle driving this trend is straightforward: Countries think they must control AI before it controls them. Consequently, there was a wave of sovereign AI announcements in 2024 and 2025. That momentum grew in 2026, starting with the launch of India’s sovereign large language model at the AI Impact Summit in February.
The White House’s AI Action Plan, published in July 2025, made it the stated policy of the federal government to export the US stack to third-party countries, including via potential funding support from the US Department of Commerce for other governments to purchase offerings from the likes of Microsoft, OpenAI, and Nvidia
China
China has emerged as the most significant challenger to American AI dominance. Over the past decade, the Chinese government has invested heavily in AI research, infrastructure, talent development, and industrial policy.
China's approach differs from that of many Western countries. Rather than relying primarily on market forces, Beijing has adopted a state-directed strategy aimed at achieving technological self-sufficiency. This includes substantial support for domestic semiconductor production, AI startups, research institutes, and national computing infrastructure.
Export controls and restrictions on advanced semiconductor technologies have accelerated China's efforts to reduce dependence on foreign suppliers. While challenges remain, China's commitment to AI independence is driving rapid innovation across multiple sectors.
In 2026, the People’s Republic of China’s (PRC’s) AI-enabled disinformation efforts are likely to intensify in scale, persistence, and technical sophistication, particularly those targeting Taiwan. PRC actors are already using AI-generated audio, video, and text, distributed through networks of fake accounts and contracted private firms, to conduct “cognitive warfare” campaigns aimed at shaping political perceptions and voter behavior. These campaigns prioritize volume, localization, and algorithmic exploitation, and they are designed to be continuous rather than episodic.
At the same time, Beijing is expected to pair these activities with defensive diplomatic messaging that rejects allegations of PRC-linked disinformation or cyber operations and reframes such claims as politically motivated attacks. This pattern reinforces a broader hybrid strategy in which AI-enabled influence operations, cyber activity, and diplomatic signaling are tightly integrated. In 2026, PRC disinformation campaigns are likely to focus less on overt propaganda and more on shaping narratives around crises and cyber incidents, contesting blame, eroding trust in attribution, and influencing strategic decision-making outcomes.
Europe
The European Union has adopted a distinct approach to AI sovereignty. Rather than focusing solely on technological competition, Europe seeks to combine innovation with regulatory leadership.
European policymakers emphasize the importance of trustworthy, transparent, and human-centered AI. The region has invested in AI research and digital infrastructure while simultaneously developing comprehensive regulatory frameworks.
Europe faces unique challenges because it lacks the concentration of major AI firms found in the United States and China. To address this gap, governments have launched initiatives designed to strengthen domestic AI capabilities and reduce dependence on foreign platforms.
The concept of "strategic autonomy" has become central to European policy discussions. This involves ensuring that Europe can access critical technologies while preserving its values, regulatory standards, and economic independence.
The European Commission has earmarked billions of euros for so-called AI gigafactories, or high-performance computing infrastructure, from Estonia to Spain, while national leaders also vocally called for a “Euro stack.” The Chinese Communist Party is urging local firms to forgo Western AI know-how and rely instead on domestic alternatives from companies such as Alibaba or Huawei.
United Kingdom
The United Kingdom's AI strategy seeks to combine innovation with responsible governance. Policy priorities include expanding AI research, supporting startups, attracting global talent, and integrating AI into public services. The UK has also emphasized AI safety and international leadership through the establishment of specialized institutions and global forums dedicated to managing emerging AI risks.
Key strengths of the UK in AI
The UK is home to major AI companies and research organizations such as DeepMind, which pioneered many advances in modern AI.
Universities including University of Cambridge, University of Oxford, and Imperial College London are internationally recognized for AI research.
London is one of Europe's largest AI startup ecosystems. Research suggests that over 40% of UK AI firms are concentrated there.
The UK government has been investing heavily in AI infrastructure and research:
A new £1.1 billion AI Hardware Plan aims to strengthen domestic chip development, AI computing infrastructure, and workforce skills.
The plan includes funding for a national AI supercomputer and support for British semiconductor companies.
UK Research and Innovation has committed £1.6 billion to AI research and innovation between 2026 and 2030. Key focus areas include explainable AI, agentic AI, edge computing, and sustainable AI systems.
AMD announced plans to invest up to £2 billion in UK AI research, computing infrastructure, and partnerships with universities and research organizations.
The UK is also expanding AI adoption in industries such as manufacturing, healthcare, cybersecurity, and public services.
Canada
Canada is one of the world's notable AI research hubs, and in 2026 it is putting significant emphasis on turning that research strength into economic growth and broader AI adoption.
Canada helped pioneer modern AI through researchers such as Geoffrey Hinton and institutions like Vector Institute, Mila, and Alberta Machine Intelligence Institute.
In June 2026, the Canadian government launched a new national strategy called "AI for All", aiming to accelerate AI adoption across businesses, education, healthcare, and government services. The strategy targets:
- $200 billion in additional economic growth
- 250,000 AI-related jobs
- Increased business adoption of AI
- AI literacy and training programs for Canadians
- Greater Canadian control over AI infrastructure and technology ("AI sovereignty")
Canada is also focusing on responsible AI, including privacy protection, transparency, AI safety evaluation, and measures against harmful uses such as non-consensual deepfakes.
One challenge is that Canada has strong AI research but historically lower rates of AI adoption by businesses compared with some other advanced economies. The new strategy is designed to close that gap.
AI infrastructure is becoming a major topic. Provinces such as Alberta are trying to attract AI data centres, while policymakers debate how to balance AI growth with energy and environmental goals.
According to the Bank of Canada, AI has not yet caused large-scale job losses in Canada, though it is expected to change how many jobs are performed and could improve productivity over time.
India
India is also becoming one of the world's most important AI markets and development hubs. India's AI policies emphasize the use of artificial intelligence for social and economic development. National strategies identify healthcare, agriculture, education, transportation, and smart governance as priority sectors.
Key developments in AI in India
- Government initiatives: The India AI Mission aims to strengthen AI infrastructure, computing capacity, datasets, and skills development.
- Growing startup ecosystem: Companies such as Sarvam AI, Krutrim, and many others are building large language models, voice AI, and enterprise AI solutions.
- AI for Indian languages: A major focus is developing AI that works across India's diverse languages, making technology more accessible.
- Education and skills: Universities, online platforms, and companies are expanding AI and machine learning training programs.
- Industry adoption: AI is increasingly used in healthcare, agriculture, finance, manufacturing, education, and government services.
Singapore
Singapore's AI strategy focuses on practical implementation and public-sector innovation. Government initiatives encourage collaboration between industry, academia, and public institutions.
Key AI Initiatives in Singapore
- National AI Strategy (NAIS 2.0): Singapore's roadmap for becoming a leading AI hub, focusing on economic growth, public services, talent development, and responsible AI governance.
- AI Research Funding: The government has committed over S$1 billion from 2025–2030 to strengthen AI research, innovation, and talent development.
- National AI Council: Established in 2026 and chaired by Prime Minister Lawrence Wong to coordinate the country's AI agenda.
- National AI Impact Programme: Aims to help 10,000 businesses adopt AI and improve workforce capabilities.
OpenAI signed a partnership with the Singapore government in 2026 to launch an Applied AI Lab and support AI talent development and innovation.
NVIDIA, Google, and other technology leaders are collaborating with Singapore on AI deployment and ecosystem growth.
- Semiconductor and cloud infrastructure investments are expanding to support rising AI demand.
United Arab Emirates
The United Arab Emirates (UAE) has positioned itself as one of the world's most ambitious countries in the field of artificial intelligence (AI). It has invested heavily in AI research, government adoption, infrastructure, and talent development as part of its strategy to diversify its economy beyond oil.
Key UAE AI Initiatives
The UAE launched the UAE National Strategy for Artificial Intelligence 2031, aiming to make AI a major contributor to economic growth and government efficiency.
In 2017, the UAE became the first country to appoint a dedicated AI minister, Omar Sultan Al Olama.
The UAE established Mohamed bin Zayed University of Artificial Intelligence in Abu Dhabi, one of the world's first graduate-level universities focused entirely on AI.
MBZUAI conducts research in machine learning, computer vision, natural language processing, robotics, and related fields.
The Abu Dhabi-based AI company G42 has become a major player in AI development, cloud computing, and healthcare AI.
G42's subsidiary Inception has developed Arabic-focused AI models.
The UAE-backed technology company MGX has invested heavily in AI infrastructure and global AI partnerships.
The UAE has invested significantly in AI systems designed for Arabic speakers, including large language models such as: Jais and Falcon.
AI is used across UAE government services, including:
- Smart traffic management
- Digital government services
- Healthcare diagnostics
- Security and surveillance systems
- Energy optimization
Cities such as Dubai and Abu Dhabi are integrating AI into transportation, urban planning, and public services.
Global AI Investment Trends
As artificial intelligence becomes a critical driver of economic growth, national security, and technological innovation, AI sovereignty will increasingly shape global politics and development. According to the Organisation for Economic Co-operation and Development AI Policy Observatory:
Global venture capital investment in AI reached approximately US$258.7 billion in 2025.
AI represented 61% of all global VC investment, up from 30% in 2022.
Generative AI funding grew from roughly US$2.8 billion (2022) to US$35.3 billion (2025).
The United States attracted about 75% of global AI VC funding, while the EU, China, and the UK followed at much smaller shares.
AI infrastructure and hosting became the largest investment category, reflecting the race to build compute capacity and data centers.
Assessing Future Opportunities, Risks of AI Sovereignty
While the pursuit of sovereign AI presents significant opportunities, it also introduces substantial risks and complex policy challenges that governments must address.
The sovereign AI race is still in its early stages. Over the next decade, competition is likely to expand beyond model development to encompass energy resources, quantum computing, advanced semiconductors, and next-generation communications networks.
At the same time, AI is encouraging new international partnerships and alliances focused on research, technology sharing, and governance. However, intense competition could also fragment the global technology landscape into rival AI ecosystems with different standards and regulations.
Despite these rivalries, countries will likely need to cooperate on issues such as AI safety, cybersecurity, climate change, and international governance. As a result, the future AI landscape is expected to involve both competition and collaboration, with technological capability becoming a key factor in global power and international relations.
Future Risks
Technological Fragmentation
One of the greatest risks is the emergence of fragmented AI ecosystems. Different countries may develop competing standards, regulations, and technological platforms, creating barriers to international cooperation and interoperability. This fragmentation could increase costs for businesses, slow technological diffusion, limit knowledge sharing and create geopolitical divisions.
Intensified Geopolitical Rivalry
AI competition may exacerbate tensions among major powers. Strategic concerns over semiconductors, computing infrastructure, data access, and military applications could contribute to technology war, export restrictions, economic sanctions and increased geopolitical instability.
Concentration of Power
Despite efforts to promote sovereignty, AI development remains highly concentrated among a limited number of countries and corporations. This concentration could increase global inequalities, limit access to advanced technologies, strengthen monopolistic market structures and reduce opportunities for developing economies.
Ethical and Social Risks
The widespread deployment of AI raises concerns regarding privacy violations, algorithmic bias, discrimination, mass surveillance, and misinformation and disinformation.
Without effective oversight, sovereign AI initiatives may prioritize strategic interests at the expense of civil liberties and human rights.
Workforce Disruption
AI-driven automation could transform labor markets by replacing certain tasks and occupations. While new jobs may emerge, workers in vulnerable sectors may face job displacement, income inequality, skills mismatches and economic insecurity.
Geoffrey Hinton on AI independence
Geoffrey Hinton, widely recognized as the "Godfather of AI" is best known for his work in deep learning and his warnings about advanced AI risks, rather than advocating specific AI sovereignty policies. His views suggest that governments increasingly see AI as a critical strategic asset, leading them to invest in research, talent, data infrastructure, and semiconductor capabilities to strengthen economic and geopolitical influence.
Hinton recognizes AI's potential to boost productivity, drive scientific and medical breakthroughs, create new industries, and enhance global competitiveness. However, he warns that these benefits may be unevenly distributed, concentrating wealth and power among a small number of companies and countries.
He has also highlighted AI's growing importance for national security, including intelligence, cybersecurity, military planning, and information operations. This can intensify international competition and create incentives to prioritize rapid development over safety.
A central concern in Hinton's commentary is that an AI race between nations could resemble an arms race, where competitive pressures undermine safety measures and responsible governance. He argues that many AI-related risks—including safety, misinformation, cyber threats, and autonomous weapons—cannot be effectively managed by any single country acting alone.
Overall, Hinton's perspective suggests that the pursuit of AI sovereignty presents both major opportunities and serious risks. The key challenge is balancing national interests and technological progress with safety, regulation, and international cooperation.
Zubina Ahmed is a contributing journalist at Universal Asset Owners. A multimedia journalist and reporter for CBC, Canada’s national public broadcaster, she has reported on business and markets across the Middle East, India and Canada for outlets including CNBC, Khaleej Times, Gulf Business and CNN-IBN. Read her full profile →