The new playbook for AI leadership: The case of the United Arab Emirates
Executive summary
This report is the first in a series by the Atlantic Council’s GeoTech Center assessing emerging artificial intelligence (AI) powers around the world according to a novel five-pillar framework. The United Arab Emirates (UAE) is an example of one such power, having leveraged state coordination, long-term strategic planning, and sovereign capital to accelerate AI development and adoption at scale.
Using a five-pillar framework covering strategic vision, governance capacity, human capital, the innovation ecosystem, and industrial capacity, the report assesses the UAE’s strengths and weaknesses across the full AI value chain. The analysis finds that the UAE’s long-horizon national vision, institutional agility, and investment-led innovation model have enabled rapid progress, particularly in AI deployment, infrastructure build-out, and ecosystem formation. The country has positioned itself as a global hub for AI investment and a regional gateway linking advanced economies with the Global South. At the same time, the UAE’s model includes trade-offs. Continued reliance on expatriate talent, incipient regulatory coherence, and a need for stronger ethical safeguards, alongside rising pressure on energy and water infrastructure, are all important areas where the UAE must improve and develop policy for the sake of long-term sustainability. Geopolitically, the UAE’s balancing strategy between the United States and China has expanded its strategic options but also introduced uncertainty around supply chains and political trust. The UAE is also subject to regional instability: its AI infrastructure has been threatened by Iran during the conflict that erupted in the region in February 2026.
The framework applied here is designed to be replicable and offers policymakers and industry leaders a structured approach to benchmarking national AI readiness and identifying priority areas for intervention.
Introduction
Artificial intelligence is increasingly viewed as a transformational, general-purpose technology that will fundamentally reshape how value is generated in the global economy. Consequently, the global competition for AI dominance has shifted from commercial rivalry to questions of national security, economic competitiveness, and geopolitical influence. Much attention has focused on the strategies adopted by the United States and China, particularly as they race to secure AI supply chains, talent, and governance influence. Yet a growing group of “emerging AI powers” is carving out paths, often using structural constraints as catalysts for innovation.
These emerging AI powers, often located in Latin America, the Middle East, Africa, and Central and Southeast Asia, are actively developing AI capabilities and could gradually tilt the balance of global AI power and capabilities. Emerging economies are becoming more central to the future of the AI landscape because they bring fast-growing digital populations, rising demand for digital public infrastructure, and an expanding role in global technology supply chains. Their choices will influence whether AI adoption becomes globally inclusive or remains concentrated among a few traditional powers.
This report introduces a new comprehensive, multifaceted framework for the evaluation of national approaches to AI readiness. The analysis is structured around a multidimensional matrix, referred to as pillars, which includes regulatory factors, government-industry relations, capital, infrastructure, foreign policy, and workforce development. Each pillar is evaluated using a consistent set of metrics informed by quantitative indicators and qualitative evidence, which together help maintain comparability across countries while allowing space for contextual nuance.
While the methodology enables clear cross-country benchmarking, constraints remain. International datasets vary in depth and reliability, especially for emerging markets, so the analysis draws on a calibrated mix of global indices and documented local insights, categorized into a multidimensional matrix that includes regulatory factors, government-industry relations, capital, infrastructure, foreign policy, and workforce development.
This framework is designed to be replicable across countries. The five pillars reflect capabilities and policy levers common to all national AI strategies, regardless of economic size, political system, or stage of technological development. By anchoring the assessment in globally available indicators supplemented by local qualitative insights, the methodology balances comparability with contextual nuance. As a result, it can be applied to other countries to benchmark progress, identify structural strengths and weaknesses, and inform strategic policy interventions in national or regional AI planning.
This case study focuses on one emerging AI power: the United Arab Emirates. The UAE’s state-directed model, built on long-term vision statements, sovereign wealth instruments, a select group of national champions, and a preference for speedy bureaucracy, has propelled it into a leading hub for AI investment. The UAE also positions itself as a bridge between regions, presenting itself as a pragmatic “gateway to the Global South” while navigating a careful balance between the two largest global AI powers: the United States and China.
Five-pillar framework for national AI readiness
The framework uses five pillars: human capital, innovation ecosystem, governance capacity, industrial capacity, and strategic vision. These elements reflect the core determinants of a country’s ability to develop, deploy, and regulate AI effectively. Each pillar contains three metrics, producing fifteen metrics in total.
Each metric is assessed on a five-point scale, informed by a combination of quantitative indicators and qualitative evidence. Quantitative inputs include internationally recognized indices and global rankings, and comparative datasets track country performance in areas such as AI skills, R&D intensity, regulatory quality, and industrial competitiveness. Qualitative inputs capture the broader institutional context, including case studies, policy and strategy implementation records, and an assessment of institutional and policy efficacy. Together, these data sources provide a more holistic and context-sensitive basis for evaluation than they would offer independently. To reduce the risk of subjectivity, scoring draws on triangulated sources and consistent calibration across countries.
All pillars carry equal weight and are scored out of five, which is calculated as the average of the two to three underlying metric scores. This approach is intentional since each one represents a fundamental enabling condition for national AI competitiveness. An explanation of the scale follows.
- 1 – Very limited: The country shows minimal activity or capability in this area, with significant gaps and little evidence of effective policy action. Progress is absent or at an early, undeveloped stage.
- 2 – Weak: Some initiatives or structures exist, but they are fragmented, under-resourced, or inconsistently implemented. Overall performance remains below international norms.
- 3 – Moderate: The country demonstrates steady but uneven capability, with clear policies or assets that are only partially realized. Performance aligns with global averages but lacks coherence or depth.
- 4 – Strong: The country shows well-developed capacity with consistent implementation and measurable results. Policies and institutions are effective, though some gaps or inefficiencies remain.
- 5 – Leading: The country performs at a best practice or globally competitive level. Capabilities are mature, comprehensive, and consistently deliver high-impact outcomes.
- The sum of the framework yields a maximum total country score of 25. An explanation of the country-score scales is below.
- 0–5 – Nascent: This category of AI powers is in the early stages of drafting policies and strategies, as well as the planning stages of building the necessary supporting infrastructure.
- 6–10 – Developing: Initial infrastructure is in place and pilot programs are active in “developing” AI powers. Oversight and institutional mechanisms are not functional yet or may still be inconsistent.
- 11–15 – Established: Reliable deployment of AI solutions, regulatory frameworks are operational, and there is a unified national approach to deployment, positioning it for rapid scaling.
- 16–20 – Advanced: A high-tier innovation ecosystem and industrial scale characterize an “advanced” AI power. We would expect to see comprehensive alignment between private innovation and public priorities.
- 21–25 – Frontier: The highest-tier AI powers are leading global innovation, setting international standards, and conducting frontier research. Governance systems are mature and consistently enforced.
Based on the scoring system laid out above, the UAE scores a total of 17.5, marking it as an “advanced AI power”. A summary of the pillar scores is below, followed by a pillar-by-pillar analysis.
a. Strategic vision
The UAE has laid out a strategic long-term vision for the country, encompassing fifty years between 2021 and 2071, under the banner of Projects of the 50. The road maps outlined in this process have catalyzed an all-of-government approach to policy planning that goes beyond short-term, budget-cycle thinking and creates space for large-scale strategic projects. In a media interview, Huda Al Hashimi, deputy minister of cabinet affairs for strategic affairs, said, “When we started, we quickly realized that the UAE government needed to rebuild its capability, machinery, and culture to deliver on the vision.”
The foundation of the UAE’s AI ambitions is the UAE National Strategy for Artificial Intelligence 2031, a comprehensive blueprint issued in 2017. The strategy sets an ambitious economic target, projecting that AI will add AED 335 billion ($91.2 billion). Omar al Olama, minister for AI, succinctly captured the UAE’s thinking on AI in a November 2019 interview, “Whoever is going to lead in the artificial intelligence race will lead the future. This technology will change the world.” The 2031 strategy outlines eight strategic objectives that position the UAE as a global AI hub by investing in talent, research, adoption, infrastructure, and governance across priority sectors. AI also sits within the broader Centennial 2071 vision for the country’s soft power, which reinforces the importance of long-term planning for education and economic diversification.
The UAE’s AI foreign policy walks a delicate line between the two most powerful countries in this space: the United States and China. In 2023, White House concerns about the ties of G42 (an Abu Dhabi-based AI development holding company) to Chinese companies prompted pressure on the UAE to distance itself from certain partnerships. Later that year, G42 CEO Peng Xiao stated that the UAE “cannot work with both sides.” This narrative was backed by actions such as G42’s reported divestment from Chinese firms and the removal of Huawei equipment from its data centers. These actions signaled a willingness to shift strategically in exchange for continued access to advanced US technology, particularly cutting-edge AI chips.
These steps also shape the UAE’s long-term exposure to supply chain risk, especially around chips and cloud infrastructure. While the decoupling actions have improved access to US technologies, the degree to which they translate into sustained political trust or domestic innovation advantages will need to continue to evolve as partnerships and trust frameworks deepen over time.
Notably, Lunate, a separate holding company under the same chairmanship as G42, took over G42’s China investment fund. Additionally, other major Emirati companies continue to engage in simultaneous partnerships with both Chinese and US firms. This arrangement has drawn the attention of US government stakeholders and continues to affect the broader policy dialogue around technology partnership. US lawmakers, for instance, continue to express concerns about the UAE’s ties with Chinese AI companies. In July 2024, chairpersons of the House Foreign Affairs Committee and the House Select Committee on Strategic Competition between the United States and the Chinese Communist Party (CCP) expressed concern that “without robust protections, sensitive U.S.-origin technology transferred as part of the Microsoft-G42 partnership could end up in the CCP’s hands.” This balancing act remains one of the UAE’s most significant diplomatic tools, though it also introduces long-term uncertainty.
b. Governance capacity
The UAE has created a governance environment designed to move quickly and experiment with institutional models that prioritize its AI ambition. The National AI Strategy paved the way for innovations such as the world’s first minister of state for artificial intelligence, Omar Sultan Al Olama, who plays a central role in leading the country’s AI deployment and integration across sectors. Additionally, the UAE established the Council for AI and Blockchain, chaired by Al Olama, as a national body responsible for the integration of AI initiatives and projects at the federal government level. The council provided an additional layer of oversight while delegating execution through subcommittees coordinating departmental activities and reporting progress at annual review meetings.
At the Emirate level, Abu Dhabi’s Artificial Intelligence and Advanced Technology Council (AIATC) consists of government and industry leaders and is focused on positioning Abu Dhabi as a global hub for technology investment and entrepreneurship. Across the country, local authorities are equipped with chief AI officers (CAIOs) to oversee specific AI use cases and address risks. Twenty-two CAIOs have been appointed in the police force, judiciary, finance, and other departments by the crown prince of Dubai and chairman of the Executive Council of the city. According to the UAE AI Office, there are over fifty CAIOs across the country.1Noora Al Malek and Khaled AlNuaimi, “UAE’s AI Playbook,” interview by Trisha Ray and Ryan Pan, GeoTech Center, Atlantic Council, November 12, 2025. Their actual level of authority varies, and while these roles signal strong commitment to AI adoption, they also highlight the need for deeper clarity on decision-making power, consistency, and accountability.
The UAE has published ethical guidelines on AI use, including the International Stance on Artificial Intelligence Policy, which outlined six key principles: advancement, collaboration, community, ethics (and transparency), sustainability, and safety. In 2024, the country also published a nonbinding Charter for the Development and Use of Artificial Intelligence that outlined twelve ethical priorities, including strengthening human-machine ties, safety, algorithmic bias, data privacy, transparency, human oversight, governance and accountability, technological excellence, human commitment, peaceful coexistence with AI, promoting AI awareness for an inclusive future, and commitment to treaties and applicable laws. These frameworks help establish clear expectations and guiding principles. However, they lack enforcement mechanisms, limiting their practical reach.
The UAE has laws regulating data use and copyright, such as the 2021 Federal Decree by Law Concerning the Protection of Personal Data, modeled after the European Union’s General Data Protection Regulation, and the Federal Decree Law on Copyright and Neighboring Rights. Simultaneously, the UAE government has established free zones, where foreign investors enjoy full ownership of companies, receive complete tax exemptions, and benefit from other financial incentives for business operations. These free zones provide a flexible and regulatory-friendly environment for AI, including AI licenses and regulatory sandboxes that create controlled environments to attract foreign investments.
AI regulation continues to evolve across jurisdictions, reflecting the UAE’s decentralized and adaptive regulatory approach. Dubai’s local authorities, for instance, have issued sector-specific laws, such as the Artificial Intelligence Policy in Healthcare and Regulating the Operation of Autonomous Vehicles in the Emirate of Dubai. However, none of these laws apply to the free zones, including the Dubai International Financial Centre. Additionally, the Law No. 3 of 2024 that established the AIATC regulates AI initiatives in Abu Dhabi. The expansion of AI-enabled systems, including biometric technologies, has elevated the importance of continued development and further implementation of privacy and data governance frameworks. The Center for AI and Digital Policy’s 2026 AI and Democracy Index ranks the UAE as a “Tier 4” country, with a lack of algorithmic transparency laws and weak independent oversight. Further strengthening regulatory coherence, transparency and oversight mechanisms, and implementation pathways across jurisdictions would help reinforce investor confidence, support responsible innovation, and enhance the UAE’s position as a global leader in AI governance.
The UAE’s approach to institutional agility brings real advantages, though it also reduces opportunities for public deliberation or independent oversight. These trade-offs contribute to the mid-range governance score.
c. Human capital
The UAE has made AI skills a national priority, both for its various agencies as well as for the workforce at large. The UAE National Strategy for Artificial Intelligence 20312UAE National Program for Artificial Intelligence, UAE National Strategy. aims to attract and train talent for future jobs enabled by AI. The CAIOs program, which seeks to empower AI leaders in government to promote AI adoption, also includes training and certification modules, designed and delivered with industry partners and prominent foreign universities. Additionally, the country has recently collaborated with Google (the supporter of this report) to launch the “AI for All” initiative, a set of training programs throughout 2026. As a result of these efforts, the UAE has a small but highly skilled pool of AI talent that is still growing The UAE’s performance on AI literacy is supported by AI course offerings covering the full range of skills in the AI supply chain, including chips, data centers, and model.3The AI Academy Launches Region’s First Executive Programme for Chief AI Officer,” Khaleej Times, September 12, 2025, https://www.khaleejtimes.com/kt-network/the-ai-academy-launches-regions-first-executive-programme-for-chief-ai-officer; and “Research Centers,” Khalifa University of Science and Technology, accessed January 6, 2026, https://www.ku.ac.ae/academics/college-of-engineering/department/department-of-electrical-engineering-and-computer-science/research-centers.
While UAE salaries certainly compete with Silicon Valley, it—like the rest of the world—faces a shortage of AI talent. The Stanford AI Vibrancy Index, for instance, ranks the UAE twenty-second out of twenty-four countries on AI talent concentration.4UAE National Program for Artificial Intelligence, UAE National Strategy. Similarly, the LinkedIn AI Talent Index ranks the nation twentieth out of twenty countries on AI literacy skills; the UAE does not appear in the top tier of global AI engineering pools.
To address these gaps, in 2022, the UAE began offering new visa types to attract skilled workers. Expatriates make up 89 percent of the UAE’s population, and visa reforms aim to attract and retain foreign talent. These include the jobseeker visit visa, which enables eligible foreign nationals to stay in the country for up to 120 days to explore job opportunities, while the Green Visa allows skilled foreign workers to self-sponsor. The UAE’s immigration reform and improved access to banking and other supporting services for migrant communities are reflected in rankings: The UAE ranked fifth out of eighty-two countries in Remitly’s Immigration Index. By attracting and retaining top global researchers and students, the UAE aims to create a self-sustaining talent ecosystem that will be essential for its long-term viability as a knowledge-based economy.
The workforce strategy still relies heavily on expatriate labor. This dependency supports rapid growth but introduces long-term risks if retention rates remain low or if global demand for AI talent tightens.
d. Innovation ecosystem
With over 5,600 start-ups, the UAE has quickly become an epicenter of entrepreneurship in the region. The Global Startup Ecosystem Index 2025, which evaluates funding availability, leading industries, and the number of privately-held billion-dollar startups rated the https://www.startupblink.com/startup-ecosystem/united-arab-emirates?page=1UAE twenty-first out of 118 countries. The Global Entrepreneurship Monitor Report (2024-2025) rated the country first among fifty-four economies in the National Entrepreneurship Context index, characterizing it as a favored destination globally for potential start-ups.
The UAE’s venture environment benefits from enabling public and private institutions that offer abundant financial resources, mentorship opportunities, and high-profile networking opportunities. These institutions are largely supported by the government and play a significant role in shaping the environment. For example, the Dubai Future District Fund is mandated to boost investment in the city’s venture-capital ecosystem with AED 1 billion in funds, and ADQ, Abu Dhabi’s active sovereign investor, cultivated more than one hundred digital, data, and AI leaders and more than two hundred data and AI use cases under a digital transformation initiative. This funding model has advantages, although it also means much of the start-up landscape depends on government-linked capital, which has played a catalytic role in shaping early-stage growth. Government-linked funders bring specific mandates, time horizons, and sector preferences that influence what kinds of risk the ecosystem is willing to absorb and which types of ventures are most likely to attract backing
Communities and gatherings such as Gitex Global (a tech and AI show), the Annual Investment Meeting Congress (a convening of global leaders, policymakers, investors, and innovators), and tech ecosystem Hub71 and its AI initiative help anchor the UAE’s innovation identity. Institutions like the Mohamed bin Zayed University of Artificial Intelligence, Khalifa University of Science and Technology, and the Technology Innovation Institute have also strengthened the country’s AI research and development footprint. The uptick in Neural Information Processing Systems (NeurIPS) paper acceptances—ranking fourteenth in 2025 for this interdisciplinary conference of researchers in machine learning, neuroscience, statistics, optimization, computer vision, natural language processing, life sciences, natural sciences, social sciences, and other fields—reflect progress. Stanford HAI’s Global Vibrancy Tool, of which R&D is an essential pillar, rates the country fifth, following the United States, China, the United Kingdom, and India. The next step will depend on improving commercialization and ensuring that research outputs translate into viable products.
Innovation is currently concentrated in key hubs such as Abu Dhabi and Dubai, reflecting a model of focused ecosystem development that may expand over time. This clustering has enabled efficiency and specialization but may be harder to scale across the wider region.
e. Industrial capacity
The UAE’s Digital Economy Strategy aims to double AI’s contribution to gross domestic product from 10 percent in 2022 to 20 percent in 2032. For the Emirates, public-private partnerships have been an essential tool for mobilizing capital, securing international technology access, and building industrial capability. The country has rallied the support of US tech giants, coupled with government and private financial backing.
The UAE is accelerating the construction of data centers, which are essential to train, deploy, and deliver AI applications. The country’s current data center capacity stands at 414 megawatts (MW). In May 2025, the UAE formed a major new partnership with the US government and US tech companies, under Stargate UAE, that would expand the UAE’s capacity. The partnership agreement will create a 1 GW data center cluster. The partnership aims to create the world’s largest data center outside the United States, including 5 GW capacity offered to the nearly three billion people living within 2,000 miles (3,219 kilometers) of the UAE. This pace of expansion, while impressive, could strain the grid and risks creating short-term supply and demand misalignments—requiring careful coordination with energy planning to ensure balance over time.
Additional constraints across other types of supporting infrastructure bear attention. The World Resources Institute rates the UAE as one of the most water-stressed countries in the world, yet water infrastructure is essential for cooling data centers as well as powering energy and manufacturing software. The Gulf’s extreme heat in the summer further exacerbates this stress, given that cooling systems require a vast amount of water as well.5Kuzma, Saccoccia, and Chertock, “25 Countries.” Electricity infrastructure demand is also rising: The International Energy Agency estimates that Gulf states may need to double their electricity generation capacity to support AI infrastructure. Recently, the UAE has been diversifying its energy sources, including through nuclear and solar power, to meet its electricity needs. The UAE’s sovereign funds have also invested in closed-loop systems for data centers, which use less water than evaporative cooling systems. The country’s growing AI capacity may also help alleviate its power challenge using AI to modernize electric grids or optimize data center consumption. In the long run, the country’s infrastructure pressure may be reduced by sustainability-oriented AI investments.
Environmental pressures are an increasingly crucial factor for investors evaluating AI infrastructure. Addressing these resource constraints (water, energy) will be critical in sustaining momentum.
Recommendations for the UAE
First, the UAE’s ambitions are unfolding within a complex geopolitical environment that carries associated supply chain risks. These dynamics are reflected in continued scrutiny from the US legislative branch regarding ties with Chinese AI companies, as illustrated above. The latest regional conflict in the Middle East, starting in February 2026, has also introduced new costs for companies looking to build out AI infrastructure in the UAE, with data centers potentially becoming retaliatory targets. This reinforces the importance of incorporating risk mitigation through planning for infrastructure resilience, physical hardening, and diversified deployment strategies as part of long-term AI investment planning.
The UAE should consider a distributed infrastructure strategy: co-investing in shared infrastructure across geographically dispersed locations outside the immediate region, while simultaneously hardening domestic data centers against physical threats. Such an approach would reduce single-point vulnerabilities (whether from supply chain disruption, geopolitical pressure, or direct targeting of infrastructure) and give the UAE’s AI ecosystem a more resilient foundation that is less exposed to any single shock.
Second, the UAE government’s institutional agility could be reinforced by expanded public consultations on key AI governance areas. The UAE’s credibility as a global leader, and as a model for other countries, is dependent on how it implements transparency mechanisms. Opportunities remain to strengthen enforceable algorithmic transparency standards, consumer-facing protections, and independent regulatory oversight. Together with greater consistency across Emirates-level guidelines, these steps would help reduce regulatory uncertainty for companies and would strengthen the UAE’s credibility as a trusted forward-looking AI governance leader.
The UAE government should open clear, accessible channels for consultation with industry and civil society to strengthen its global positioning and credibility on AI governance.
Third, resource constraints, particularly on the UAE’s scarce water resources, are a significant stressor for the buildout of AI data center infrastructure. While efforts have been made to increase supply through seawater desalination projects and improve efficiency in use, economic dynamics, such as Jevon’s Paradox, suggest that efficiency gains may also drive increased demand. Desalination is also an energy-intensive process, and rising AI-related water demand will need to be carefully balanced alongside other UAE policy priorities, including food security.
We recommend a unified regulatory framework for data center licensing, aligning AI, water security, and food security goals, with mandated benchmarks for water and power usage effectiveness.
Transferrable insights and conditions for replications
The UAE case offers lessons that are relevant for other emerging economies seeking to advance national AI capabilities.
First, an AI-forward long-term strategic vision is foundational. The UAE’s use of long-term national vision statements, such as the UAE National Strategy for Artificial Intelligence 2031, and sector-specific AI strategies have helped align government agencies, attract private capital, and sustain political momentum beyond electoral or budgetary cycles. Strategic clarity has reduced policy uncertainty and mobilized public and private actors around shared objectives.
Articulating a credible long-term direction can reduce uncertainty for domestic and international partners and stakeholders.
Second, institutional agility can compensate for limited scale. The UAE’s willingness to experiment with new governance structures, including the world’s first AI minister, dedicated chief AI officers, and cross-government coordination mechanisms, has enabled faster policy execution and deployment. Dedicated leadership roles and coordination bodies signal strong political commitment. Ethical principles exist but are nonbinding, reflecting a preference for flexibility over constraint.
For other emerging economies, the UAE highlights the value of empowered coordinating bodies and clear lines of authority, even within more constrained bureaucratic systems.
Third, targeted use of public capital can catalyze innovation ecosystems. Government linked funds, public-private partnerships, and global convening platforms (e.g., Hub71, Dubai Future District Fund) have unlocked venture capital and attracted talent. Start-up growth and research output are increasing, though innovation remains geographically concentrated and reliant on government-linked funding.
While not all countries can replicate the scale of sovereign investment, public-private partnerships with clear governance and diversification can build and sustain innovation ecosystems over the long term.
Fourth, openness to global talent and partnerships remains critical. The UAE’s immigration reforms and international collaborations have enabled rapid capability building, but they also expose vulnerabilities linked to talent retention and geopolitical alignment. While the UAE has built a highly skilled but small AI workforce, it remains heavily dependent on expatriates, creating long-term retention and resilience risks.
Countries seeking to replicate this approach should pair openness with sustained investment in domestic skills development and institutional resilience across the government and general population.
Fifth, AI literacy is a core national capability. The UAE has positioned AI literacy as a core nationwide priority, rather than a niche technical skill, embedding workforce development into its broader AI strategy. Alongside targeted training for senior government officials, the country has partnered with global technology firms to expand AI awareness and foundational skills across the wider population.
Broad-based AI literacy programs can help countries normalize AI adoption, expand the pool of capable users and implementers, and ensure that the economic and social benefits of AI extend beyond a narrow technical elite.
Sixth, public-private partnerships are an enabler for local infrastructure development. The UAE’s AI industrial capacity has been built through large-scale public-private partnerships that have supported the expansion of digital infrastructure, particularly cloud infrastructure. The 2025 US-UAE partnership to develop a 1 GW data center cluster highlights the country’s ambition, while parallel investments in nuclear and solar energy reflect the UAE’s national efforts to manage infrastructure demand over the long term.
Public-private partnerships bridge critical gaps in terms of technology access, financing, and operational expertise. Such partnerships require careful alignment with national goals to be viable.
The UAE offers one of the most coherent and ambitious playbooks for AI development among emerging economies. Its experience demonstrates that emerging markets are active architects of national AI ecosystems. At the same time, the speed and unpredictability of AI’s evolution make it increasingly challenging for governments to future-proof their strategies or lock-in durable advantages. By applying this framework to additional emerging AI powers, future case studies will evaluate the transferability of this report’s framework to other emerging markets, highlight alternative pathways, and sharpen our understanding of how different institutional, economic, and geopolitical conditions shape AI development.
Replication is most feasible where certain preconditions exist. These include high-level political commitment, baseline digital infrastructure, regulatory flexibility, and the administrative capacity to coordinate across government entities. For capital- or capacity-constrained states, elements of the UAE approach may need to be adopted incrementally in target sectors or through regional cooperation.
For emerging markets, the UAE case should be understood not as a template to copy wholesale, but as a demonstration that AI competitiveness is not limited to traditional technology powers. With deliberate strategy, selective investment, and institutional adaptation, countries outside the global AI core can shape their own trajectories and influence the future distribution of AI capabilities.
About the authors
Trisha Ray is an associate director and resident fellow at the Atlantic Council’s GeoTech Center.
Ryan (Zhenye) Pan is a project assistant at the Atlantic Council’s GeoTech Center.
Raul Brens Jr. is the director at the GeoTech Center, part of the Atlantic Council Technology Programs.
acknowledgements
The Atlantic Council’s GeoTech Center is grateful to Google for its support of this report.
Note: The GeoTech Center also receives support from the Embassy of the United Arab Emirates for its broader work, which is independent of this report.
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