UAE’s TII challenges big tech dominance with open source Falcon AI models
Through its Falcon models and an open, efficiency-driven research strategy, the Technology Innovation Institute is positioning the UAE as a producer of foundational AI, not merely a consumer of global platforms
As global artificial intelligence (AI) development becomes increasingly concentrated among a handful of large technology players, the United Arab Emirates (UAE) is pursuing a different path. Rather than relying on imported models or closed ecosystems, the country is investing in open, efficient and language-native AI through the Technology Innovation Institute (TII), its applied research arm based in Abu Dhabi.
At the centre of this strategy is Falcon, TII’s family of large language models (LLMs), which have consistently ranked among the world’s top-performing open models since their debut in 2023. According to Najwa Aaraj, CEO of TII, the latest Falcon releases signal a broader ambition for the UAE’s role in global AI.
“The Falcon results demonstrate that advanced AI innovation is no longer confined to a small number of countries,” she says. “They reinforce a vision where the UAE is not just a consumer of frontier technologies, but a driver of foundational breakthroughs in AI research and innovation.”
An applied research model with national intent
Unlike many AI labs that focus primarily on commercial deployment, TII operates as an applied research institute designed to translate cutting-edge science into real-world systems. This applied focus is linked to the UAE’s wider technology strategy, which places strong emphasis on digital sovereignty, local capability building and long-term economic resilience by embedding advanced research within national infrastructure. TII aims to ensure that knowledge, skills and intellectual property are retained and developed locally.
“Efficiency is critical for real-world deployment, scalability and sustainability. By delivering high performance in compact models, we are expanding access to advanced AI without sacrificing quality”
Najwa Aaraj, TII
“Our research is developed with practical readiness in mind,” says Aaraj. “The goal is to ensure outputs can be translated into solutions that deliver real impact across government, industry and society.”
At a time when many leading AI developers are restricting access to their most advanced models, TII has doubled down on an open AI approach. Falcon models are released openly, allowing developers, researchers and institutions worldwide to build on them. For Aaraj, openness is strategic. “Openness is central to building AI that delivers national and global value,” she says. “By releasing Falcon models openly, we support transparency, collaboration and accessibility, while encouraging responsible adoption.”
Open release also allows for extensive community testing and iterative improvement, strengthening model robustness and relevance over time. In contrast to closed systems optimised for narrow commercial use cases, Falcon is designed as a set of foundational models adaptable across sectors and regions.
Arabic-first AI as a global differentiator
One of TII’s most significant contributions has been its investment in Arabic-first AI. Falcon-H1 Arabic currently leads the Open Arabic LLM Leaderboard, addressing a long-standing gap in global AI capability. “Arabic presents unique challenges for AI, from rich morphology to wide variation between Modern Standard Arabic and regional dialects,” says Aaraj. “Models trained primarily on English often struggle to capture nuance and context.”
By training models natively in Arabic rather than relying on translation, TII is enabling more accurate, context-aware applications. While the immediate benefits are regional, the global relevance is clear: Arabic is spoken by hundreds of millions of people, yet remains underrepresented in frontier AI systems. “This work positions the UAE as a leader in advancing AI for a globally significant language,” she adds.
Our direction is about building AI systems that are both globally competitive and practically useful,” explains Aaraj. “That means continued investment in applied research, efficiency-driven models and ethically governed innovation
Najwa Aaraj, TII
Another defining feature of Falcon’s evolution is its emphasis on efficiency. The Falcon H1R 7B model, for example, delivers advanced reasoning performance in a compact, seven billion-parameter architecture with significantly lower memory and energy requirements. “Efficiency is critical for real-world deployment, scalability and sustainability. By delivering high performance in compact models, we are expanding access to advanced AI without sacrificing quality.”
This performance-to-efficiency focus allows Falcon models to operate across a wider range of infrastructure environments, including those with constrained compute resources, making them particularly relevant for emerging markets and government deployments.
Despite operating without the vast commercial platforms of global hyperscalers, TII has managed to compete at the highest levels of model performance. Aaraj attributes this to a combination of deep research expertise, architectural innovation and an open source strategy. Recent Falcon releases incorporate hybrid architectures that combine classical transformers with emerging state-space models, enabling performance gains without relying solely on scale. “Our approach is about architectural innovation, not just bigger models.”
TII has a long-term commitment to talent development and technological sovereignty. The institute operates with international, multidisciplinary research teams, while embedding advanced capabilities into local ecosystems to support skills transfer. Initiatives such as joint research labs and global partnerships are designed not just to accelerate innovation, but to build sustainable national capabilities. “Our focus is on long-term capacity building, not short-term technology adoption,” she adds.
Looking ahead, TII plans to continue advancing Falcon through architectural innovation, improved robustness and responsible deployment. Future releases will be guided by efficiency, openness and real-world applicability. “Our direction is about building AI systems that are both globally competitive and practically useful,” explains Aaraj. “That means continued investment in applied research, efficiency-driven models and ethically governed innovation.”
As global AI development becomes more fragmented and politicised, TII’s approach offers a distinct alternative: open, language-native, efficient AI rooted in applied research. For the UAE, it represents not just technological progress but a statement of intent about its role in shaping the future of artificial intelligence.
