MBZUAI secures $1 million from Google.org to advance AI for Arabic and MENA languages

Funding backs research into low-resource language models, aiming to close the “data divide” in speech and language technologies across the Middle East and North Africa.

Mohamed bin Zayed University of Artificial Intelligence has received $1 million from Google.org to support research focused on improving AI systems for Arabic dialects and other underrepresented languages in the Middle East and North Africa.

The initiative, led by Thamar Solorio, Vice Provost of Faculty Excellence and Advancement and Professor of Natural Language Processing at MBZUAI, targets what the university describes as a persistent “data divide” in language technologies.

The funding is designed to address the imbalance in AI training data, which remains heavily concentrated on English and other high-resource Western languages. According to MBZUAI, this skew limits the accuracy and cultural nuance of AI systems when applied to Arabic dialects and minority languages across the MENA region.

In a LinkedIn post announcing the grant, MBZUAI stated that “Hundreds of millions of people across the region speak Arabic dialects and minority languages that are poorly supported by today's language and speech technologies.” The university added that the project will rethink how AI systems learn language, moving beyond approaches designed primarily for English.

Moving beyond adaptation

Solorio’s research aims to build a framework grounded in the sociocultural and linguistic realities of the MENA region rather than adapting models developed for Western contexts.

“This funding allows us to take our research from an early exploratory phase to a level that cannot only redefine the field, but lead to impact in people’s lives,” Solorio says. “This support is vital because it allows us to move beyond adaptation of high-resource models to linguistically grounded AI for MENA languages, which highlights a much-needed paradigm shift in the field.”

The initiative focuses on developing “resource-lean” AI systems. As large language models grow in scale and cost, the project aims to design training frameworks that require less manually annotated data and lower computational power. MBZUAI states that this approach is intended to make AI development more accessible to local institutions, startups, and researchers without extensive infrastructure.

Google collaboration and regional focus

To mark the announcement, Yossi Matias, Vice President at Google and Head of Google Research, visited the MBZUAI campus and met with President and University Professor Eric Xing. The collaboration forms part of what Google describes as the MENA AI Opportunity Initiative.

Matias says, “We are happy to collaborate with MBZUAI, which is deeply rooted in advancing AI research and fostering regional academic talent. By focusing on low-resource languages in Large Language Models, we are progressing on the MENA AI Opportunity Initiative’s commitment to providing access to the most innovative AI technology in Arabic, its dialects and other languages spoken in the region. Funding this research aligns with our goal to accelerate scientific discovery through cooperation that delivers real-world impact.”

MBZUAI indicates that the funding will also support postdoctoral and early-career researchers, positioning talent development as a central outcome of the project.

Implications for education and digital access

The anticipated applications extend beyond research. The university states that improved speech and language technologies could support education, accessibility, cultural preservation, and digital communication across the region.

For EdTech providers operating in Arabic-speaking markets, the initiative highlights a structural challenge: many AI-powered tools rely on models optimized for English. Addressing dialect diversity and minority languages requires targeted research rather than translation layers added after the fact.

As governments and institutions in the Gulf and wider MENA region invest in AI infrastructure, language inclusion is emerging as both a technical and policy priority. The question is not only whether AI can scale, but whether it can do so in ways that reflect linguistic and cultural realities across diverse communities.

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