Nigeria Begins Teaching AI to Speak Yoruba, Igbo, and Hausa Languages

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Tech Cabal reports that in a landmark move to cement its role as a continental AI powerhouse, Nigeria has unveiled an ambitious plan to build a multilingual large language model (LLM) that is fluent in its own indigenous languages. 

Announced by Dr. Bosun Tijani, the Minister of Communications, Innovation, and Digital Economy, at GITEX Nigeria in Abuja, the initiative represents one of the government’s most significant efforts to harness artificial intelligence for national development.

Diverging from mainstream AI models trained predominantly on English and other global languages, Nigeria’s homegrown LLM is being developed to understand and process five indigenous languages in addition to locally accented English. For a nation of over 200 million people speaking more than 500 languages, adapting AI to local contexts is not just a cultural imperative but a decisive strategic move.

The goal, according to Minister Tijani, is to ensure Nigeria is not left behind in the global race to develop foundational AI. “When I came in, I was extremely bullish about the fact that the only way for Nigeria would be to have our own foundational model,” he explained during a panel at GITEX. “We opted to kick off a large multilingual language model for the country, covering about five of our languages. We’ve done significantly well in collecting the data.”

The logic is compelling: tens of millions of people speak languages like Yoruba, Hausa, and Igbo, yet these tongues are virtually invisible to mainstream AI. By building a model that understands them, Nigeria aims to preserve its rich linguistic heritage while making technology radically more accessible and valuable for its citizens.

According to Business Day, this pioneering project is a collaborative effort, spearheaded by the National Information Technology Development Agency (NITDA) via its National Centre for Artificial Intelligence and Robotics (NCAIR). Key partners include the Lagos-based startup Awarri and the global technology non-profit, Data.Org.

Building a large-scale AI model is a monumental task, demanding profound scientific expertise, immense computing power, and sustained funding—a challenge that Tijani openly acknowledged. He said, “The truth is that leaders like me are struggling with the cost of building the required scientific know-how and the geopolitics around it.”

He cited India’s approach, developing local AI models while fostering community participation and external collaboration, as a potential blueprint. Nigeria, he suggested, might need a hybrid strategy that blends proprietary development with the power of open-source contributions.

This multilingual LLM is a cornerstone of Nigeria’s broader National AI Strategy, which has been in development since 2024. Professor Yinka David-West of Lagos Business School, a key strategist, explained that it is based on five pillars: robust infrastructure, ecosystem development, widespread adoption, responsible frameworks, and effective governance.

A central component of this strategy is the AI Collective, a powerful coalition uniting academia, civil society, and industry. Under this framework, Lagos Business School is spearheading research, the Centre for Justice and Legal Development (CJLD) is engaging civil society, and Data Science Nigeria is nurturing the startup and technical community.

“The AI Collective is really looking at building out the ecosystem,” said David-West. “Because when you think about the ecosystem, academia is part of it, industry is part of it, and talent and startups are part of it. 

Education lies at the heart of this ambitious vision. The nation’s Three Million Technical Talent (3MTT) programme is channelling thousands of its fellows into the AI initiative. The LLM project will directly involve over 7,000 participants, who will simultaneously build a talent pipeline and gain invaluable hands-on experience.

The educational push extends to the public sector, where Lagos Business School has been conducting workshops for government officials on AI ethics, intellectual property, and practical applications in governance. David-West emphasised that the governance environment will remain limited if we fail to educate the public sector.

The LLM project has secured an initial $3.5 million in seed funding from a consortium of international and local partners, including the UNDP, UNESCO, Meta, Google, and Microsoft. However, the minister is pragmatic about the long-term financial needs, admitting that relying solely on donor funding is unsustainable. “For the government to actually invest millions of dollars in those things, where is the money going to come from? That’s the conflict we need to handle,” he stated.

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Ultimately, the project’s success will be measured by its real-world social impact. An AI that understands indigenous languages could revolutionise education, allowing rural students to learn in their mother tongue, and empowering traders and artisans to access digital finance tools in dialects they understand. As Professor David-West envisioned, “If that mother speaks only one native dialect and the homework is in English, it doesn’t mean she doesn’t comprehend. With AI, we can bridge those gaps.”

While still in its early days, Nigeria’s multilingual LLM has the potential to become a template for other African nations facing similar linguistic diversity and developmental challenges. The stakes, as Tijani highlighted at GITEX, are immense.

“AI is not just another startup frenzy. It’s about resources, research, and how we make it work for us,” he concluded. “Balancing the global and the local—that is the challenge every nation must face.”

The development of an indigenous language LLM in Nigeria could be a game-changer for its tourism sector and provide a powerful model for the rest of Africa. International and domestic tourists, particularly from the diaspora, could interact with AI-powered chatbots, virtual guides, and tourism apps in their native Nigerian languages (e.g., Yoruba, Igbo). This fosters a more profound cultural connection and makes travel more accessible.

The LLM can also power real-time translation tools that break down language barriers. A foreign tourist could speak English into an app, have it translated into contextually accurate Hausa for a market vendor in Kano, and understand the vendor’s reply in their own language, drastically improving interactions and commerce.

AI can be used to digitise and create interactive experiences around Nigeria’s rich folklore, history, and traditions in their original languages. Museums and cultural sites could offer immersive AI-driven exhibits that tell stories in the very languages in which they were first told.

 

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FAQs

1. What is Nigeria’s large multilingual language model (LLM)?

It is an artificial intelligence program being specifically trained to understand, process, and generate text in several of Nigeria’s indigenous languages, like Yoruba, Hausa, and Igbo, in addition to accented English.

2. Who is leading this AI project?

The initiative is led by Nigeria’s Ministry of Communications, Innovation, and Digital Economy. The development is being handled by the National Information Technology Development Agency (NITDA), in collaboration with partners like the AI startup Awarri and the global non-profit Data.Org.

3. How is the project being funded?

It has secured an initial $3.5 million in seed funding from a mix of local and international partners, including UNDP, UNESCO, Meta, Google, and Microsoft.

4. Why is building an AI for local languages important?

It makes technology more accessible and useful for millions of citizens who do not speak English as their first language. It also helps preserve cultural and linguistic heritage and ensures that the benefits of AI are relevant to local contexts in areas like education, healthcare, and commerce.

5. Could this model be used in other African countries?

Yes. Nigeria’s project could serve as a blueprint or template for other African nations to develop similar AI models for their own diverse languages, fostering a more inclusive and locally relevant technological landscape across the continent.