African Languages in Tech: Coding the Future in Swahili and Yoruba

African Languages in Tech: Coding the Future in Swahili and Yoruba

Ask ChatGPT a complex question in Hausa.

Watch it fail.

Try having a conversation with Alexa in Yoruba.

Silence.

Search for medical information in Amharic online.

Good luck finding anything useful.

Africa is home to over 2,000 languages—roughly one-third of the world's linguistic diversity. Yet in the digital world, these languages barely exist.

Less than 0.1% of websites have content in any African language. When Africans go online, they must often do so in English, French, or Portuguese—languages that hundreds of millions don't speak fluently.

But that's changing. African developers, linguists, and AI researchers are building technology that speaks African languages. And they're doing it themselves.

The Digital Language Gap

The Numbers

The internet was built in English, and it shows:

More websites exist in Norwegian (5 million speakers) than in Swahili (200 million speakers).

This isn't an accident. It's the result of who built the internet, where investment flows, and whose languages are considered "valuable."

What This Means in Practice

Healthcare:

A mother in rural Kenya searching for information about childhood fever finds results in English—a language she may not read fluently. Life-or-death information is locked behind a language barrier.

Education:

Students across Africa learn in colonial languages they don't speak at home. They must master foreign grammar before they can master physics.

Commerce:

Small business owners can't use sophisticated digital tools because they don't exist in their languages.

AI exclusion:

When you speak to an AI assistant in Igbo, Zulu, or Amharic, the response is often nonsense. These languages weren't in the training data.

The digital divide isn't just about who has internet access—it's about who the internet was built for.

Why African Languages Were Left Out

The Data Problem

Modern AI systems learn from data. The more text in a language, the better the AI performs.

English has:

• Billions of web pages

• Millions of books digitized

• Decades of newspaper archives online

• Massive social media corpora

African languages have:

• Limited written traditions (many are primarily oral)

• Few digitized books and documents

• Minimal web presence

• Sparse social media text in formal language

Training a decent language model requires approximately one terabyte of text data—roughly one million sentences. Most African languages don't have anywhere near this amount of digitized content.

The Investment Problem

Big Tech companies—Google, Meta, Microsoft, OpenAI—allocate resources based on market size and revenue potential.

The logic: Why invest in Yoruba (45 million speakers, mostly in Nigeria) when you could improve Spanish (550 million speakers, across wealthy markets)?

The result: African languages are perpetually deprioritized.

The Colonial Hangover

Colonial education systems taught that African languages were inferior—suitable for the village, not for science or technology.

This attitude persists. Governments often neglect African language education. Parents push children toward English or French. The languages themselves are associated with poverty and backwardness.

Breaking this cycle requires proving that African languages belong in the digital future.

The Pioneers Fighting Back

Masakhane: "We Build Together"

Masakhane (isiZulu for "we build together") is a grassroots movement that's transforming African language technology.

What it is:

• Pan-African natural language processing (NLP) research community

• Over 1,000 contributors from across Africa and the diaspora

• 35+ active core contributors

• Open-source, volunteer-driven

What they've built:

• Machine translation models for dozens of African languages

• Datasets for training AI systems

• Research papers advancing the field

• A community of African AI researchers

Languages covered:

Swahili, Yoruba, Hausa, Igbo, Amharic, Zulu, Xhosa, Twi, Luganda, Kinyarwanda, Somali, Tigrinya, and many more.

Masakhane proved that Africans could build world-class AI without waiting for Big Tech to care.

Lelapa AI: Africa's First Multilingual LLM

In 2024, South African company Lelapa AI launched InkubaLM—Africa's first multilingual large language model built specifically for African languages.

Languages supported:

• Swahili

• Yoruba

• Hausa

• isiZulu

• isiXhosa

What makes it special:

• Only 0.4 billion parameters (compact by industry standards)

• Performs comparably to much larger models on African language tasks

• Designed for Africa's infrastructure constraints

• Open access for researchers and developers

CEO Pelonomi Moiloa explained the mission: "No one should have to adopt a foreign culture to access cutting-edge tools."

The model is named after the dung beetle (inkuba in Zulu)—small but remarkably strong.

Ghana NLP: Volunteer-Powered Translation

Ghana NLP is an open-source initiative building language technology for Ghanaian languages.

Their app, Khaya, offers:

• Automatic speech recognition in Twi, Ga, and Dagbani

• Expanding to Ewe and other Ghanaian languages

• Also supports Yoruba, Kikuyu, and Luo

How they get data:

Since limited text exists online, Ghana NLP works with communities:

• Wikipedia editors in Dagbani contribute audio recordings

• Bible translations provide initial text corpora

• Volunteer speakers donate voice data

Felix Akwerh, a machine learning engineer with Ghana NLP, sees use cases in:

• Hospitals where doctors and patients speak different languages

• Courts where translators are scarce

• Schools where instruction could happen in mother tongues

The entire project is volunteer-led. No Big Tech budget. Just Africans solving African problems.

Nigerian Government LLM Initiative

In 2024, the Nigerian government partnered with AI startups to build a national multilingual language model.

Target languages:

• Yoruba

• Hausa

• Igbo

• Ibibio

• Nigerian Pidgin

The approach:

• 7,000+ fellows from Nigeria's tech talent program collecting data

• Local volunteers fluent in target languages

• Partnerships with startups like Awarri

Silas Adekunle, co-founder of Awarri: "We have so many different accents and languages, and this will enable many people and developers to build products that leverage AI but are for the Nigerian market."

This is what sovereignty in tech looks like: building your own AI infrastructure rather than waiting for Silicon Valley.

2025: African AI Products That Speak Local

African developers aren't just building research projects—they're shipping products.

YarnGPT: Video Dubbing in African Languages

Built by Nigerian AI engineer Saheed Azeez, YarnGPT lets creators dub English videos into Yoruba, Igbo, and Hausa—sounding natural, not robotic.

How it works:

• Text-to-speech models trained on locally sourced voice data

• Voice-overs sound familiar, with correct local cadence

• Use cases in media, education, and accessibility

A YouTube cooking video in English can become a Yoruba tutorial in minutes.

Indigenius: 180+ African Languages

CDIAL AI built Indigenius to support over 180 African languages and dialects.

Features:

• Predictive multilingual typing

• Speech-to-text

• No-code voice agent APIs

• Support for Hausa, Igbo, Yoruba, Pidgin, and many more

For the first time, an African small business can build a customer service chatbot that speaks Pidgin.

Xara: WhatsApp Banking in Nigerian Languages

Xara is a WhatsApp-based AI banking assistant launched in 2025.

What it does:

• Send money, pay bills, track spending via WhatsApp

• Understands Nigerian speech patterns and Pidgin

• Plans to add Hausa and Yoruba

Users can type "Send ₦5,000 to Chioma for breakfast" in natural language—no app navigation required.

UlizaLlama: Maternal Health in Swahili

Kenyan foundation Jacaranda Health developed UlizaLlama to support expectant mothers with AI-driven health advice in Swahili.

Why it matters:

• Maternal mortality remains high in East Africa

• Medical information is often only available in English

• Culturally appropriate AI can save lives

Terp 360: Sign Language Translation

This Kenyan app translates English and Swahili into Kenyan Sign Language in real time using AI and 3D avatars.

Sign language speakers across Africa have been almost entirely excluded from the digital revolution. Terp 360 is changing that.

Gebeya Dala: Code in Swahili, Hausa, Amharic

Ethiopian company Gebeya's Gebeya Dala lets users describe apps they want in plain language—including Swahili, Hausa, Amharic, and Arabic—and generates working code.

A farmer can describe "an app to track local crop prices" in Amharic and get a functional application.

The Challenges Remaining

Data Scarcity

Most African languages still lack:

• Large digitized text collections

• Standardized orthographies (spelling systems)

• Audio datasets for speech recognition

Building this data requires massive community effort.

Infrastructure

AI models need computing power. Africa has:

• Limited data centers

• Expensive cloud computing

• Unreliable electricity

Lelapa AI designed InkubaLM to be compact specifically because African developers can't access the same compute resources as Google or OpenAI.

Funding

Global AI investment flows to US, China, and Europe. African language AI projects survive on:

• Grants from foundations

• Volunteer labor

• Occasional Big Tech crumbs

The Nigerian government initiative is notable precisely because government-backed AI projects for African languages are rare.

Standardization

Many African languages have:

• Multiple dialects

• Varying written forms

• Tone systems that are hard to represent digitally

Should AI learn "proper" Yoruba or the version young people speak on Twitter? These questions have no easy answers.

What's at Stake

Language Death

UNESCO estimates that 50-90% of the world's languages could disappear by 2100.

Languages without digital presence are especially vulnerable. If your children can't use their mother tongue online, on their phones, in school—why would they pass it on?

Digital inclusion isn't just convenient. It's existential for thousands of languages.

Economic Exclusion

The global digital economy—worth trillions—largely operates in English.

If African languages remain locked out:

• African markets remain underserved

• African workers can't access global opportunities

• African innovation stays local

Conversely, if Nigerian Pidgin works with AI assistants:

• 100+ million speakers gain digital access

• Businesses can serve customers in their language

• New markets open

AI Colonialism

Right now, when Africans use AI, they use tools trained on Western data, reflecting Western perspectives, in Western languages.

This is a form of cognitive colonialism—the AI that shapes how you think was built by people who don't understand your context.

African language AI built by Africans means:

• Cultural context preserved

• Local knowledge valued

• African perspectives embedded in technology

How to Support African Language Tech

If You're a Developer

Contribute to open-source projects:

• Masakhane (machine translation)

• Ghana NLP (speech recognition)

• Mozilla Common Voice (voice data collection)

Build in African languages:

• Even if imperfect, more content in African languages helps

• Localize your apps

If You're a Speaker

Donate your voice:

• Mozilla Common Voice collects recordings for AI training

• Ghana NLP and others need volunteers

Create content:

• Write Wikipedia articles in your language

• Blog, tweet, post in African languages

• Every sentence helps train future AI

If You Have Resources

Fund African AI research:

• Masakhane needs compute resources

• Startups like Lelapa AI need investment

• University programs need support

Demand African language support:

• Pressure Big Tech to support more African languages

• Prioritize products that speak your language

The Future

A decade ago, African language technology barely existed. Today:

• Africa's first multilingual LLM is live (InkubaLM)

• Products are shipping in Yoruba, Swahili, Hausa, and Pidgin

• Governments are investing in national language AI

• A vibrant research community exists (Masakhane)

The goal isn't just to catch up to English—it's to build technology that reflects African realities from the ground up.

Pelonomi Moiloa of Lelapa AI put it simply:

"No one should have to adopt a foreign culture to access cutting-edge tools."

Imagine AI that understands Igbo proverbs. Voice assistants that speak proper Twi. Medical chatbots in Amharic. Banking apps in Pidgin. Educational tools in Zulu.

That future is being built now—by Africans, for Africans, in African languages.

The colonial internet was built in English.

The African internet will be built in 2,000 tongues.

Key Statistics

African Language AI Projects

FAQ: African Languages in Tech

1. Why are African languages underrepresented in tech?

Limited digitized text data, low investment from Big Tech, colonial educational legacies that devalued African languages, and the internet's English-first development.

2. What is Masakhane?

A Pan-African NLP research community with over 1,000 contributors building machine translation and other language tools for African languages. The name means "we build together" in isiZulu.

3. What is InkubaLM?

Africa's first multilingual large language model, built by Lelapa AI, supporting Swahili, Yoruba, Hausa, isiZulu, and isiXhosa.

4. How many speakers does Swahili have?

Approximately 200 million, including native and second-language speakers across East Africa.

5. Why can't existing AI systems handle African languages?

They were trained primarily on English text. African languages weren't included in training data because little digitized text exists online.

6. How can I help?

Donate voice recordings to Mozilla Common Voice, write Wikipedia articles in your language, create content in African languages, or contribute to open-source projects like Masakhane.

7. What is Ghana NLP?

A volunteer-driven initiative building speech recognition and other language tools for Ghanaian languages like Twi, Ga, and Dagbani.

8. Are any governments investing in African language AI?

Yes. Nigeria has launched an initiative to build a national multilingual language model covering Yoruba, Hausa, Igbo, Ibibio, and Pidgin.

9. What's the risk if African languages stay out of tech?

Language death (50-90% of languages may disappear by 2100), economic exclusion, and AI systems that don't reflect African cultures or perspectives.

10. Can I use AI in Yoruba or Swahili today?

Yes, increasingly. Products like InkubaLM, Khaya, YarnGPT, and Indigenius support multiple African languages. Quality varies but is improving rapidly.

Sources

• Masakhane NLP

• Lelapa AI

• Ghana NLP

• Mozilla Common Voice

• TechCabal

• Techpoint Africa

• W3Techs Language Statistics

• CNBC Africa

• Nature Middle East

• Princeton Africa World Initiative