Ghana Must Prioritise AI Development in Its Local Languages

Students are already turning to AI to help explain difficult topics, businesses are using it to handle customer queries, health workers are exploring it for faster access to information, and governments are weighing how it could improve public services. Yet as this technology expands, access to it risks remaining unequal if AI systems cannot understand the languages most Ghanaians actually speak.

As artificial intelligence becomes embedded in daily life across Ghana, a pressing question has emerged: whether the AI systems Ghanaians use will serve those who speak local languages or only those comfortable in English.

The argument is not that English should be replaced. English continues to play an important role in education, business and public administration. The concern is that access to technology should not be conditional on a person's ability to communicate confidently in English. A farmer in a rural area may understand a crop problem fully but struggle to describe it in formal English. A market trader may find it far easier to ask about prices, loans or taxes in Twi or Ewe. An elderly person may grasp a health instruction better when it is delivered in their home language. In each of these situations, language determines whether technology is useful or alienating.

Languages such as Twi, Ewe, Ga, Dagbani and Fante are not merely tools for informal conversation. They carry history, humour, values, knowledge and identity. If new technology cannot work in these languages, a large share of Ghanaians will be sidelined from the digital future — an outcome that contradicts the goal of technology improving the lives of all citizens.

National Strategy and Existing Research

Ghana's recent policy direction has been described as encouraging in this regard. When the National Artificial Intelligence Strategy was launched in April 2026, the government stated that AI systems should reflect Ghanaian languages and cultural realities. That principle, it has been argued, must now move beyond policy documents and speeches and translate into real investment in local language data, research, voice technology, translation systems and practical tools for ordinary users.

There is already evidence of relevant work underway. Ghana Natural Language Processing, an open research community, has been building datasets, translation tools and speech systems for Ghanaian languages. Its Khaya project has supported translation work involving Twi, Ewe and Ga, among others. In August 2026, the group announced a speech dataset containing more than two thousand hours of recordings across 42 Ghanaian languages. Because AI systems learn from data, languages with little digital text or recorded speech are more difficult for modern systems to process. Building strong local datasets is therefore considered part of building national digital infrastructure, not a peripheral activity.

Education, Agriculture and Public Services

In education, local language AI could allow a pupil who struggles to grasp a concept in English to request an explanation in a familiar Ghanaian language. Teachers could develop learning materials for communities where children speak different first languages. Adult learners could use voice-based tools without requiring advanced typing skills. The Ministry of Communication, Digital Technology and Innovations has also pointed to potential benefits in agriculture, where a farmer could speak into a phone in Bono, Dagbani or Twi to describe a problem with a crop, ask about rainfall or seek market information, and receive a response in the same language.

In health care and public services, important information about disease prevention, pensions, taxes, business registration and social programmes becomes less accessible when citizens cannot readily understand it. Local language AI could support call centres, voice assistants and translation services that allow institutions to communicate with a broader public. A voice-based system also benefits people with limited literacy, enabling them to speak and listen rather than navigate lengthy written instructions.

Cultural Preservation and the Path Forward

There is also a cultural dimension to this issue. When younger generations rarely encounter their languages in digital or modern contexts, those languages can gradually weaken. If the digital world operates primarily in English, young people may come to associate Ghanaian languages only with home, market or traditional settings. When a language appears in apps, digital assistants, educational software and creative tools, it secures a place in contemporary life. Technology can therefore contribute to language preservation not only by storing words, but by keeping those words in active use.

Some may argue that Ghana has too many languages to support and that the cost of developing AI for them is prohibitive. Resources are finite and building complete systems for every language simultaneously would be unrealistic. However, the proposed response is not to ignore local languages, but to begin with the most widely spoken while creating open datasets and research methods that make it easier to incorporate others over time. Universities, technology companies, government agencies and language communities could collaborate, and open research could prevent institutions from having to begin from nothing.

Accuracy in these systems is also considered essential. A system that speaks Twi poorly or mistranslates a medical instruction can cause harm. Local language AI should therefore be developed with the involvement of teachers, linguists, native speakers, researchers and community groups, not only software engineers. Ghanaian languages contain dialects, expressions and cultural meanings that automated systems can easily misrepresent, and trustworthy tools will require careful testing and ongoing correction by those who use the languages daily.

Ghana faces a choice between waiting for foreign technology companies to decide which of its languages merit support, or treating those languages as central to the country's technological future. Depending entirely on imported systems may be practical in the short term, but it limits Ghana's control over what is represented, what is overlooked and whose experiences shape the technology. The case being made is that Ghana's ambition should extend beyond adopting the latest AI tools, to actively building tools that understand Ghanaians — in the languages they actually speak.