(Graphic: John McCann/M&G)
Every year on 25 May, Africa Day is observed to celebrate the continent’s strength and rich cultural heritage. But it is also a day that reminds us how far we still have to go. Across Africa, many still face daily struggles with unemployment, poverty and inadequate access to basic services. Less visible, but just as urgent, is another kind of inequality: language.
As governments increasingly connect with citizens through digital platforms, millions are left out, partly because the technology does not speak their language.
Africa is home to more than 2 000 languages and a vibrant linguistic and cultural tradition, yet its civic tech infrastructure remains stubbornly monolingual. In a world where artificial intelligence (AI) and digital tools increasingly mediate civic engagement, leaving out African languages in these platforms is both a technical oversight and a governance failure.
Civic technology (civic tech) refers to digital tools used to promote citizen engagement, government transparency and public participation. From apps that track service delivery to platforms that allow people to report corruption and access public services, civic tech is important for participatory democracy. But what happens when the very people these tools are meant to serve and empower cannot understand them?
The reality is that most African civic tech platforms are designed in English or French, the languages of former colonial powers. This excludes most citizens who are more comfortable in indigenous languages such as Swahili, Yoruba or isiZulu. In most cases, English is the default interface language, even in countries where only a minority speak English fluently.
A key reason for this dominance is that English is the primary language of the internet, where most training data for language technologies used in digital tools comes from. Natural language processing (NLP), the AI subfield that allows machines to understand and generate human language, depends on large, annotated datasets. These are widely available for English but rarely for African languages, many of which are considered “low-resource”.
Tech developers often lack the training, tools or funding to build NLP models for these languages, especially when faced with the added complexity of dialectal variation, oral traditions and frequent code-switching.
Another reason is that civic tech initiatives and efforts are often concentrated in developed urban areas, where English tends to be the main language of communication. This creates a situation where digital governance tools are more responsive to elites and uphold old hierarchies.
The other barrier is institutional. In many cases, language inclusion is often an afterthought in civic tech development, with design decisions made by teams that do not consider the linguistic realities of the users they serve. This disconnect is worsened by the inadequacy of language policies or government mandates requiring digital platforms to support indigenous languages. As a result, civic tech ends up amplifying the voices of those already heard (urban, educated and English-speaking) while muting those on the margins.
Take South Africa, for instance. It has 11 official spoken languages and the highest number of civic tech initiatives on the continent. Yet, most government websites, mobile apps and AI-driven chatbots are English-only. This is partly a hangover from apartheid-era policies that relegating indigenous languages to the margins.
Post-apartheid reforms may have constitutionally elevated African languages, but digital systems have not caught up. Language inequity is being replicated in digital space, and this often results in diminished civic participation, poor service uptake and distrust in institutions.
These problems are worse in rural areas, where literacy in former colonial languages is low. In Kenya, for example, citizen feedback platforms like Ushahidi have struggled to reach monolingual Swahili speakers. In Nigeria, digital voting education tools often exclude Hausa, Igbo or Yoruba, creating information asymmetries in the democratic process. In Ethiopia, the dominance of Amharic-based civic systems means that minority language speakers in Oromia or Tigray are digitally disenfranchised.
There are growing efforts across the continent to localise AI and digital governance tools, and, equally, lessons to learn from these initiatives. The Masakhane project, for example, is a pan-African research initiative developing machine translation models for African languages. In Rwanda, Kinyarwanda-language platforms are being integrated into agriculture extension services, enabling farmers to get weather forecasts and pricing in real time.
Open-source solutions are also important. Projects such as Mozilla Common Voice have crowdsourced voice data in several African languages. These community-collected datasets can help train AI and language technologies to understand under-resourced languages, bypassing the expensive proprietary route.
As these efforts grow, so does the need to centre accessibility and inclusion from the very beginning of civic tech projects. Mark Renja, project manager at Code for Africa, explains that accessibility must be embedded from the planning stage. “Having accessibility as a central part of your thinking at every stage of a project, beginning with when you first start planning it, is critical. This way, you avoid a scenario where you have to go back and fix things you overlooked.” This foresight, Renja argues, allows teams to allocate resources early on and deliver tools that work for everyone.
Others in the civic tech space echo this view. “We are quick to condemn inaccessibility in the physical space because it is glaring, but we are making the digital space inaccessible because we think it doesn’t matter,” said journalist and advocate Blessing Oladunjoye.
Professor Mpho Primus, co-director of the Institute of AI Systems at the University of Johannesburg, argues that the rise of the Fifth Industrial Revolution (a shift focused on ethics, collaboration and human-centred AI) provides a key opportunity for change. She explains that this new paradigm corresponds with Africa’s pluralistic and multilingual societies, if we choose to embrace it.
She notes that integrating African languages into emerging technologies would not only help bridge the digital divide but could also position the continent as a leader in shaping ethical AI development. “The push toward human-centred AI requires linguistic inclusion to be at the forefront,” says Primus.
Importantly, there is a strong case for governments to mandate the inclusion of indigenous languages in all e-governance systems. This includes local language support in digital identity systems, chatbots, mobile apps and voting education platforms. Multilingual support should not be viewed as a “feature” but as a default standard, much like data protection or accessibility for persons with disabilities.
Donors and international development partners also have a role to play. Too often civic tech funding is tied to short-term performance metrics (number of users, clicks or reports filed) rather than long-term inclusivity. But trust is the foundation on which civic tech succeeds and delivers.
If marginalised communities do not trust the system or the institutions behind it, the technology will either fail or exacerbate inequalities. Language inclusion is one way to build that trust. A multilingual platform may be slower to scale in the short term, but it is more likely to foster trust, uptake, and resilience.
Funders must be willing to back projects that prioritise inclusion over convenience, invest in research that improves the quality and availability of language data and support programmes that connect technology, governance and language inclusion.
Finally, we must reframe language not as a barrier, but as an enabler. African languages are rich in nuance, metaphor and centuries of indigenous knowledge. When we include them in civic tech, we are making tools more accessible and meaningful. Imagine an AI tool that interprets a proverb-laden community feedback report in Tshivenda, or a chatbot that explains land tenure in Wolof using culturally grounded analogies. Those are the kind of tech that truly speaks to people.
As AI becomes central to everything from taxation to public service delivery, the cost of exclusion will grow. Civic tech needs to be built with more voices at the table, especially from communities that speak lesser-known or low-resource African languages. A digital state that cannot speak the language of its people is a state that cannot hear them either.
Nnaemeka Ohamadike is a senior data analyst at Good Governance Africa.