Across Africa, a new wave of startups is emerging in the artificial intelligence (AI) space, developing locally relevant solutions that address the continent’s unique challenges while asserting greater control over data and digital infrastructure.
From Nairobi to Lagos and Johannesburg, entrepreneurs are leveraging open-source AI models to build applications tailored to local environments. These efforts aim to reduce reliance on dominant global players—primarily large technology firms in the United States and China—while promoting data sovereignty and technological independence.
According to Toffene Kama of Mercy Corps Ventures, the future of AI will include not only large, global models but also smaller, highly specialised systems designed to solve specific problems more efficiently. These “micro-models” are particularly suited to Africa’s needs, where infrastructure constraints often demand lightweight and adaptable solutions.
Localised Innovation Driving Impact
African AI startups are focusing on practical applications across key sectors such as healthcare, agriculture, and financial services.
In Kenya, Jacaranda Health uses AI-powered SMS tools to deliver maternal and postnatal healthcare information to women, even in low-connectivity environments. Meanwhile, Senegal-based Tolbi leverages weather data analytics to support farmers in improving crop yields and adapting to climate variability.
AI is also expanding access to financial services, enabling underserved populations to access credit, insurance, and other essential tools that were previously out of reach.
These developments are being actively discussed by policymakers and investors at forums such as the Africa Forward Summit in Nairobi, where stakeholders are examining both the opportunities and risks associated with rapid AI adoption.
Mike Mompi of Enza Capital emphasised that Africa remains well-positioned to build its own AI ecosystem despite global competition. He noted that while advanced technologies have been developed elsewhere, there is significant scope for Africa to innovate around local use cases.
Data Sovereignty and Policy Concerns
The importance of local data governance has been underscored by recent policy developments. In Kenya, a high court ruling suspended a major health data agreement with the United States over concerns related to data protection and sovereignty. Similar concerns have prompted governments in Ghana and Zambia to reconsider comparable arrangements.
These developments highlight the growing recognition that control over data is central to both national security and economic development in the AI era.
Despite these concerns, public sentiment toward AI remains largely positive across parts of Africa. Surveys indicate that populations in countries such as Nigeria and Kenya are more optimistic about AI’s potential benefits compared to their counterparts in many Western nations, where skepticism is increasing.
AI for Development and Inclusion
Many African AI solutions are specifically designed to operate in low-resource environments, where access to reliable electricity, internet connectivity, and computing power may be limited.
Organisations such as Digital Green have introduced tools like FarmerChat, enabling farmers to access agricultural advice in local languages via messaging platforms. Similarly, Kenya-based Cliniva integrates AI chatbots into healthcare delivery, improving access for underserved populations.
However, industry stakeholders caution that global AI models often fail to reflect African realities. Yulia Sidorova noted that AI systems trained on non-African datasets may produce inaccurate or even harmful outcomes when applied in local contexts, particularly in sensitive areas such as maternal healthcare.
Building the AI Infrastructure Stack
While early efforts have focused on applications, a second wave of innovation is targeting the underlying infrastructure required to support AI ecosystems. This includes investments in data centres, language models, and structured datasets.
Initiatives such as Masakhane and companies like Lelapa AI are working to develop language models that incorporate African languages, including Swahili, Yoruba, Hausa, and isiZulu, collectively spoken by hundreds of millions of people.
Global organisations such as The Rockefeller Foundation are also supporting efforts to build local datasets, recognising that data availability is essential for both AI development and investment.
Strategic Importance for Africa’s Future
Experts warn that without active participation in AI development, Africa risks becoming a passive consumer of technologies built elsewhere, potentially reinforcing existing patterns of economic extraction.
Companies such as Hakimu are addressing this challenge by developing AI tools trained on African-specific data, including legal records, to improve efficiency and access to services.
According to industry leaders, building a robust, inclusive AI ecosystem in Africa will require coordinated efforts across policy, investment, infrastructure, and innovation. However, the current trajectory suggests that the continent is not only adopting AI but actively shaping its evolution in ways that reflect local priorities and realities.
