By Benedicta Etafo
In 2022, Generative AI (GenAI) exploded into public consciousness, capturing imaginations with chatbots that could write poems, design logos, and explain quantum physics in plain English. For months, it felt like a Silicon Valley fever dream when underpinned by the hype, headlines, and hallucinations.
But in 2024 and now 2025, the conversation is shifting. Across Africa, GenAI is not just a novelty or an imported luxury. It is becoming a practical tool that is disrupting, accelerating, and in some cases, leapfrogging entire processes in key industries. Beyond the buzzwords and entrepreneurs/investor proposals, GenAI is solving real “African problems”.
This article explores the pragmatic application of GenAI across sectors like agriculture, education, finance, healthcare, and governance, highlighting African-led innovation, locally tuned solutions, and the promise of a more inclusive AI-powered future.
Agriculture: Precision support for smallholder farmers
The agricultural sector in Africa, dominated by smallholder farmers, has long struggled with low yields, inadequate access to information, and volatile climate patterns. However, in recent times, the capabilities provided by GenAI are increasingly being unleashed with the piloting of newly developed tools that offer a wide range of hyper-local, language-friendly possibilities.
AgriTech startups like UjuziKilimo in Kenya and Zenvus in Nigeria are incorporating AI to analyze soil data, weather patterns, and historical crop outcomes. GenAI models are being leveraged by these platforms to generate real-time planting schedules, pest management strategies, and even market forecasts, which are all translated into local dialects via voice bots or SMS.
The result: Farmers no longer rely solely on anecdotal advice or inaccessible government extension services. With the adoption of GenAI, farmers can now receive tailored, data-driven guidance in languages and preferred communication channel. A first for most of the farmers.
Education: Scaling personalised learning at low cost
Across the continent, especially in areas with high student-to-teacher ratios and uneven curriculum coverage, GenAI is proving to be an unexpected equaliser.
Platforms like uLesson and M-Shule are beginning to explore how LLMs (Large Language Models) can offer personalised tutoring in core subjects like mathematics and science. For underserved students, AI-driven chatbots can explain concepts in multiple languages, provide interactive exercises, and offer on-demand homework help.
In South Africa, a pilot project is testing a GenAI assistant trained on the national curriculum. Currently, teachers report that it’s helping bridge gaps for learners in rural areas, allowing students to progress at their own pace, even with limited internet connectivity.
It is critical to emphasise that the role of the human teacher remains central to delivering learning outcomes to students. However, GenAI is augmenting their reach, acting as a scalable classroom assistant, not a replacement.
Financial services: Streamlining access and combating fraud
The fintech boom in Africa has created a vibrant financial ecosystem, which, along with its numerous positives, has also brought to the fore a couple of challenges, such as fraud, onboarding delays, and customer support challenges due to the explosive scale of service users and subscribers across the various offered products and services.
GenAI is helping on multiple fronts to provide scalable, cost-effective, and efficient capabilities to address these challenges such as evident in examples below:
- Customer service automation: Banks like UBA and fintechs like Flutterwave are testing GenAI-powered chatbots for Tier-1 support, significantly reducing call center traffic, customer wait times, and improving overall customer experience.
- Fraud fetection: Generative Adversarial Networks (GANs) are increasingly being explored to simulate attack patterns, allowing financial institutions to proactively train models against emerging and continually evolving fraud tactics and techniques.
- Credit scoring: For the unbanked and underbanked, GenAI is providing capabilities for synthesising alternative data (like mobile usage patterns) to generate more inclusive credit profiles, potentially bringing millions into the formal financial system.
The key here is adaptability. While these capabilities are still in their early phases of development and adoption, they are already providing significant value and promise, which is driving even more research into their adoption for more use cases while continually optimising developments for existing solutions to covered use cases. GenAI models are being fine-tuned with local languages, user behaviours, and regulatory compliance frameworks, making them useful and trustworthy.
Healthcare: Bridging the diagnostic divide
Africa faces a stark shortage of healthcare professionals driven by several factors, including the cost of training professionals, recent heightened human capital flight of skilled healthcare professionals to Western countries, among others. GenAI offers an opportunity to address some of these gaps not with robots, but by providing augmentative tools and solutions that provide effective support for overburdened clinicians.
In Rwanda and Ghana, health startups are experimenting with AI systems that summarise patient notes, suggest differential diagnoses, or translate medical literature into local contexts. For example, a midwife in a rural clinic could describe symptoms in Kiswahili and receive a risk analysis in seconds, cross-checked against WHO guidelines.
HealthTech solutions like BenevolentAI and mPharma, are exploring the use of GenAI in pharmaceutical supply chain management and predictive diagnostics, ensuring that essential medicines are both in stock and appropriately prescribed.
Privacy and data security remain critical, especially as there are currently no developed frameworks/regulations across Africa at both national and regional levels providing comprehensive guidelines on AI governance. With the right guardrails, GenAI can dramatically enhance diagnostic capacity and clinical decision-making.
5. Governance and civic engagement: Making sense of policy
GenAI is also being used in an unlikely arena, “Government transparency”.
Civic tech organisations like BudgIT in Nigeria are exploring the use of GenAI to summarise budget documents and legislation, turning dense public data into plain-English narratives. Their aim being to empower everyday citizens to engage with how their taxes and revenues are spent.
In Kenya, a GenAI chatbot trained on constitutional law is being trialed to support paralegals and community members with legal queries, especially in underserved communities with limited access to legal professionals.
This represents a quiet revolution in democratic participation. Where language, jargon, and bureaucracy have historically been barriers, GenAI could serve as a translator, explainer, simplifier, and an enabler.
The challenges: Infrastructure, data, and equity
Certainly, like every disruptor, GenAI is not a silver bullet. While it provides numerous opportunities and benefits such as those highlighted, several challenges remain that need to be carefully considered:
- Data Quality: Many GenAI tools require vast, clean datasets, which are often unavailable or siloed in African contexts.
- Connectivity: Despite progress, rural and low-income users may still be faced with limited or no access to consistent internet, limiting the reach of these AI-powered solutions.
- Bias and Localisation: Many foundational models are trained predominantly on Western datasets. Without retraining, they risk encoding irrelevant assumptions or biases.
- Policy and Ethics: Regulation around GenAI is still nascent across the continent. There’s an urgent need for homegrown frameworks that safeguard privacy while fostering innovation.
Conclusion: Africa’s GenAI moment is here
The story of GenAI in Africa is no longer theoretical or aspirational. It’s unfolding now, in classrooms, clinics, farms, and boardrooms. It’s not about replacing humans, but augmenting humans by amplifying what’s possible with the right tools, local insight, and contextual intelligence to tackle pertinent problems at scale and with improved precision.
As African entrepreneurs, policymakers, and communities continue to adapt GenAI to solve problems that matter, they are helping reshape global narratives not as passive recipients of technology, but as innovators, architects, and co-creators of world-class solutions with contextual relevance to addressing local problem statements.
GenAI’s future on the continent depends on collaboration across sectors, languages, and through inclusive design. The potential is real. The impact is growing. And the hype? It’s finally giving way to substance.
