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Coding the Future: How the Adoption of Artificial Intelligence is Reshaping Africa
- THE GEOSTRATA
- 1 hour ago
- 5 min read
INTRODUCTION TO THE ADOPTION OF AI: AFRICA
Of the countless innovations made in the 20th and 21st centuries, Artificial Intelligence (AI) has emerged as one of the most transformative technologies of our era. What began as a mere computational tool has now evolved into a powerful driver of economic growth. The scope of AI has expanded immensely, with its applications now extending to automation, decision making, resource allocation, data organisation and analytics.
Illustration by The Geostrata
The technological revolution led by AI has now entered Africa. Integration of AI in industries, especially those of healthcare, finance, manufacturing, agriculture, and education have led to increased outputs with uncompromised efficiency. By ushering economic growth, improving access to quality education and healthcare, and promoting sustainable agriculture, AI is actively attempting to solve some of Africa’s most pressing challenges.
However, for a continent the size and population of Africa, the question is not whether the adoption of AI can reshape Africa; it is how Africa is planning to utilise AI to bring about a change, and what kind of change it is bringing. Another intriguing aspect one can ponder upon is how Africa is adopting AI in the face of many hurdles, be it the lack of digital infrastructure, funding, relevant technical skills, or research.
Through this article, we illustrate how AI is being adopted by Africa, along with the challenges that Africa is actively facing in the process.
LOCAL PROBLEMS, MODERN SOLUTIONS: ADOPTION OF AI THROUGH START-UPS, AND BUSINESSES
Presently, Africa is amidst a wave of innovation. With its AI ecosystem presently hosting over 2,400 companies specialising in the field of AI, it is being utilised efficiently by businesses and startups as a nifty way to address local and real-time problems with modern solutions. These startups are often driven by both domestic efforts and international collaborations. For instance, along with the many Africa-based startups, Google has also launched its first AI research centre in Ghana.
A prominent example of the adoption of AI in local startups is illustrated through Agrix Tech, a Cameroon-based startup. By leveraging AI, Agrix Tech assists farmers by helping them combat plant diseases and pests. It does so by enabling farmers to scan their leaves, after which the app notifies farmers of any ailments their plants might have. It further suggests required interventions, and can work in low internet connectivity. Hence, through creative adoption of AI, this startup identified a local challenge and proposed an efficient solution for the same.
Through the adoption of AI, tech hubs have emerged in Africa, namely Nigeria, South Africa, Kenya and Egypt. Named the ‘big four,’ they have the potential to generate an additional $126 billion in revenues through the adoption of AI. Startups in these locations, owing to their application of AI, large populations, and their growing economies, attract foreign investments as well. Google’s AI Research Centre in Ghana is an example of the same.
HOW IS THE ADOPTION OF AI DIFFERENT IN AFRICA?
If we were to compare the African AI Ecosystem and the version of Silicon Valley, we would notice that the difference is not in the mere definition of it, but rather it is embedded in the nature and structure of adopting AI mechanisms.
Unlike technology hubs such as Silicon Valley, where AI innovation often prioritises large-scale commercial models, African countries have chosen the route of diversifying the application of AI. Alongside its baseline adoption in startups, healthcare, agriculture, finance, and education are a few sectors which have begun utilizing AI in order to produce more effective and localised results.
This diversification allows every sector to utilize and adopt AI tools that are best suited to its needs and demands, instead of using a singular ‘one size fits all’ tool as a solution for all problems. AI adoption in Africa, unlike that in Silicon Valley, is not concerned with building multi-million dollar language models. Instead, it has driven its focus to building practical, application-driven tools tailored to local problems, which can be used by both African companies and ordinary citizens on a daily basis. Hence, AI adoption in Africa is concerned with accessibility over commercial gains.
Drawing from the utility of AI in problem-solving, Africa adopts AI tools which carry weightage in application, not just research. AI is deployed in sectors where it can effectively mitigate and solve problems which conventional or traditional methods cannot address. Be it through fraud detection in digital payments, crop advisory systems that guide farmers with satellite data, AI risk assessment for loans, AI-powered learning systems, or diagnostic tools which can be operated even in the absence of medical professionals, AI in Africa aims to address grassroots problems. Hence, the end goal of AI in African countries is fundamentally different from that of Silicon Valley, or any other country in the world.
These elements underscore the different nature of adoption of AI in Africa, but upon further observation, we realise that Africa’s AI tools are tailored in a way which enables the continent to have an AI ecosystem regardless of its infrastructural, financial, and skillset deficiencies. For instance, diagnostic tools leveraged by AI can assist many regions of Africa, as some regions do not have access to medical facilities or staff. Another example could be the aforementioned Agrix Tech. With most of Africa engaging in the agricultural sector, an AI tool of this kind enables farmers to spot ailments which are oftentimes not visible to the naked eye. This helps the farmer acquire better produce for sale. Although these tools make an attempt to bypass such hurdles, they are not always entirely successful.
CHALLENGES TO THE ADOPTION OF AI IN AFRICA
As illustrated thus far, Africa has begun adopting AI tools and mechanisms for an easier life. But, if it aspires to diversify more, or if it wishes to scale up and adopt AI in all countries of Africa instead of the ‘big four,’ there exist many hurdles it must overcome. To start with, Africa would require stronger digital infrastructure and internet connectivity. Only 37% of Africans have access to the internet, with many startups reporting downtime due to low connectivity and frequent blackouts. Both heavily impact the functioning of these models. AI requires data storage as well, but Africa cannot support the funding of such large data centres. For instance, nearly $200 million will be needed to build a Tier-3 data centre in Nigeria. The amount, along with the ROI deter private investments in such projects.
Hardware is outdated in many parts of Africa, and its procurement is riddled with high costs and tariffs. For instance, an AI lab in Ethiopia still relies on donated older-generation chips, limiting its performance drastically. The youth isn’t as trained in data sciences, machine learning, or AI engineering due to a lack of access to education for all. This leads to a shortage of AI talent as well. Lastly, and with immense weightage, is low investment and funding. African companies and startups barely accounted for 0.02% of the global total of $47 billion in 2025’s Q2 AI funding. This money is needed to foster research, deployment, development, and hence, adoption of AI initiatives. The lack thereof is a major barrier that AI adoption faces in Africa.
FUTURE OF AI
This strategic adoption of AI will support the economic growth of Africa. Regardless of the challenges it faces, it cannot be denied that the adoption of AI has proven to be beneficial to many sectors in Africa. With efficient planning and mapping of resources, and through collaboration with other states, AI can contribute to the continent’s GDP in trillions. With the advancement of AI even further, Africa has a chance to completely transform itself into an independent and self-reliant continent.
BY VIJAYLAXMI
TEAM GEOSTRATA