Intelligent farming: An AI opportunity in Africa


Stake: Understand the issues related to the development potential of the African agricultural sector through artificial intelligence and the challenges to be met to promote its deployment.

The Fourth Industrial Revolution will transform our lives in unprecedented ways. This revolution, which is characterised by the confluence of digital, physical, and biological systems, is slowly disrupting and redefining value chains across a multitude of industries, particularly through Artificial Intelligence (AI). One sector that demonstrates immense potential for AI applicability in Africa is the agricultural sector. 

As such, it is especially relevant to understand the implications of the implementation of AI solutions in farming and how they could respond to food insecurity, particularly given climate change among other factors.

From potential to deployment 

In a world increasingly prone to natural disasters resulting from climate change, if Africa does not devise methods to adapt its agricultural processes to climate change, it will likely face 22% yield losses by 2050 further accentuating the existing problem of food security. The AU also estimates that hunger costs African countries between 1.9% and 16.5% of their GDP. 

Yet, it is estimated that African food markets will be worth USD 1 trillion by 2030 up from the current USD 300 billion. The demand for food is likely to double by 2050, largely as a result of population growth, rising incomes, rapid urbanisation, changes in national diets, and more open intra-regional trade policies, all of which are helping create new opportunities for Africa’s farmers. 

Apart from concerns related to food security, it is also important to note that a majority of Africans are still heavily reliant on farming for their livelihoods, with agriculture accounting for 65% of employment and 35% of gross domestic product (GDP) on the continent. All of these structural gaps in the African agricultural sector present immense opportunities for the targeted application of AI powered solutions.

Various stakeholders on the continent are increasingly recognizing the transformative potential of AI technology. As a result, a number of solutions have begun to spring up across the continent. Among African startups leading this transformation are Zenvus, a Nigerian precision farming startup, and UjuziKilimo, a Kenyan big data analytics platform. Zenvus measures and analyzes soil data like temperature, nutrients, and vegetative health to help farmers apply the right fertilizer and optimally irrigate their farms. On the other hand, UjuziKilimo uses big data and analytic capabilities to transform farmers into a knowledge-based community, with the goal of improving productivity through precision insights. 

There is also potential to apply existing global models in Africa. Abdoulaye Baniré Diallo, Director of the Bioinformatics Lab at UQAM, as well as the co-founder and chief scientific officer of the MIMs startup, is working with advanced algorithms and machine learning methods to leverage genomic precision in livestock production models in thousands of farms. As Dr. Banire Diallo notes, the team he is leading, was able to design a successful model for the Canadian dairy industry, which if adequately implemented would add  200 million dollars per year to the sector. He is currently working on how this could be applied in selected countries in Africa. 

Overall, AI has the ability to mitigate issues arising from weak supply chains, low productivity, vulnerability to climate change, along with the insufficient financial resources on the continent, by improving productivity and efficiency at all of the stages of the agricultural value chain.

There are some challenges…

With such great potential, there are still many challenges in deploying AI solutions. These challenges undermine the growth of AI technology in regards to farming and other fields on the continent. These include poor digital infrastructure and including last mile infrastructure, lack of both basic tech literacy and the lack of substantial human capital trained in AI and data science etc. These are added on to lack of or the overregulation related to technologies like AI as well as the lack of funding to scale up successful pilots and demonstrations that would have a transformative impact in the agricultural sector although there are important projects by Morocco’s OCP Innovation Fund for Agriculture, a 20 million US dollar fund, as well as one acre fund and Agri Business Capital fund to name a few, which are  working to change this.

At the Next Einstein Forum, we believe it is urgent for African governments, development partners, the private sector, civil society and academic and scientific institutions to draft and ratify a continental strategic roadmap for leveraging new enabling technologies like AI. A roadmap that addresses basic and digital infrastructure gaps, funding, regulation and policy challenges, and talent and technology gaps. 

The funding challenge is not a small one. We estimate that Africa needs to collectively bring together more than 21 trillion US dollars until 2030 to fundamentally move into the fourth industrial revolution with $3 trillion US dollars of that spent on revitalizing the education system. Africans cannot just be consumers of AI technologies, they must be creators of these important technologies. Furthermore, it is predicted that the continent will require  a 73 billion US dollars investment to fulfil its agricultural promise.

This is only the first step. The next is targeted research, design and deployment approaches to leveraging AI in Africa. AI and machine learning relies mostly on statistical quantification making it an arduous task when applied in agriculture. Farming is a complex mix of physical and material processes, and thus requires a considerably large number of  variables. These physical and biological processes vary from one region to another, meaning that an algorithm for crop disease prediction in Rwanda, might prove obsolete in the Sahel region. 

Therefore, it is crucial to roll out targeted approaches to AI solutions in agriculture, in order to ensure that African innovators are able to design and produce relevant and efficient products. This can be achieved by orienting research towards the use of omics (genomics, metabolomics and phenomics) in tandem with AI to target early prediction based on observations not visible to the human eye. This would facilitate the design of transversal models adapted to the different African regions.

The way forward

Africa’s challenges related to agriculture offer a great opportunity for transformative innovation leveraging new technologies like AI. Multiple start ups on the continent are already working to close some of the gaps in the food production value chain, but much remains to be done. 

As such, a Pan-African roadmap is required to put in place mechanisms that will ensure that innovators are able to pilot their ideas all the way through industrialization in order for African countries to reap the full benefits of AI technology. 

To achieve the above, we need to devise a continental framework, which takes into consideration the financial, regulatory, the adequate training programs and political implications of implementing a successful AI strategy. 

Africa has a lot to gain, there is a projected 126 billion dollars to be made from industries relying on AI technologies globally.