The adoption of Artificial Intelligence (AI) in Kenya is predominantly focused on the agricultural sector, with machine learning technologies being utilized to provide data-driven insights that enhance productivity for local farmers. The ‘AI for Africa’ report by the Global System for Mobile Communications Association (GSMA) reveals that agriculture and food security account for 49 percent of all AI applications in Kenya, followed by climate action and energy use cases at 26 percent and 24 percent, respectively.
The report highlights that predictive AI is the most common use case due to factors such as the availability of historical data, ease of application, and lower computational needs compared to generative AI models. In agriculture, AI is being used for advisory services and alternative credit assessments, exemplified by companies like Apollo Agriculture which are innovating in agricultural finance.
Microsoft’s AI for Good Lab has contributed by developing a spatiotemporal machine learning model to identify malnutrition hotspots, facilitating timely interventions. This model aims to mitigate the impact of malnutrition among vulnerable populations, showcasing the potential of AI in addressing critical health issues.
Investment in local data centers by major tech firms and Mobile Network Operators (MNOs) is driving AI momentum by providing essential storage and computing resources. Despite this progress, the report points out significant infrastructure challenges, including power outages and high costs of hardware like GPUs, which hinder broader AI adoption and deepen the digital divide.
The report also notes a significant skills gap in the AI sector, with universities struggling to align their curriculum with industry needs. The high cost of GPUs in Kenya, which is 31 times more expensive than in high-income countries, and a lack of practical learning opportunities for students are major barriers to AI development.
Deep tech startup Fastagger is addressing these challenges by creating software infrastructure that enables machine learning and AI models to run on edge devices, including lower-end smartphones. This innovation aims to make AI more accessible and practical for local entrepreneurs and researchers.
ArtificialIntelligence #KenyaAI #AgricultureTech #MachineLearning #DigitalDivide #TechInnovation #DataCenters #AIChallenges #TechForGood #KenyaTech
