According to the literature AI is rapidly evolv- ing as a key technological driver in Africa, ush- ering the continent into a new era of innovation and digital transformation (Okolo, Aruleba, and Obaido 2023). The adoption of AI across the di- verse landscapes of African countries showcases a commitment to leveraging technology to ad- dress both longstanding and emerging challeng- es (No et al. 2021). Among the core elements of AI are algorithmically controlled automated deci- sion-making (ADM) systems, or decision support systems, which are social technological frame- works that comprise decision-making models and the algorithms that translate the models into computable codes (Hofmann 2021; Authur Gwagwa et al. 2020; Fuster 2020; Centre for Re- sponsible Business Conduct in the Directorate for Financial and Enterprise Affairs 2019). In the African context, ADM systems are being used to improve efficiency, support evidence-based poli- cymaking, and address humanity’s most pressing issues which include a better-educated society, a more productive continent, less hungry nations, healthier populations and a society better placed 02 Literature Review
to tackle the effects of climate change (Authur Gwagwa et al. 2020). AI is being used across the continent to address needs and gaps in educa- tion, agriculture, health, fintech, climate change, public transport, logistics, enterprise develop- ment, and language translation, accelerating Afri- ca’s capacity to achieve UN sustainable develop- ment goals, 2030 (Hofmann 2021). For example, according to (Sedola, Pescino, and Greene 2021), a total investment of approximately $ 2.02 billion has been made towards the promotion and ac- celeration of AI activities in Africa. This has had an impact in sectors such as Agriculture, Education, Manufacturing, Banking & Finance, Healthcare, and Marketing. The education sector recorded the highest impact with a total of 216 entities, healthcare with 114 entities, and agriculture and manufacturing sectors recorded the lowest with approximately 53 entities. However, there was not enough data for some other countries in West, Central, and East Africa such as Ghana, Central African Republic, and Kenya to conclude that the agriculture and manufacturing sectors have the lowest AI adoption since most African countries
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