Exploring Use Cases on How AI Delivers Impact in Africa

This article was originally published on GT Perspectives.

"AI holds immense potential to boost Africa's economy and to support the Sustainable Development Goals (SDGs) on the continent, says a report published by the GSMA, a UK-based organization that aims to unify the mobile ecosystem to discover, develop and deliver innovation foundational to positive business environments and societal change. With funding from the UK Foreign, Commonwealth and Development Office, the report's authors explain that "While AI is already being developed and deployed to support a range of use cases across African countries, little research has focused on building a body of evidence of AI use cases for development on the continent." They further explain that their "report is based on the analysis of over 90 use case applications identified in Kenya, Nigeria, and South Africa – which benefit from thriving tech ecosystems – across agriculture and food security, energy, and climate. While many AI use cases are relatively nascent, with some being deployed as part of projects or pilot schemes, a number of commercially viable solutions have also emerged. Often, AI is being incorporated into existing digital products and services, acting as an enabler to make digital solutions more relevant and efficient, amplify their impact, and facilitate scaling."

The report importantly points out that "The agritech sector is seeing most of the AI innovation, especially in Kenya and Nigeria where agriculture continues to play a significant role in the economy. AI is already being used for agricultural advisory, with companies like TomorrowNow and ThriveAgric providing farm-level insights to farmers, and for financial services with companies like Apollo Agriculture developing alternative credit assessment methods."

AI is also "being deployed in the energy sector, especially in Nigeria, where emerging technologies like Internet of Things (IoT) act as an entry point for advanced data analytics in smart energy management. Use cases such as energy access monitoring and productive use asset financing, developed by companies like Nithio, remain at a developing or nascent stage but present significant potential to reduce energy poverty. AI is also supporting climate use cases especially for biodiversity monitoring and wildlife protection in Kenya and South Africa, driven by large tech companies like Microsoft's AI for Good Lab and nonprofit organizations such as Rainforest Connection."

Regarding high-level recommendations, the report says different stakeholders – governments, development partners, development finance institutions (DFIs), non-governmental organizations (NGOs) and Civil Society Organizations (CSOs), large tech companies and startups, and research and academic institutions – "can take a number of actions and collaborate to ensure that impactful innovations in Africa can be deployed and scaled. This involves investing in domain-specific and local language data, adopting participatory approaches to data collection, unlocking access to existing data sources, and ensuring data privacy and security."

The report adds that "Strengthening baseline infrastructure and promoting renewable energy, providing hardware and cloud credits, enhancing edge computing capabilities and building institutional capacity will be essential to boost local compute capacity. In addition, fostering academic-industry collaboration, raising awareness and building capacity in the public sector will be essential to create a pipeline of AI talent while ensuring informed policymaking. To foster adoption and usage of AI-enabled services, enhancing digital skills among end users and integrating emerging skills like prompt-engineering into upskilling programs will be key, especially as generative AI solutions gradually grow in Africa."

Moreover, "Stakeholders across sectors can also focus on supporting the wider tech and AI ecosystem to foster an environment conducive to innovation and AI deployment across use cases. This involves engaging in partnerships to unlock access to critical resources for AI entrepreneurs and researchers, and to support the development of the AI ecosystem through data-sharing or infrastructure-sharing initiatives."

I concur with the authors that:

Adopting a consortium-based approach has the potential to help address the financing gap, while adopting innovative finance mechanisms can de-risk investments. Combining funding with technical assistance and go-to-market support can also help founders in their scaling journey. Increased R&D spending will be essential to support local research capacity, while local-global knowledge exchange can drive further momentum and raise awareness about local innovation. As countries work on developing national AI strategies, it will be critical to ensure a collaborative and inclusive process, to include principles for the ethical and safe use of AI, and to establish a clear roadmap for implementation. Policymakers can also consider rolling out regulations in a phased manner to allow innovation to flourish.

Do you agree with the recommendations on how different stakeholders can deploy and scale impactful AI innovations in Africa?

Aaron Rose is a board member, corporate advisor, and co-founder of great companies. He also serves as the editor of GT Perspectives, an online forum focused on turning perspective into opportunity.