Right now, many of Africa’s leaders have pledged to accelerate the adoption of AI and GenAI.
Earlier this month, more than 2,000 policymakers and business leaders from nearly 100 nations gathered in Kigali, Rwanda, for Africa’s first Global AI Summit.
The outcome was the Africa Declaration on Artificial Intelligence which aims to increase innovation and competitiveness in AI as well as position the continent as a global leader in ethical and inclusive AI adoption.
The So What
“Africa is determined not to be left behind when it comes to the rapid advance of AI and the tangible impact it is already having elsewhere,” says Takeshi Oikawa, a BCG managing director and partner based in Nairobi who attended the summit.
“While there are already numerous use cases being rolled out by governments, enterprises, and startups across the continent, there are also many barriers to scale, including the shortage in datasets and computing resources, skilled talent, and regulatory frameworks.”
AI is expected to contribute almost $16 trillion to the global economy by 2030. But only 10% of this will be felt in the Global South, according to the UNDP.
And BCG’s AI Maturity Matrix, which assesses the readiness and exposure of 73 global economies to AI, also shows that many African nations are at the nascent stages of their AI journey.
Nevertheless, Africa has some of the fastest growing markets in the world as well as a booming population.
“This provides a huge opportunity for a ‘learning by doing’ culture to help address urgent needs such as improving health care, responding to climate change, or reshaping agriculture,” explains Oikawa.
“And the adoption of AI in the Global South may gain momentum due to a shortage of trained people to perform tasks that AI is now capable of,” he says.
Now What
These are some of the areas of focus to accelerate the adoption of AI across Africa.
Grow talent. Although Africa is home to one of the largest workforces in the world, there is also a capability gap that needs to be closed. This includes building basic AI skills among white collar employees. It also includes training and equipping the people who are building tech solutions with AI. And it means having the advanced education and qualifications needed for the people who will develop and train the AI. Although some African universities such as UM6P in Morocco and the University of Cape Town in South Africa are taking a lead, strong PhDs and specialized AI Masters are offered by only a handful of R&D hubs and Centers of Excellence across Africa. The most important gaps to address are in training Africa’s research and data scientists since employers mention they are predominantly recruiting these from global institutions. Partnerships with both industry and globally-leading AI universities can help strengthen Africa’s AI talent pool, for example with curriculum development, student scholarships, joint projects and research, and job placements.
Focus on responsible AI. Governments and businesses will need to define AI policies and strategies. AI brings unique business risks, especially when it comes to unsafe experimentation with AI within an organization, adhering to regulation, or data privacy and the security of data sets. There will need to be policies around data sharing between countries. Within Africa, some of the ethical decisions around AI are especially critical given the need for inclusive AI in a diverse region of one billion people. There will also need to be strong evidence-based validation of AI’s outcomes, especially when it comes to poverty reduction. However, when done right, organizations that lead in responsible AI build better products and services, accelerate innovation, and decrease the frequency and severity of system failures.
Target innovative funding mechanisms. Private companies are already making some of the investments needed to scale up Africa’s AI capabilities. Cassava Technologies, for example, is partnering with Nvidia, a world leader in the high-end GPUs that power AI, to develop Africa’s first AI factory in South Africa this year. The firm also plans to deploy Nvidia’s advanced computing and AI software at other facilities in Egypt, Kenya, Morocco, and Nigeria. In addition to greater private sector involvement, there will also need to be innovative financing methods and blended financing to attract funds from the public sector and development banks in order to mobilize resources, especially when it comes to building the necessary digital infrastructure such as increased compute power and a stable electricity supply. Such partnerships could also help deliver the computing infrastructure needed to develop advanced AI models and help establish more data sets to apply AI skills in a local context.
