Africa has a unique opportunity to leverage new digital technologies to drive large-scale transformation and competitiveness.
Copyright by www.brookings.edu
The future is intelligent: By 2030, artificial intelligence (AI) will add $15.7 trillion to the global GDP, with $6.6 trillion projected to be from increased productivity and $9.1 trillion from consumption effects. Furthermore, augmentation, which allows people and AI to work together to enhance performance, “will create $2.9 trillion of business value and 6.2 billion hours of worker productivity globally.” In a world that is increasingly characterized by enhanced connectivity and where data is as pervasive as it is valuable, Africa has a unique opportunity to leverage new digital technologies to drive large-scale transformation and competitiveness. Africa cannot and should not be left behind.
There are 10 key enabling technologies that will drive Africa’s digital economy, including cybersecurity, cloud computing, big data analytics, blockchain, the Internet of Things, 3D printing, biotechnology, robotics, energy storage, and AI. AI in particular presents countless avenues for both the public and private sectors to optimize solutions to the most crucial problems facing the continent today, especially for struggling industries. For example, in health care, AI solutions can help scarce personnel and facilities do more with less by speeding initial processing, triage, diagnosis, and post-care follow up. Furthermore, AI-based pharmacogenomics applications, which focus on the likely response of an individual to therapeutic drugs based on certain genetic markers, can be used to tailor treatments. Considering the genetic diversity found on the African continent, it is highly likely that the application of these technologies in Africa will result in considerable advancement in medical treatment on a global level.
In agriculture, Abdoulaye Baniré Diallo, co-founder and chief scientific officer of the AI startup My Intelligent Machines, is working with advanced algorithms and machine learning methods to leverage genomic precision in livestock production models. With genomic precision, it is possible to build intelligent breeding programs that minimize the ecological footprint, address changing consumer demands, and contribute to the well-being of people and animals alike through the selection of good genetic characteristics at an early stage of the livestock production process. These are just a few examples that illustrate the transformative potential of AI technology in Africa.
However, a number of structural challenges undermine rapid adoption and implementation of AI on the continent. Inadequate basic and digital infrastructure seriously erodes efforts to activate AI-powered solutions as it reduces crucial connectivity. (For more on strategies to improve Africa’s digital infrastructure, see the viewpoint on page 67 of the full report). A lack of flexible and dynamic regulatory systems also frustrates the growth of a digital ecosystem that favors AI technology, especially as tech leaders want to scale across borders.