How Africa Can Forge Its AI-Powered Economic Future
Artificial Intelligence (AI) is emerging as a transformative force comparable to past General-Purpose Technologies (GPTs), which drove previous industrial revolutions, and is anticipated to bring about similar—and perhaps even greater—effects in Africa.
Discussing the importance of this technology, Brad Smith, who serves as both the co-chair and president at Microsoft, stated: "Throughout history, technological advancements have reshaped economies," he elaborates.
He states that the initial Industrial Revolution was fueled by advancements in ironworking, the subsequent one by electricity and machinery, and the most recent third revolution—which has spanned the past five decades—by developments in computer chips and software.
Smith notes that whenever a new Industrial Revolution occurs, people often focus on identifying the key leader. However, historical evidence shows that nations making the greatest strides are typically those where the technology becomes broadly disseminated and embraced.
Since technology transforms all aspects of an economy, the nation that employs it extensively will reap the greatest benefits.
This can be clearly seen in the case of electricity: gross domestic product (GDP) grows as electricity is adopted and used. “There is no country where this is the exception,” Smith states. “And the same is true in Africa.”
He points out that the secret to achieving future success lies in implementing versatile technologies.
In this emerging AI age, we begin with the firm belief that it represents the next evolution of GPT.
According to Smith, countries aiming to successfully adopt a GPT must excel in four areas.
The primary aspect is the underlying technology. "As it happens, each GPT relies on a technological framework. This gives rise to a novel economic landscape because each component within this framework corresponds to emerging businesses, different kinds of enterprises, and various job roles."
The current AI technological framework comprises three tiers: infrastructure, platform, and applications.
“IS has an enormous footprint,” Smith states. “It demands the billions of rands being invested in our data centers. Similar to how you cannot generate electricity without power stations, artificial intelligence cannot function without these data centers.”
The platform level encompasses both open-source and proprietary models developed to utilize data for training purposes. "It is here that a fresh wave of AI platforms and software services are coming into existence."
On top of the hierarchy sits the application layer, enabling individuals to accomplish their tasks.
"Electricity brought about transformative changes at the level of appliances, and similarly today, with the AI technology stack, it’s the applications that people interact with and utilize," Smith states.
To develop a new AI-driven economy, you must have all three elements working together to kickstart the cycle. Infrastructure enables the creation of models, which in turn facilitates the development of applications—this then encourages further expansion of the infrastructure.
He points to the South African Revenue Services (SARS) as a prime example of an organization utilizing cutting-edge technology, including artificial intelligence, for tax collection purposes and transforming citizen interactions with governmental bodies.
When developing a new economy, governments and businesses must focus not only on mastering the technology but also on understanding economics thoroughly, according to Smith.
The economics of artificial intelligence revolves around economic structures, financial frameworks, and business models.
For instance, he points out that each technology stack includes an economic framework, where components at the base tend to be costly, whereas those at the peak are relatively inexpensive.
“Similarly with AI, you observe billions being invested at the infrastructure level, whereas students can begin building new companies quite affordably at the application level.”
Following this, it's essential to develop a financial framework. Smith points out that companies such as Microsoft are collaborating with partners to fund the development of AI infrastructure globally.
This usually begins with private companies and private funds, followed by sovereign wealth and additional public financing. This structure isn't solely aimed at releasing capital; it also focuses on boosting demand.
When nations struggle to gather the necessary amount of capital, Smith suggests they might consider forming partnerships within geographical regions. "An alternative approach to speed things up is increased utilization by the public sector."
The government plays a crucial role in initiating this process, not just through policy formulation but also by ensuring all aspects of the public sector adopt the technology.
Developing the appropriate business models represents the ultimate, and essential, stage for achieving sustainable success. As Smith highlights, "The lesson we can glean from history is that these business models tend to evolve."
The third crucial step to capitalizing on the emerging AI economy involves developing skills.
This is merely commonsense," argues Smith. "If it's crucial for something to be utilized across the entire economy, then the necessary skills should also be prevalent throughout the economic landscape.
The past industrial revolutions tackled this issue through technical schools and apprenticeships during the first revolution; via land-grant universities and industry standards in the second; and through employee training alongside computer science programs in tertiary education during the third.
When scaling up workforce development for the AI age, Smith argues that we require three categories of skills: first, AI literacy, enabling individuals to utilize these technologies effectively in their jobs; second, AI engineering, an extension of traditional computer science; and third, AI system design, empowering non-technical professionals to integrate AI into strategic planning, operational procedures, and process improvements within businesses.
According to Smith, every nation should develop a comprehensive AI talent strategy to evaluate market demands and increase AI literacy.
This would cover more than just universities and technikons; it should also incorporate programs such as South Africa’s Youth Employment Scheme (YES), aimed at wider skill development.
According to Smith, for a technology to be widely adopted, it needs to achieve a certain degree of societal acceptance.
And for a technology to gain social acceptance, it needs to be both beneficial and reliable.
The development of a genuine strategy and framework of trust is essential for the future of AI.
To establish this trust, privacy, digital security, and ethical AI are essential, he notes.
This is precisely why we're developing AI governance structures starting from scratch—from internal corporate policies all the way to international regulations.
According to Smith, sustainability is a crucial component of the trust formula. He emphasizes that "we cannot adopt a responsible stance towards AI without tackling the necessity for sustainable AI."
To turn the AI economy into a tangible reality, businesses and nations must concentrate on every aspect of it. "This is remarkable, exhilarating, and intimidating," Smith remarks.
He emphasizes that the key to accomplishing everything is motivation. "Consider all the incredible possibilities we have with AI."
“However, while we ought to find motivation in every potential success, we should equally draw inspiration from each possible failure.”
For instance, he highlights that it has been 140 years since Thomas Edison brought electric power to lower Manhattan. Despite this progress, many people in Africa still lack access to electricity even today.
“This is a cautionary tale that should inspire is to do better,” Smith says.
We have the chance to aim higher, act more boldly, and chase after something even Edison couldn’t have imagined.
Provided by Syndigate Media Inc. ( Syndigate.info ).