Microsoft’s role to help sow AI success in Africa

Global spend on AI, including software, hardware, and services for AI-centric systems, is predicted to more than double between 2023 and 2026, according to the latest forecasts from IDC. This increase will see AI spend reach $154 billion in 2023 and increase to well over $300 billion by 2026.

So with this monumental trend in mind, Lillian Barnard, president for Microsoft Africa, is excited to see how AI can help the continent fast track its journey toward adopting more advanced and sophisticated technologies.

Today, there are more than 2,400 AI organizations operating across Africa, spanning a wide range of industries, all of which teem with potential to revolutionize many aspects of people’s lives. “All of this being said, I think we need to inject a degree of realism in terms where we are as a continent and also in terms of the work we still have to do to make sure we take advantage of this incredible new technology,” she says, acknowledging that the 2022 AI Readiness Index highlights that sub-Saharan Africa is playing catch up when it comes to progress in this space.

What’s holding Africa back

This lack of AI readiness essentially stems from inadequate access to connectivity, high levels of inequality, and incomplete and unstructured datasets. “Addressing this demands that we put the necessary governing frameworks and infrastructure in place, and focus on building the core skills and resources Africa needs to adequately prepare for the adoption and acceleration of AI,” she says. “If we want to move forward with this technology without leaving people behind, all of these foundations are essential.”

The success of AI applications also depends on the availability of high-quality and diverse data, but, unfortunately, this is where an inherent problem resides. According to the African Centre for Technology Studies (ACTS) in Kenya, available datasets across Africa are largely inadequate. In addition, Africa has only one data scientist for every 14 in the Global North, which means a deficiency of data science skills is a major hurdle, too. To address this, Barnard says there needs to be democratized learning around AI so anyone can develop, use, and benefit from AI innovation.

“Given the level of optimism around AI, we must be sure to remain grounded so we’re responsible in how we use this technology,” she says. “Here, the focus has to be on responsible AI by design so any developments made are driven with accountability, safety, privacy, security, inclusiveness, and are done with transparency in mind.”