Artificial intelligence (AI) is rapidly gaining traction in Africa, like the rest of the world. Governments, companies, and entrepreneurs across the continent are stepping up efforts every day to keep up with the Fourth Industrial Revolution.
Although AI adoption is a bit of a challenge in Africa, this technological advancement continues to serve many individual organisations. For example, in South Africa, a group of fashion vendors leverage AI algorithms to evaluate the coming season’s stiff competitors while in Kenya, the taxi-hailing app, Little, has already embraced artificial intelligence to monitor their cab operations.
Safaricom, a leading mobile network operator in Kenya, has recently introduced an AI chatbot, Zuri, to improve its customer service. Meanwhile, the Nigerian lending agency, Carbon, has also taken to using AI to evaluate loan applicants’ creditworthiness. And the list goes on and on.
Despite the relatively high growth of AI in Africa, many native entrepreneurs and founders find it very difficult to scale their startups. This is because building an AI-powered startup in Africa comes with a unique set of challenges, some of which are not experienced by Silicon Valley entrepreneurs. These include securing human resources, capital, and market openness to emerging startups.
Here are three big challenges entrepreneurs face running an AI start-up in Africa and how you can overcome them.
1. Early-stage AI start-up battle to earn an appraisal
First things first, the rate of VC funding in North America is incomparable with the one in Africa.
A report released by Southern African Venture Capital and Private Equity Association revealed that in 2017, South Africa’s VC industry invested around $77 million in 2017. During the same period, US startups struck VC deals amounting to $84.24 billion, which is an average of $115 million every morning.
One reason given for this huge difference is that most VCs investing in African startups are more risk-averse compared to their counterparts in Silicon Valley. U.S VCs are generally willing to back high-risk innovative ideas while their African counterparts typically reject companies that lack proven cash flow and evidence of market traction.
For example, a start-up in Silicon Valley only needs to explain the idea and the direction of the company- there exists an understanding in Silicon Valley that a startup lacks a comprehensive business plan until when the product is launched in the market.
“Once the start-up has received initial feedback from customers, it will start iterating to create a product-market fit. US VCs put a very high premium on innovative products and ideas, but attracting investment based on a concept or idea is tough in South Africa,” said Vian Chinner, CEO of South Africa-based Xineoh, which uses AI to predict consumer behavior.
Lack of in-house expertise to assess AI solutions fully is another major challenge for startups in Africa. Contrary to Silicon Valley investors who are experienced techies, many African VCs only boast banking experience, says Chinner, who was speaking to the World Economic Forum (WEF)
For this reason, many early-stage startups look for funding from abroad, but it is not always that simple. While the economic and political instability in Africa is a big problem for VCs, crossing the seas for help is a much bigger challenge. These investors want startups that are within their vicinity and would prefer to support a startup that is based close to them.
Given the distance and the lack of networks in the US, Africa-based entrepreneurs are at a massive disadvantage when it comes to attracting investments abroad.
2. Getting AI human resources is a challenge
Very smart data scientists are the key to the success of AI companies but the African continent has very little supply of these professionals
There’s an acute shortage of data science experts in Africa compared to other parts of the world. In Europe and North America, for example, nearly every university is offering degree programs and training in the area of data science. In Africa, however, educational institutions are just commencing to bridge this gap.
“There are enough smart people in SA that can become data scientists, but it seems that this is not a well-embraced career choice,” says Chinner.
Chinner and his company recruit graduates of applied mathematics and mold them to fit in modern-day data science. He says that training people with knowledge of applied mathematics is much easier since they have a better picture of the current world of AI.
Besides data scientists, companies running AI also have to recruit salespersons who can explain complex algorithms. These people have been hard to find in Africa because there are a few available.
3. Corporates not ready to embrace the advantages of AI
Big corporates in Africa understand the importance of AI, but they are only willing to support pilot programs. Many are not yet ready to adopt AI on a large scale. Even for companies that build their own AI solutions, such in-house initiatives rarely go past the proof of concept stage.
In South Africa, one sector that has displayed a glimpse of interest in adopting AI in the retail sector. The intensity of the competition, as well as the need to improve customer satisfaction, are the reasons behind this trend. The retail industry also boasts accurate and well-streamlined transaction data that AI algorithms can use.
So what can local AI startups do to compete with global brands like Microsoft, IBM, and Oracle? The answer lies in developing solutions that address African problems. Build solutions that are more robust, flexible and suited to the local ecosystem.