In Africa, like everywhere else in the world, artificial intelligence (AI) is moving up the agenda as companies, entrepreneurs and governments work out how to keep pace with the Fourth Industrial Revolution. While the continent has a long way to go when it comes to AI adoption, these technologies already play a prominent role in many individual organizations: Nigerian mobile-lending platform Carbon uses machine learning to evaluate credit applications, South African fashion retailers rely on algorithms to predict the next season's top sellers and Kenyan ride-hailing app Little has implemented AI to assess driver performance. For the continent to remain relevant on the global stage, it is not only vital that companies embrace AI, but also that local entrepreneurs have equity in these technologies. That said, building an AI-powered start-up in Africa comes with a unique set of challenges not experienced by entrepreneurs in Silicon Valley, particularly in terms of raising capital, human resources and market receptiveness. Entrepreneur Vian Chinner has first-hand experience of both worlds.

All retailers have models for predicting market response to new products, but with cutting-edge new fashion items and revolutionary products that have no historical sales data, it can be difficult to gauge the market success the items might enjoy. Artificial Intelligence (AI) has the answers, says Vian Chinner, CEO of local start-up Xineoh. AI tools – the evolution of early recommendation engines – are already delivering on their potential to accurately predict customer behaviour, improve retail sales and enhance customer experience. Born-in-SA Xineoh, whose team of data scientists has gained global acclaim for their pioneering predictive algorithms, is already helping South African organisations improve their ability to predict customer behaviour. In fact, Chinner is so confident of the solution's ability to deliver measurable improvements that he offers new customers a money-back guarantee of satisfaction.

Google recently repitched Duplex to explicitly reveal to restaurant hosts and salon staff that they are speaking with the Google Assistant and are being recorded. Google omitted this small but important detail when it first introduced Duplex at its I/O developer conference in May. A media backlash ensued, and critics renewed old fears about the implications of unleashing AI agents that can impersonate the behavior of humans in indistinguishable ways. By tweaking Duplex, Google puts to rest some of that criticism. But why is it so important that companies be transparent about the identity of their AI agents?

Artificial intelligence has been shaking up the marketing world for the last few years, helping automate menial, repetitive tasks, inform better creative decisions, and predict revenue projections. But many of the tools available for that latter category, namely, predictive analytics, have a less-than-stellar accuracy rate. South Africa-based Xineoh has developed a platform for predicting customer behavior with AI. The company claims its technolgoy is more accurate than any other solution available. Xineoh was founded in 2010 and raised $2 million from U.S. and Canadian investors in June 2017.

Thanks to recent improvements in internet connectivity and the emergence of numerous global big-hitters, South Africa has finally made a name for itself in the technological space. But while one might expect the country's'next big thing' to be found in tech-centric cities like Stellenbosch, it's in fact in an unassuming corner of Bloemfontein where the foundations for South Africa's own Silicon Valley are being laid. Founded in 2014, Bloem-based performance marketing company Xineoh is making waves internationally thanks to its unique vectorization algorithm, which has already generated in excess of $30 million in revenue for clients across the globe, attracting the interest of investors, with $2million received in backing to date in 2017. A pioneer in the AI and machine learning space, Xineoh's distinctive algorithm bears similarities to those used by the likes of Amazon.com and Netflix, tapping into user behaviour to predict potential purchasing behaviour and serve users bespoke information likely to incite conversion. Yet unlike these tried and tested models, Xineoh's algorithm relies on available rather than inputted information, creating associations based on the way other users have interacted with the same product or service, thus enabling it to be used across a wide variety of industries and generate uncannily accurate recommendations.