We have come to witness the time when artificial intelligence is part of our lives. Of course, humanity is only at the beginning of a road we do not know where it will take us, a road that is still in the construction phase. Beyond technology and its inevitable advance, a social construction suitable for integrating AI into everyday life is needed. The first step in this direction is the creation of an economy of AIs. Regarding this path, the latest Deloitte report says that while AI continues moving closer to the core of the enterprise sector, outcomes seem to lag.

How are Machine Learning Models going to change the Payments Industry? It wasn't so long ago that CEO's and large commercial banks were convinced that more bank locations would always be necessary to service and acquire new customers. However, in the last ten or five years we have seen an emergence of Digital Banks, that have never and will probably never own a physical location, but still manage to grow their user base and add additional services including insurance, mortgages, and loans. In the Banking industry, we have seen companies like First Bank of Nigeria, United Bank of Africa, Zenith Bank, Guaranty Trust Bank dominate for well over twenty years. However, just like the digitization of banking has forced incumbents to change their strategies, the digitization of payments has provided companies like Flutterwave, Paystack, Remita and lately even Korapay to take up some of the market shares, not by focusing on traditional businesses, but by focusing on startups who have grown to overshadow and sometimes even bankrupt traditional businesses.

Digital disruption has broken out of Silicon Valley. Any company, no matter how nuts-and-bolts, can be disrupted by a digital competitor; equally, any company could be that digital disruptor. The discussion was kick-started by two leading industry thinkers: Andrew Moore, chief transformation officer of chipmaking giant Intel, and Nigel Moulton, chief technology officer at Dell EMC, part of a corporation that services 99% of the Fortune 500 companies. Their remarks sparked lively discussion. Both Intel's Mr Moore and Dell EMC's Mr Moulton spend a lot of time talking to leading companies about their digital transformation journey, and they kicked off with a tough message: it's hard work.

The likes of Uber and Ola are already using machine learning to connect riders with ride providers, and they are providing excellent services like minimal waiting time, predictable fares, predictable time to reach the destination, driver verification etc. Many of these thing were not possible in traditional businesses at the price point available now.

Machine learning, deep learning and artificial intelligence (AI) are attracting huge amounts of interest from analysts, press and IT teams. We are seeing large corporations apply data science and machine learning to make AI a reality for businesses and consumers. But is there a problem with too few companies holding too much of the market? What is the "one percent" problem around AI? Gartner predicts that 80 percent of data scientists will have deep learning skills in place by 2019, according to its research team in September 2017; meanwhile Teradata and Vanson Bourne research found that more than 42 percent of enterprises see opportunities for further implementation and process integration of AI in their operations. With so many enterprises looking at their approaches to AI and machine learning, the availability of people with the right skills and experience can become a stumbling block.

In 2011, in an article in the Wall Street Journal, Marc Andreessen proclaimed that software is eating the world. He argued that a slew of technological innovations including advanced microprocessors and high-speed connectivity will revolutionize traditional business, and that every company should become a software company. Many pundits have subsequently argued that even traditional businesses will need to rethink their business models. Andreessen even went so far as to say that the entire retail vertical will eventually die due to the scalability of companies like Amazon. In short, if you aren't thinking about how you will disrupt your industry you can bet your competitors are already doing so.