Top risks related to Artificial Intelligence projects and how to overcome themDecember 19, 2017

Remember Skynet, the fictional Artificial Intelligence (AI) system which threatened to take over the world in the Terminator franchise? That was many of our first introductions to AI and to the “horrors” it might unleash. That was our imagination in hyper-drive, and over the decades, we’ve played out similar scenarios in other major blockbusters from the Matrix to iRobot and everything in between. Yet, despite continued fear-mongering, the scenario playing out in real life is a very different picture. AI is being used to address major business challenges for anti-money laundering and fraud where large volumes of data make it difficult for humans to resolve manually. Predictive analytics in financial services, healthcare and other industries are making it easier to plan around negative outcomes to create safer situations for workers and citizens. However, AI does have its risks if its not managed and governed well.

Today, we hear of every second corporation trying to use AI in some way or the other to help achieve either one or many business objectives – becoming more efficient, effective, leaner, faster turnaround time, better customer service, reducing costs, and the list goes on and on. AI is now seen as an answer to all the ills plaguing the world of business and just about everyone is either already on the bandwagon or ready to jump.

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