siliconindia | | April 20189plexity of the problem, he has to come up with a model which brings value to business.5. Team Expansion: You need an army of data scientists to mine loads of real time data. The lead data scientist should invest time in hiring the right kind of guys, who not only can read data but also come up with solutions that impact the business. But what next after you have setup your team and laid out your expectations. I have tried to categorize four areas where AI can help us and we need to focus on once we have set up a team and set the expectations.The four areas are:1. Interaction with Platform: Instead of interacting with one person at a time like a human representative, an AI system can interact with an infinite number of people at once, based on the skills built for it. Not only can AI create and maintain a powerful, 100 percent consistent brand experience through every interaction, but it can also use learning capabilities to tailor that experience to each individual, and rapidly evolve the experience to react to any new product or strategy the enterprise wants to implement. Voice and Chatbots are two new powerful way of interaction to any platform, and this has changed the way customer used to interact with any company.2. Create an Intelligent Product: AI can help us in creating more advanced and intelligent product; for example:Personalization: There is a very high chance since A and B have been bought together that you would also need be. This works really well for mass produced products, but it doesn't really work for personalized items. For personalization, we really need to get-in deeper. Need to understand the content what the consumer likes and the specific thing within the content that the consumer likes or dislikes.Smart Search: Where clients would once be happy to filter a list of properties by area or price, they now want to be able to add deeper layers such as the likelihood of a high return on investment. Artificial intelligence can build these layers into the results of searches before a customer even thinks to ask them3. Business Insights: With the help of AI now, we can bring more business insight and can create more revenue generation sources. Like finding out how effective is our sales and how can we improve to get more sales.4. Automation: With AI coming into picture, we can now automate decade-old processes and therefore helps organization to use manpower in more intelligent and in a more effective way.To evolve from the culture of knowing to a culture of learning, we need to embrace the power of data. From a process driven culture, we have to move towards a culture where decisions are taken in a more objective way that is driven by data. All one needs is a bit of imagination. For long, I have heard that the job of data scientist would be the most sought after in the 21st century. But why? The simple answer is the explosion of data generated by companies, all thanks to digitization over the past decade. This `big data' that will certainly shape how business would be done in future. From a process driven culture, we have to move towards a culture where decisions are taken in a more objective way that is driven by dataSubodh Kumar
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