Shailender Kumar, Managing Director, Oracle India

Machine learning is rapidly pervading every sphere of our lives, transforming the world around us in many significant ways. The technology is helping us access the right information on time, enabling us to make better decisions quicker than before. It’s no surprise therefore to see enterprises rapidly embracing machine learning to fast track innovation and increase speed to market. It’s immense potential to transform the very way in which businesses function is what’s bound to make it an era defining technology.  

We are now in a data revolution era and as we progress, the roles of people will also change, leading to the creation of new jobs, new business models and new industries altogether. According to Gartner, AI technologies will be present in “almost every new software product” by 2020, making this an exciting and opportune time for software providers to help transform business innovation as we know it and a crucial growth pivot for the businesses who buy from them. 

Furthermore, with the proliferation of cloud, the pace of adoption for machine learning is increasing exponentially. The seamless integration of cloud applications, platforms and infrastructure are major drivers of the growth and effectiveness of machine learning. They unlock the power of machine learning to greater pools of data, breaking down silos and drawing in data from across organisations and their networks. This spans multiple uses: like rapidly analyzing and deriving understanding from data, identifying trends or anomalies in vast data sets, and it can generate profound transformation across the board - ranging from clinical research to compliance and security.

The algorithms that drive machine learning need data from as many sources, as possible. For any machine learning solution, the more it feeds on relevant data, the smarter it becomes, paving the way for greater decision-making potential. The exponential growth and adoption of cloud technologies add to the reasons why 2018 represents such a favourable opportunity for machine learning. For effective implementation, strategy comes into play. The key to getting the most from machine learning is to look for applications that deliver long-term strategic value, which fundamentally transforms functions or critical processes within the business, rather than delivering a short term ‘wow factor’.

Machine learning is also transforming the customer service industry. In any customer facing industry, vast number of support enquiries fall into a number of different categories. Imagine what intelligent chatbots powered by machine learning can do – they can be deployed to intuitively respond to the customer queries adequately, also freeing up resources for more high value work. This is a classic example of how machine learning enables businesses to accurately respond to customers. It also frees up customer service agents to handle the limited number of complaints that are more unique and require human intervention. In my opinion, this is also a clear example of machine learning augmenting people’s capabilities to enhance work effectiveness. Contrary to what many people think, it will not replace people, but it will certainly make people more efficient, creating value across the board.

There is no doubt that machine learning is dedicated to simplifying our lives and work processes. It’s therefore no surprise when I hear from most CXOs I meet tell me that they believe 2018 will be the year of machine learning, with more and more businesses committing to explore and unlock the value of machine learning in its entirety.


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