There is a rise of innovation that is troublesome to the capacity to scale; and also many fail to understand these forces until it is too late says a KPMG report. As the bang of the Covid pandemic gradually slows, many companies would get back on their feet, and be prepared for one more digital disruption in the upcoming years.
Digital innovation or transformation face challenges associated with growth, customer, productivity, and people. These issues can conquer the transformation levers such as innovation, latest technologies, and data-powered with AI and some new ways of working. KPMG in India said which was from the report by Feroz Khan, Partner and Head of Department, New Digital Technology. A three-point approach would be needed by companies to tackle this. Companies would include innovating, incubating, and commercializing in this ever shifting world. And if they want to survive, organizations should remain proactive, than reactive to the changes the report argued.
For companies that wish to survive the digital age innovation should not be a one-time activity but will have to be part of their day to day thinking. As digital disruption continues to get together well, organizations must increase their capacity to spot, prioritize, and respond to this digital disruption in order to compel better business results.
With the opportunity of incorporating different systems and automating several tasks, the digital transformation takes another leap while Artificial Intelligence (AI) and Machine Learning (ML) became part of the business strategies of many organizations’. Resulting in faster and efficient operations and, more productivity, these technologies are so significant in the digital transformation or digital disruption as they enable better use of the data. These data are collected by companies in several ways. 90% of all data created in history has been produced in the past two years, and it is necessary to make sense of them or it is of no use. As we know data is the new oil.
There is no way to include artificial intelligence without a clear and defined data tactic. There is no point in talking about Artificial Intelligence if you do not have data organized. It would be recommended to do your homework before starting the experiments with AI and Machine Learning. Today, it is challenging to keep a large amount of data produced by the business. It should be organized sustainably on a server or data center. Cloud is the direction you have to follow if this is the issue. Investing in digital technology is to train the machine and the algorithms from databases.
