Continuous Delivery is no longer a value-enhancing strategy, it is a much-needed approach in software development and release lifecycle. It has substantially changed the way enterprises test and launch their applications in a volatile consumer ecosystem. The demand for Intelligent Applications is on the rise. In fact, it is predicted that almost all the applications will be delivered with embedded intelligence. It practically implies that these applications will have the capability to scrutinize historical and real-time data to deliver customized experiences and results to the end-users by leveraging Machine Learning technologies. Hence, testing these applications will need a relevant Test Automation strategy and a Continuous Delivery plan.
In the current Digital ecosystem, consumers are swarmed by chatbots and virtual assistants across diverse websites and applications. These features are not only automating basic activities, but are also delivering enhanced and personalized experiences. At a recent Google conference, CEO Sundar Pichai opened the event by stating, "We’re moving from a mobile-first to an AI-first world." Hence, due to growing business mandate and evolving consumer preferences, the need to build such robust applications is increasing by the day.
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