Tracking bugs and fixing them through automation and manual testing processes, and with help of various tools is becoming increasingly efficient. Although; this brings efficiency only to execution process it has no predictability to it. The next big thing that will alter the landscape of software testing is Predictive Quality Analytics through Artificial Intelligence(AI) and Machine Learning. As this technology matures; it will not only identify major bottlenecks, bug categories and improvement areas; it will also suggest improvements based on the analytics to majorly improve efficiencies of subsequent test runs and ultimately quality of software as well as end-user experience.
Digital transformation in enterprises today demands continuous quality. Such technology can become a potent tool for software testing teams to deliver better quality faster and thus impacting not only the quality but effort, costs and time to market.
While for this presentation; we have used Software Testing domain as focus area; the predictive analytics technology aided by AI and Machine Learning will increasingly become all-pervasive across diverse business areas like sales, operations management, Security, etc. Through the example of Predictive Quality Analytics; this presentation will help readers visualize and comprehend future with AI & Machine Learning.