1. Introduction
When the historians of the future get around the commerce of our times, they are sure to garner overwhelming evidence around the appeal for artificial intelligence and machine learning. The way these two technologies have dug their heels into every possible sector in today’s global market is a revolution in itself. For IT and digitalization industries, in particular, the phrases “DevOps” and “continuous testing” are now finding themselves inseparable from the conversations around AI- and ML-based automation strategies. If anything, it already seems a bit late to expand that conversation to accommodate QA automation.
As new technology is introduced, companies, though reasonably skeptical, are beginning to explore and adapt them against the unique demands of consumers. By implementing safe and efficient automated programs for quality assurance, they are already ensuring minimal downtime and uncompromised service experience for their customers. Continuous testing has become synonymous with the QA strategies in most of the DevOps pipelines. Therefore, it only makes sense to bridge the benefits of continuous testing with the potential enrichments of AI-driven automation. Through the course of this article, we will discuss the various aspects of this bridge, including its relevance, necessity, and aftermath for the world that is already going through its fourth industrial revolution.