Modern Approaches to Automating QA Processes in the Context of Digital Transformation

Abstract

The article examines approaches to automating quality assurance (QA) processes within the framework of digital transformation. Based on an extensive analysis of publicly available literature, the work describes how the transition from traditional manual methods to flexible automated solutions contributes to reducing the time required for developing test scripts, enhancing the accuracy of defect detection, and improving the overall efficiency of QA processes. The author’s hypothesis is that the integration of AI methods into QA processes not only shortens the time needed for test script development but also increases defect detection accuracy by optimizing test scenarios and employing flexible analysis algorithms. The scientific novelty of the article lies in the development of a new perspective on the use of automation methods in QA processes, made possible by the literature review. The material will be useful for other researchers as well as for professionals working in the fields of information technology, digital transformation management, and process automation who aim to integrate advanced testing methods into the infrastructure of modern IT systems. It is particularly valuable for academic teams, strategic analysts, and top managers seeking scientifically substantiated solutions for the optimization and sustainable development of QA processes in the dynamically evolving digital economy.