A recent study by Enterprise Management Associates (EMA) revealed that visual AI is extremely important in software testing compared to other applications of AI technology in the market.
Indeed, it was reported that organizations that rely on traditional testing tools and practices do not meet the digital demands and needs and are more likely to fall behind their competitors. Some of the factors that hinder software engineering teams are the escalating costs of quality control as well as the growing complexity of release velocity, smart devices, operating systems, and programming languages.
Hence, the study showed that AI and machine learning (ML) can provide a real return on investment (ROI) and scale to support the growing complexity of software delivery. They allow businesses to accelerate the delivery of customer value through software innovation at a lower cost, which gives them competitive advantages.
By using AI-based test automation technologies, organizations are able to release faster, optimize spend, improve the quality of the product, as well as innovate.