Quality assurance with AI and automation


Test automation and AI are the future Quality assurance with AI and automation

Not least because of the pandemic, companies need to find ways to realize fast release cycles without compromising application security. A quality management system that relies on automation and AI support, can provide valuable assistance.

Companies on the topic

AI-controlled test automation helps to improve the quality of software products.AI-controlled test automation helps to improve the quality of software products.

(© sdecoret – stock.adobe.com)

While public life was shut down, digitalization experienced a rapid boost. In order not to lose their customers and to open up new sources of income, many companies that had not previously been present in this field also relied on online shops and digital services.

In autumn 2020, e-commerce experienced a real boom, while during the Black Friday and Cyber Monday action days, German retail sales increased by 18 percent compared to the previous year. At the same time, the infrastructures of companies that sent their employees to the home office changed.

Overall, this means that different sectors have had to rethink, adapt or even re-establish their existing digitization strategies. This situation, in which more and more communication, transactions and services were shifted to the virtual space, meant that companies had to react quickly and launched new services under high pressure. The sheer speed was usually the top priority, but this naturally increases the susceptibility to errors.

In the case of online services, this means that both application security and user experience, and thus customer satisfaction, suffer-not to mention the reputation of a company. In the long term, these factors can even lead to customer losses and revenue losses. Quality assurance, which consistently relies on test automation, can help to resolve the apparent contradiction between speed and quality.

Quality assurance as an integral part of development

In recent years, quality assurance has become an elementary component of software development. The current World Quality Report by Capgemini and Sogeti with the support of Micro Focus confirms this increase in importance. For most of the participating companies, the promotion of test automation focuses on clear business interests – such as accelerated growth.

In contrast to this increase in importance, however, stands the budget that companies plan for quality assurance. The funds provided have been falling for several years. The proportion spent on quality assurance has fallen from 35 percent in 2015 to 22 percent in 2020. The logical consequence of decreasing budgets and increasing requirements is the search for alternatives.

As teams around the world moved from the corporate office to the home office to reduce contagion risks, the number of security incidents and cyber attacks increased. As a result, 83 percent of CIOs and IT managers expressed more concerns about application security.

This in turn had a direct impact on quality assurance strategies and increased acceptance of cloud infrastructures. According to WQR, 34 percent of respondents believe it is necessary to provide their teams with secure and efficient remote access to test systems and environments to ensure quality and security in application development despite distributed teams.

Test automation increases productivity

Against the backdrop of the diverse challenges, agile DevOps models experienced a major boom last year. This was also accompanied by the increased implementation of the shift-left approach in software development. However, this should not hide the fact that there is often a lack of expertise in the area of quality assurance in general and automation in particular.

Sprint automation, a test that is automatically executed within a sprint, is used by very few developers so far. However, the participants of the WQR are aware of the potential of new technologies. 88 Percent of respondents say that AI and automation are among the fastest growing areas in their testing. In addition, 86 percent are convinced that AI support is an essential criterion in the selection of new quality assurance solutions.

Intelligent automation solutions can increase the productivity of software companies by removing annoying, time-consuming tasks from employees. Anomaly detection is a particular strength of AI, be it latency problems, broken links or script errors. Sophisticated algorithms also create the test data in such a way that the data set is as compact as possible and the test times are kept as low as possible – without significant quality losses. Companies should ensure that they choose a platform solution that integrates all common technologies.


The current World Quality Report shows: When it comes to the reliable and secure provision of software, today there is no way around automated testing. This should be clear to most IT decision makers. However, the consistent implementation often fails due to limited budgets and technical hurdles. Companies that want to achieve their goals and deliver the best possible quality to their customers should set their priorities accordingly in order to overcome these challenges.

Raffi Margaliot

Raffi Margaliot (Picture: Micro Focus)

Comprehensive quality management, which includes AI-controlled test automation, helps to effectively address challenges at an early stage and throughout the entire outstaffing development cycle.This includes expanding the competencies of the responsible teams in the areas of (test)automation, test data and test environment management as well as AI.

* Raffi Margaliot is Senior Vice President and General Manager of Application Delivery Management at Micro Focus. He has more than a decade of experience in developing business strategies, product development and providing technology solutions that address customer issues. Raffi was one of the founders of today’s Application Lifecycle Management platform.


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