Artificial Intelligence automation is developing at an astonishing pace. The expansion of its capabilities and ways it can be used and is impacting and changes important sectors, with business and the economy among them. With the advancement organizations are focusing more and more on how technology can drive their success by increasing efficiency and effectiveness of how they operate. This article will focus on some of the identified benefits, however it is fair to acknowledge the fear of an inevitable upcoming change to some of the sectors as people perceive the risk of unemployment through job loss.
One among many areas of our professional lives where Artificial Intelligence is making a tremendous impact is software engineering. Even before AI, automation alone has allowed a change in the approach to the was software is developed and tested. Seems that just a moment ago testing was done as a last stage, only after development, where QA engineers looked into what was done. This waterfall approach is moving away with the “shift left testing” trend – testing more and earlier than simply after development. Organizations becoming more Agile understand and implement testing activities in each step of the software development life cycle. While the demand for QA testers is increasing, the most innovative organizations also lean towards automation of the tests. Surely automating repetitive tasks is not a new concept, however doing it more efficiently by turning to Artificial Intelligence and Machine Learning is the next big thing in this area.
On a general level Artificial Intelligence and Machine Learning can be used to automate certain aspects of software testing. Repetitive outcomes received at a faster pace in a more efficient manner allow the identification of patterns in software defects. Those will return will spot areas which require the most significant attention – making it a testing cycle in itself. From the development team’s perspective AI is used to simplify the software development lifecycle. With AI employed to do the testing, the team does not have to run through laborious yet often times boring repetitions of the same manual tasks. The technological world is expanding rapidly with the complexity of solutions keeping up to its pace. The more complex the products we use and develop, the more significant and indispensable proper testing and maintenance is.
Software development is a field where testing is considered a critical step. However, one would need an army of resources and an unlimited supply of time to perform thorough and complete comprehensive tests. Even then, since it would be people doing the work, mistakes in reviewing of test results are unavoidable. Moreover, a human tester spends up to 80% of his testing work actually re-running tests done in the past. This is an area where Artificial Intelligence could assist in automating the process to become more effective. A mix of human cognitive abilities and AI automation seems like a good practice to implement. Allowing AI to focus on repeating tests and analyse the outcomes will give the QA engineers a significant portion of their time back to focus on tasks which require creativity and thinking. Obvious benefits for the business are already visible – reduction in required resources, time and money. Other “soft” positive aspects of such an approach will include but not limit to increased staff motivation and sense of agency and fulfilment.
Diving deeper into the value-added aspects of AI automation of software testing, there are at least 5 quantifiable benefits which one can think of. As mentioned in the previous paragraph, human work is prone to errors. Even a most experienced tester will not avoid them, especially with frequent manual tasks. Applying AI automation instead will guarantee enhanced precision, it will perform the same tasks properly each time, hence ensuring accurate outcomes. Secondly, a well-established AI automation system can perform the work of a great number of virtual users simultaneously. With an AI automated testing process issues can be detected faster and directly to the developers reducing the time between development and QA saving time in the overall SDLC by removing possible bottlenecks. Implementing AI automation will enable the possibility of performing an increased volume of tests without the need of employing a large group of people to do so. On some occasions it actually could cover more distinct test cases that any group of human resource would ever do. With software development requiring retesting every time modifications are applied to the source code, AI automated tests can be automatically performed in almost no time and with no extra effort from the staff side. QA engineers can focus on testing the newly added features, which their AI counterpart will make sure what worked before – is still working as expected currently.
We as Brickendon have already done the homework of understanding the benefits of implementing AI Automation. With the current pace of AI advancement, it becomes a question of when as opposed to if your organization will have to start the adaptation of AI in their business processes. Our consultants are here to help you to work smart and drive your business success.
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- S. Battina, “Artificial Intelligence in Software Test Automation: A Systematic Literature Review”, Journal of Emerging Technologies and Innovative Research (JETIR), vol 6, issue 12, 2019
- T. Yarlagadda, “AI Automation and it’s Future in the United States”, International Journal of Creative Research Thoughts (IJCRT), vol 5, issue 1, 2017