Nowadays nobody stays indifferent when it comes to Artificial Intelligence (AI). Its business value is projected to reach almost four trillion U.S. dollars by 2025. So why do we bring up this point again? It seems like everybody is satisfied: the business is growing and employees’ work is simplified. The reason is the following — what if AI bots will fully replace the QA team and when do we need to start worrying about it? Let’s find out.
Real advantages of AI bots in QA
Testers face numerous challenges while performing quality assurance of a software product. Almost always it takes substantial time and effort. These resources can be saved today by applying AI in certain QA processes. Here is what you and your project can get from AI implementation:
AI to speed up manual testing. Routine and repeated actions like “click the icon 100 times” are not that rare in the process of testing. Plus it takes much time and is more expensive if conducted manually. Besides, human testers can make mistakes and give false results of such checks. Artificial intelligence considerably speeds up this process for both developers and testing engineers. Analyzing big data and sorting log files aren’t that scary anymore.
Automated testing. Code optimization is a part and parcel of any development process. AI bots now are able to define and estimate changes in the code. The required test code is updated manually and then run by AI bots.
Risk coverage optimization. Artificial intelligence assists in test optimization by reducing the number of test cases and designating their risk level.
Reduction of False-Positive Experience. False alarms are connected with those negatives (malware) that lead to positive test outcomes. AI bots are designed to recognize and block such threats.
User Experience Analysis. When it comes to big data processing, AI capabilities take leading positions. Scenarios for software testing that predict users’ needs and requirements are developed and analyzed by AI bots.
It is far from being the whole list of functions that machines can do instead of manual testers. They become a significant element of the entire QA process, complementing manual testing with automated processes. In addition, AI bots do not complain, work without sick leaves and are always ready to perform their duties. Should we pack our suitcases and look for places that aren’t YET occupied by robots? Take it easy for now because it is not that simple.
Disadvantages of AI bots in QA
Artificial intelligence runs the testing process when we face analyzing big scopes of data, performing continuous (routine) actions that do not expect any deviations in the process. That is great when your clients are patient and don’t require immediate feedback or changes to the existing product’s functionalities. QA engineers can now enjoy a small triumph: AI bots cannot handle such issues.
Meeting business requirements presupposes the implementation of new functionality and usability characteristics. Validation of all these requirements and their correspondence to the product’s specifications is one of the reasons why humans won’t be fully replaced by AI bots. They can be successfully used for performing repetitive actions while still staying under the control of human testers. Another challenge for machines is exploratory testing which fully depends on human skills to discover, investigate, and learn.
It is also hard to believe that usability testing can be effectively performed by AI bots. They aren’t able (at least for now) to explain why a definite format or configuration is preferable or user-friendly. This is one more proof in favor of a tester’s logic and common sense. On the other hand, we cannot simply divide the world into black and white. Artificial Intelligence penetrates our life step by step. According to the World Quality Report, 60% of respondents stated that their current or future projects involve the use of AI.
As for its market revenue, it is projected to reach 40 billion US dollars by 2025.
Final Thoughts on AI in QA
The conclusion is that the implementation of AI in the QA area drives testers to improve their skills and competencies not to be fully replaced by robots. Machines are here to stay and run automated processes while humans are responsible for logic, creativity, management, and supervision. QA activities that require such kind of skills will still be performed by people, but the adoption of AI and smart cooperation with machines will take the QA process to a higher level.
