JavaScript Required

We're sorry, but we doesn't work properly without JavaScript enabled.

Looking for an Expert Development Team? Take two weeks Trial! Try Now

What is the Impact of AI and ML in Software Testing Jobs?

Impact of AI

Software Testing in general has evolved over a Period of Time in the past few decades. In the 1980s and 1990s. When companies realized there should be a separate QA team to find the Defects in the software. Having an impression Developer who Builds the Software would not like to present the Defect in later stages once the build is ready. Because Developer would assume the software has been Built Perfectly by him. Then separate Software Testing QA jobs came into existence.

Testing was predominantly Manual Testing and we didn't have any such tools for Automation initially and the Development Methodology was basically in waterfall Methodology. Where developers used to work for 6 to 8 months and finally Build a product and then it used to come to the QA Testers’ hands. Once the Tester finds any Bugs on a later stage, then send it back to the developers and then the Dev Team has to fix that bug. after fixing the same they send it back for re-test again. It used to happen in the early stage of Software QA Testing or some of the companies still follow the same Waterfall model.

In the late 1990s in the 2003 period, Software Testing Services Companies started looking at some Software Tools that can help the testers to perform the Testing of Software releases. Then QA Automation Tools came into existence to help the Manual Tester to perform Testing on Regression Test cases & smoke Testing. Which helped to Automate the monotonous job for Testers used to perform every time and they can focus more on Functional Test cases for the new Functionalities. So far so good and in the last two decades, many Automation Tools came into Existence like Selenium, QTP, Winrunner, Test complete, etc. And many people have got lots of opportunities in IT services Project base and Product Based companies to work into QA roles like Manual and Automation Testers.

Impact of Artificial Intelligence / Machine Learning in QA Jobs

While coming into the current Era and future Decades. Artificial Intelligence (AI), Learning Machines and Robotic process Automation are coming very fast and taking huge places into the Technology side.

While coming into the present Era and if we discuss future Decades. AI (AI), Learning Machines, Data Science and Robotic process Automation are coming very fast and taking huge places into the Technology side and Software Industry. Many Experts are Predicting (AI) and associated technologies are going to be present across many industries, with a good number of software packages that have more combinations of these technologies, and a part of our daily lives by 2020. As per Some of the Expert reviews and Prediction, a few numbers of Jobs could also be very less or seems to be invisible within the Future decades in the Software Market.

While coming to the QA Part some Experts assume because of AI & related Technologies there may be several Cut-off in Software Testing QA jobs as well. Some AI Tools will be coming into the Market & those AI Tools will soon start correcting code as the developers write it automatically. AI may come up with many more innovations into Testing, which would be much faster and much accurate. In the coming years, QA and Automated Testing will be more integrated using Machine Learning and AI. The main objective will be achieving Good Quality at Speed and faster resolutions. There are lots of Experiments are Going into these AI/ML related Technologies for creating Faster and more accurate Test framework architecture.

Some of the Experts review it may slow down the QA opportunities in Manual as well as Test Automation industry also. Since AI Tools will be replacing much more Human intervention. Somehow, they may be correct but not completely. It’s not so easy to remove all human intervention but yes it will be less intervention. Because on the other side, some other Experts think there may be some Transitional Roles from Software Testing Professionals to Artificial Intelligence (AI) and Machine Learning (ML), Data Science related Products Testing Engineers. Testers have to upskill themselves in terms of Technology learning about the same products. There is a fear in QA Professionals like soon AI/ML will be replacing their Jobs. Instead of having that fear QA professionals should focus on learning AI/ML/Data Science related technologies, which can help them in the future to Test these particular related Applications. Some experts think some number of Jobs may come in the Future in QA with the Knowledge of these Products. Experts think AI will make it easy to perform testing jobs. Which will be good for QA professionals.

Impact of AI

With the help of AI/ML, some new Tools and Technologies can come into the market with Predictive Analysis, Robotic Automation and cognitive solution and it would be easier to make Tester’s job. Once the developer writes code or if there is any change in application code. Artificial intelligence tools will be smart enough to read those particular steps automatically without any human intervention or very rare human intervention. This kind of ML-based tool can be used for Regression Automation testing and Smoke testing.

When it comes to Artificial Intelligence & Machine learning technology in terms of Software Testing is more focused on creating and making the Software development lifecycle easier. Through the device of Problem-Solving and reasoning whereas AI/ML associated technologies can also help to automate the repetitive task and monotonous work in companies software Projects under development and testing industries. In the coming years, we are expecting many more inventions within this industry to deliver high-quality product releases.IT services have already started the transformation with the use of these technologies in testing automation and creating Hybrid applications.

Machine learning and Artificial Intelligence can also be used in understanding, Predicting and forecasting the client requirements. The correctness of client requirements can change into the testing process and will help testers to analyze the customer data. Predictive analysis will give more information and inputs on the company’s product features as they need them.

Still, Machine learning and Artificial Intelligence should not be considered a hazard to software testing jobs. Testers can look into the advancement of Technologies to grasp and learn the same.

Recent Blogs


NSS Note

Some of our clients