Any ideas on how would AI be helpful to the QA community

Hello everyone, I am excited to be a part of this club. It would interesting to know what your ideas are when it comes to AI(artificial intelligence) helping our QA community. How could AI make life better for QA? Please share your ideas. I am planning to do a small poc. Let me know if you have any interesting thoughts.

Hello @deepikasachdeva!


In my opinion, there is a great opportunity for AI or Machine Learning (ML) in the testing (not QA) community.

One opportunity I see is in regression testing. I would like to have a utility that I can train against one of my applications. Once it is trained, I want to run it frequently against that same application and have it report differences including navigation, image changes, and dynamic and static content. From the report, I want to be able to tell the utility which changes it should accept as a new normal.

Another opportunity may be in transaction review. I would like to have a utility that I can train using a list of transactions. I would expect it to detect patterns in those transactions where I could define the patterns as normal (customers see success) or abnormal (customers see errors). Once it is trained, I want it to monitor all transactions and report abnormal transactions and their frequency. I want to use this information to guide project teams towards the most valuable work.
In my opinion, a really good utility might detect where some transactions were attempted by the same customer multiple times. Additionally, it might detect similar patterns in other customer transactions. I want to use this information to make enhancements to the transactions.

I believe we are just scratching the surface of this opportunity!


There’s a great primer here:


Not sure how feasible this is but I like the idea of using Generative Adversarial Networks for generating specific kinds of test data specifically pictures. Possible other types of life like test data. I think without even being fancy once could use simple statistical methods to make predictions about applications and services one is testing and maintaining. The amount of data and expertise in the tooling is significant barrier to many types of adoption.


Thanks for your suggestion Joe, for the first one I believe we have tool called Applitool which does a similar thing however the second idea seems good to try out and I think “optimizely” does something of this sort which helps business drive decisions on what needs improvement or enhancements based on customer behavior but i am not entirely sure :slight_smile:

AI stands for Artificial Intelligence. As we all know that with software development life-cycles becoming more complicated day by day and delivery time spans are reducing. The testers need to impart feedback and evaluations instantly to development teams. Artificial Intelligence is a continuous testing platform these days which can recognize changed controls more efficiently than a normal human being, and it contains many useful features like constant updates to its algorithms, even the slightest changes can be observed.

One of the biggest advantage of Artificial Intelligence is being widely used in top software testing companies as it broadly used in object application categorizations for all user interfaces. Everyone knows that Software testing usually takes up the most amount of time, human resource, and capital. But, if we talk about AI it is an appropriate way forward because with the help of AI we can easily find a way to automate it and move it forward with efficiency instead of a human tester which needlessly inflates costs and efforts.

Many quality assurance companies know that with the help of AI, we can ensure more foolproof results because manual testing not only requires extensive human hours but is prone to inaccuracies and inconsistencies. More frequently manual testing faces scalability issues and it also requires the maximum management of several machines to run.

Hope this information is helpful for you.

There are so many ways AI is going to be helpful not only to testers, but developers and the whole team as well. I wrote an article on the exact same topic here - Just like automation tool/frameworks, I think AI will help us with repeatable tasks and finding patterns for us quickly while we continue to do our exploratory testing.