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June 1st, 2022

9 Benefits of Artificial Intelligence for Software Testing and QA Outsourcing


Artificial Intelligence has the potential to detect bugs and glitches with no human intervention quickly. Artificial Intelligence aims to reduce tedious manual work by automating repetitive tasks for software engineers. It seeks to solve future problems by learning from the past. Although software engineers must continue to do what they do, now they have access to AI-based automated testing tools that can be used to increase their efficiency.

Artificial Intelligence will allow QA testers to transform from being software testers to becoming an automated testing team. Artificial Intelligence tends to increase the efficiency of QA tests. AI is fast gaining ground in this space as around 70% of testing is recurring. This will allow for many changes in the field of testing. Software testers can use AI tools to increase the quality of an item launched quickly and significantly.

1) High Level of Accuracy

Manual tests can be accurate, but they are not always error-free. Sometimes, QA engineers do not notice the possibility of bugs or errors. To complete the recurring test, QA engineers use automated software. Automating test steps allows you to perform the same actions repeatedly without losing details.

2) Better Defect Tracking

There are many bugs and errors. Old test methods leave bugs and errors unnoticed for long periods. These bugs that are not noticed become annoying later. Artificial Intelligence can detect flaws in seconds and can analyse these bugs. The number of bugs and errors in test data increases with increasing test data. As such , artificial Intelligence automates processes so that codes can be corrected automatically, and software testing teams can smartly do bug tracking. Artificial Intelligence detects duplicate errors and takes debugging logs’ fingerprints.

3) Higher Flexibility

Traditional test scenarios only consider one path or selector. This makes such test approaches somewhat rigid. Testing failures can occur even for the most obvious modifications to an app. Artificial Intelligence and ML allow for highly flexible testing procedures and knowledge relationships among several documentation elements. These systems are both reliable and flexible, as they can automatically adapt to any changes in real-time.

4) Controls Testing Time

Artificial Intelligence is used in QA testing to reduce the time spent performing manual tests. QA teams can apply their skills to complex jobs that require human interpretation. Developers and QA staff would need to make little effort to plan, prioritize, write and manage E2E testing. It will speed up the release timelines and allow developers to use their resources to create new products rather than testing a new release.

5) Enhanced regression tests

Regression tests are becoming more critical as technology advances. Organizations can use Artificial Intelligence to perform a few repetitive regression test tasks, and Machine Learning can be used to create test scripts. Artificial Intelligence/Machine Learning can be used to scan the User Interface for overlap, size, shape, and colour. These tests would usually be done manually. Artificial Intelligence can also be used to validate any alterations that a software tester might miss.

6) Consistency when Testing

Although QA testers can detect and address complex issues and prove testing scenarios, they still have to be human. Bugs can affect tests, especially if the monotonous process is finished. Artificial Intelligence doesn’t suffer from duplicate tests and therefore produces more accurate and reliable results. QA analysts and developers often have grudges, mainly due to time constraints or test results. AI/ML can eliminate human interactions that could cause delays in testing procedures by providing objective results.

7) Enhances Test Coverage

Software testing is made more accessible by the detailed nature of the automated testing. Artificial Intelligence allows QA engineers to test memory, internal program states, file storage, content, and data tables. AI detects patterns in data and analyzes them to determine if the results are as expected. AI can perform multiple test cases simultaneously, providing comprehensive coverage.

8) Quick Release of Software – Faster Time to Market

Automated testing reduces the time it takes to develop and test. Test automation automates the execution of a test after every source code change. This reduces the cost of running recurring tests. Since time is directly proportional to money in the QA/software test industry, AI-integrated software testing proves to be both accurate and efficient.

9) Executing Visual Tests

Artificial Intelligence technology can recognize patterns and images, allowing it to detect visual bugs in apps by running visual tests. Artificial Intelligence can distinguish dynamic User Interface controls regardless of their size and shape and assess them at the pixel level.


Artificial Intelligence will be the next big thing, but it won’t replace humans. Artificial Intelligence can quickly execute many tests, although it cannot perform final tests yet. Human testers must execute implicit and latent testing.

Moreover, humans will still be able to manage the testing results. QA testers can observe the most exciting aspects of QA tests when they work in harmony with Artificial Intelligence. Artificial Intelligence can be revolutionised by QA engineers who work hand-in-hand.

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