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3 Reasons for Incorporating AI in Functional Testing

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Artificial intelligence is the imitation of human intelligence procedures by computing systems. Some particular apps of artificial intelligence include:

  • Machine vision
  • Speech recognition
  • Expert systems
  • Natural learning process

Functional testing comes under black-box testing that bases its test cases on the qualification of the software being tested. Testers test the function by feeding input in them and examining the result in the end. The internal program structure is not usually examined. 

After viewing these two definitions, you might be interested in knowing the benefits of incorporating AI in functional testing. Let’s look at the three reasons why a software testing company should incorporate AI in functional testing. 

1. Developers do not have the skills and time to test everything vigorously by hand. 

As per Sacolick, 200 IT leaders who were using AI in the test were surveyed and only 1% of them did not want to incorporate AI in the quality assurance process. 49% of them were witnessing the business benefits of using AI.

According to the report, areas, where machine learning has utmost potential, include:

  • Spotting irregularities via computer vision to detect changes in the user interface
  • Relying on natural language processing during test creation

One of the most common reasons why companies are adopting AI technology is that they know developers lack the skill set and time to vigorously by hand. Therefore, software testing companies look for tools to perform this function efficiently.

This is because artificial intelligence can assist to decrease the maintenance of apps and scripts. If testing teams adjust as per the latest paradigm, there is a noteworthy impact on testing supportability and robustness.

2. Test Automation cannot be done due to a lack of platform coverage

As per the survey, testers claimed that they get irritated testing on different operating systems, multiple browsers, and devices. Therefore, due to lack of platform coverage test automation cannot be performed. According to research:

  • 22% of the respondents claimed that the test case they write can run on any platform and requires no modification
  • 77% of the respondents claimed that they have to write different test cases for different scenarios

This surprised Donald Jackson who is a chief technology officer at microfocus. Therefore, according to Jackson CXO’s do not work on what developers are doing.

3. AI Plays An Imperative Role In Reducing Barriers To Automation

Another important function of artificial intelligence is to decrease the hurdles for those who want to perform automation. It has two reasons

It is very easy to do so.

It would not require much domain experience like traditional automation.

This means that you can get many testers involved in automation.

Furthermore, developers can also be involved in automation. They have a complete understanding of the product and they know the coding done by them. However, it is not their duty to know the process to automate. This might be because the hurdles to automation have decreased significantly.

The process of test automation during the development process and enhancing the testing scope to involve app programming, functional, security and performance interface test cases is a shift-left testing strategy.


Machine learning (ML) and Artificial Intelligence (AI) permit software testing companies to minimize the gaps present in testing. The best time to apply this is when they expand people’s capabilities and expertise to process current information.

Implementing an AI-first approach meets the requirements of leadership and testing teams by lowering the cost and time of attaining the anticipated test coverage. AI-first tools are known to eliminate the burden of maintaining various tests for various operating systems and browsers. This allows quality assurance teams to concentrate on quality instead of tests.

Therefore, all software testing companies are requested to view all these three points before incorporating Artificial Intelligence in functional testing.