QA has become an essential practice for businesses that are in the digital space. To achieve digital transformation businesses should embrace the latest technologies in their software development process and build a strong data engineering foundation to fuel innovation.

1. How AI Can Be Leveraged In All Aspects Of
QA Testing

2. QA has become an essential practice for businesses that are in the
digital space. To achieve digital transformation businesses should
embrace the latest technologies in their software development
process and build a strong data engineering foundation to fuel
innovation.
In this article, let’s look at how Artificial Intelligence (AI) can be
leveraged in various aspects of Quality Assurance (QA) and Quality
Engineering (QE), increase speed in software development and help
businesses achieve digital transformation.

3. According to the latest World Quality Report 2018-19 AI is going to be among the biggest trends in QA &
testing for the next two to three years, and organizations will need to develop a strategy around it. As per
the key findings from the report, ensuring end-user satisfaction in digital and DevOps transformation is the
top QA priority.
Adopting Artificial Intelligence and automating software testing has become inevitable, specially to get up
to speed on the state of QA.
AI in testing can be perceived in two ways – leveraging AI in QA activities, and testing AI-based applications
or products. In this article we will see the first type of application in detail. Whether it’s applying AI to
testing, or integrating AI with existing systems, APIs and legacy applications, there is a range of challenges
that need to be overcome.

4. Automate with AI-Powered Testing
1. AI-based testing for DevOps & Agile teams
By integrating AI with your existing Continuous Integration (CI)
or Continuous Development (CD) process, you can significantly
reduce time-to-market as there is no need for a team to manage
the entire testing infrastructure. This in fact helps creating an
amazing agile team.

5. 2. Write Tests – Faster,
Better And Cheaper
Developing patterns and test
cases to test how an application
performs, aka application under
test accurately is time taking if it
is done by a human. AI can
automatically write tests for an
application or system by
spidering, i.e., collects data,
capture screenshots and more.
Hence, AI-based testing cut costs
and save time.

6. The challenge that we commonly see in the software
development and testing process is our human inability to
fully understand and review the requirements.
The intelligent assistants understand software
requirements and limitations of complex systems, which
would support in better requirements gathering than a
human. AI also helps in collecting test requirements
based on the latest trends and marketing
competitiveness.
Example: To develop an eCommerce site, AI can help
collect and review requirements based on competition.
3. Requirements Gathering - Better Than The
Best Human

7. 4. Exploratory Testing Made Easy
Since AI is trained on the collective knowledge of all people that work in the team, they help in
identifying various scenarios effortlessly.
AI not just performs testing, but also used as background tools that capture test data, user
behaviours by navigating through an application or system and records default test cases.

8. 5. Find System Errors And New Patterns Of Failure
When it comes to analyzing logs, AI is already here. With AI, data-mining logs for errors and
performance, and identifying the root cause of problems is made easy.
Each call can have multiple sub-calls, where AI can seamlessly track and identify which part is
consuming more time. This could have been quite a challenging task for a human. Al provides
an opportunity to restrict unauthorized access.

9. 6. Reusing Test Cases
AI helps in creating well-written test cases and reuse these test
cases much faster and better compared to humans. Because
the ML-based tool crawls system or an application, collects
crucial data by capturing screenshots, measuring load time,
analysing basic UI elements and more.

10. 7. Faster Decision Making
In this DevOps world, most test decisions actually take less than
a second. It means people need to think faster, better and
smarter. Leveraging AI, hundreds of applications can be tested
faster.

11. 8. UI Regression - Visual UI Testing And Monitoring
To make sure the recent code changes have no effect on the existing
features is a painful thing. The functionality of an application and user
satisfaction plays a crucial role, because for a user the backend API
doesn’t matter. What matters the most is the User Connect. Machines
can be accurate than humans and analyse outcomes of regression
testing most effectively and effortlessly.

12. Conclusion
AI is going to be smarter than human testers. AI can do a various range
of testing tasks and cover all aspects of testing much better than
humans.