BLOG

Back

Artificial Intelligence and its Impact on the Software Testing Industry

Posted on: 7:55 pm on 08/01/2018 By admin
Artificial Intelligence & future of Software Testing Industry

Software testing industry is becoming extensive with each passing day. Applications these days have started interacting seamlessly with other applications through APIs. With the sudden increase in the technology challenges, applications are growing in complexity which creates an incessant need for effective software testing.

Software testing is the only premeditated way where an application can be observed under certain conditions and where testers can recognize the risks involved in the software implementation. Testing, on the other hand, is gradually transitioning to greater automation to ensure maximum precision and accuracy in the journey towards digital transformation. In an attempt to make the application foolproof, the world is turning towards Artificial Intelligence (AI). This implies that instead of manual testing and human intervention, we are moving towards a situation where machines will be slowly taking over.

The AI Advantage

Simply put, AI is the science behind computers performing tasks that are traditionally performed by humans. AI provides machines with the skill to process information about its conditions and learns to adapt to the transformations. Machines are learning faster than ever given the technology advancements. The computer is fed with a huge amount of data to adapt as per a set of inputs so that it can identify patterns and logic and as a result make an effective connection between similar input and output pairs. It is through machine learning that websites like Amazon and Netflix are able to deliver targeted ads to their customers by using huge amounts of data-based on the web pages the customer searches.

Machine Learning has come a long way with people using it to drive cars without a human. AI has become quite famous in the field of healthcare also as it is used to identify cancerous tumors. As AI begins to progress, technology experts across the globe are finding ways to leverage its potential in the software testing field as well. It is only a matter of sometimes when training applications to be familiar with problems for agile and more efficient testing becomes a reality.

Why do we need AI in Testing?

Software testing is usually a time-consuming process. Artificial Intelligence is the best choice for developers looking for faster deployments with insufficient infrastructure. It is best to leave the arduous work to the AI-powered automation which leaves only 20% of the testing work to human ingenious and cognitive ability. It would ensure more fail-safe results as hand-crafted testing does not only require extensive human hours but is also susceptible to imprecisions and discrepancies. Quite the reverse, AI bots-based testing requires less maintenance and are proficient to discover new trails through the product on their own. As industries realize the advantages of AI, developers are considering it to drive automation, enable decision making, and also improve efficiency in the area of software testing.

Build Business Agility with Software And QA Testing Services

In Conclusion

Digital Transformation is becoming impossible without the implementation of new and emerging technologies. The consumer market has become dynamic, organizations that do not leverage these technologies will end up way behind in the race. Businesses need to experiment and innovate to make their product success with the end-user. This can only be possible when these technologies are tested extensively against the odds and under all conditions.

TestingXperts brings machine learning together with analytics to unleash the power of software testing and drive automation and innovation, consequently improving QA efficiencies. Our intelligent frameworks are based on industry best practices and standards, to efficiently evaluate clients’ testing maturity. Connect with our experts to understand and improve all QA focus areas across the delivery lifecycle.