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Why AI-Powered Test Automation Is the Future?

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Mushrooming of microservices, rapid adoption of cloud, increasing use of mobile and web-based applications, and the meteoric rise of digital transformation by organisations of every size and revenue to become digital-first have led to the mammoth increase in test automation and its speedy adoption by enterprises and growth firms alike. 

By 2027, automated testing is estimated to become a $ 52.7 billion market at a CAGR of 16.4%. While the pace of technological development augments this growth story, what acts as a balancing loop is the playing out of uncertainty in market forces, an impending recession, political instability and a simultaneous shift in consumer preferences. Keeping these in mind, it becomes critical for test automation to evolve from being just an enabler of speedy and quality releases to one that helps organisations develop a strategic edge over peers.

This is where AI-powered test automation takes the lead. With advanced built-in capabilities that allow teams to test software products faster, deeper and more reliably, AI-powered test automation resolves the trade-off puzzle (prioritising quality, speed and cost) that is used to confound tech firms before every release.

Strategic Benefits of AI-powered Test Automation

AI-powered test automation helps organisations achieve key business goals of higher ROI, better risk management and greater customer satisfaction. Following are the five significant strategic benefits of implementing it:

  1. Enhances operational efficiency by accelerating repetitive testing and precision of results
  2. Improves workforce morale and productivity by enabling them to focus on more intelligent endeavours
  3. Evaluates the ROI of test automation through accurate tracking of relevant metrics and increasing it further
  4. Resolves cybersecurity challenges by plugging in security loopholes early in the development cycle
  5. Provides real-time and actionable insights to boost the quality and scope of test automation

Let us now understand how it enables the achievement of the above business goals. On a technical level, AI-powered test automation aims to resolve the challenges posed by test automation, like shortage of skilled QE testers, cumbersome maintenance of test cases, compromising test coverage depth, especially for complex applications and struggle to improve the accuracy of repetitive tests.

Lowering IT Barriers and Aiding to Rise Of Citizen Developers

Various pieces of research on the failure of test automation adoption have highlighted the need for more skilled QE experts to build, implement and maintain test automation as one of the critical factors. AI-powered test automation in low code/no code/ codeless test automation resolves this challenge by making test automation and coding possible for business users. Democratising software development and testing reduces the IT workload for digital deliveries and makes cross-functional teams more agile and productive by accelerating the pace of digital enablement.

Easier Test Maintenance

One of the challenges faced in test automation implementation is the timely maintenance and updation of test cases. App UI undergoes frequent changes during the development phase. If the test cases are not updated simultaneously, they become brittle. In contrast, frequently updating test cases is quite time-consuming and mundane.

But not with AI. AI-powered test automation ensures that changes in application code are incorporated in test cases in real-time, guaranteeing consistent test results’ reliability. Test maintenance becomes more accessible and faster with AI. Test cases become more robust, leading to greater confidence in them by the QA team. This also means your QA and dev can focus on more productive outcomes.

More Secured Releases with Better Test Coverage

Though reasons vary, it is widespread for product teams to overlook test coverage despite its significance. This has consequences in the form of more significant bug leakage into production, lousy user experience, mounting technical debt and overlooked security vulnerabilities. AI-powered test automation can improve test coverage enormously without compromising on speed of releases. This brings multi-layered benefits for product teams – decreased technical debt, reduced bug leakage into production, addressed security loopholes and delivered a robust and breach-proof customer experience.

Improving release velocity and quality

AI-powered test automation drastically improves the accuracy of tests, especially those that are repetitive, thereby making them more reliable and less flaky. Additionally, AI can conduct these tests at lightning-fast speed, contributing to faster GTM timelines.

While test automation aids in quick and more quality releases by providing a more efficient and scalable alternative to manual releases. But the future lies in making test automation more intelligent, easier to maintain and more effective in delivering secure releases, and that’s where AI steps in. And while we write this piece, this future is unravelling itself in multiple forms. Have you witnessed it yet?

Please write to us at [email protected] for a free demo on how AI-powered test automation can supercharge your software testing.

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