AI is Shaking Up the Testing Landscape
By Intellias Head of QA Center of Excellence Lucy Suslova
Testing is no longer just about finding bugs but transforming how we ensure quality. With the introduction and development of AI, testing effectiveness has evolved even further. So, let's dive into how AI is shaking up the testing landscape across different industries and why it's a game-changer.?
Mobility
AI in mobility isn't just about predictive analytics. It's about crafting safer, more efficient journeys. Imagine a world where self-driving cars become the norm. AI-driven testing simulates countless scenarios, ensuring these vehicles navigate diverse road conditions with unwavering precision. The transformation goes beyond the technology; it touches the core of urban mobility and personal safety. Take ride-sharing giant?Uber, for instance. They employ AI-driven testing to simulate various driving scenarios and rigorously test their self-driving cars. This ensures their vehicles can react to different road conditions, making roads safer.
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Retail
Retailers, especially in the e-commerce realm, know that performance is critical. AI-driven testing can simulate user interactions, help identify performance bottlenecks, and even predict when your website or app will buzz with activity. A retail powerhouse like?Amazon?is a prime example. AI ensures their website can handle massive traffic surges during Black Friday sales, offering a smooth shopping experience for millions of customers.
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Financial Services & Insurance
For FS&I, security and compliance are non-negotiable. AI shines here. Consider insurance provider?Allstate, which utilizes AI to analyze and validate policy and claim data. AI assists in fraud detection, helping protect customers' assets and ensuring compliance with regulatory requirements.
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Telecom
In telecom, network quality is everything. AI crunches network performance data to predict issues before they strike. A telecommunications giant like?AT&T?leverages AI in its testing to predict network congestion and optimize data flow, ensuring uninterrupted service for its millions of users.
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The impact of AI on software testing extends well beyond bug identification. It is found to be extremely helpful in accelerating time-to-market, reducing development costs, and optimizing resource allocation.?
AI can assist in finding those elusive defects, improve test coverage, and craft complex test scenarios. This boosts user satisfaction, which is vital for companies across all industries.?Furthermore, as AI's role in testing continues to expand, it has ignited a competitive frenzy among companies vying to tap into its potential and seamlessly integrate it into their testing solutions and tools.?
According to Gartner , "The increasing complexity of applications, including microservices and support for multiple clients " is driving the adoption of AI-augmented software testing tools in the next 2-3 years. Find more insights from Gartner on?AI-augmented software testing tools. ?
Personally, my attention is consistently drawn to?Applitools ?and?Mabl .?
Mabl?focuses on end-to-end test automation, strongly emphasizing AI-driven test creation and maintenance. It uses AI to autonomously update tests when the application changes, reducing the need for manual test script updates. Meanwhile,?Applitools?specializes in visual testing, using AI to detect and manage visible application differences. It helps maintain visual test scripts by detecting visual changes but may not assist as comprehensively in functional test maintenance.?
The importance lies not in the tool itself defining quality processes but in carefully selecting the right instrument to enhance your endeavors in attaining the desired level of quality. AI-powered tools undoubtedly play a pivotal role in elevating the quality of the engineering process. They contribute significantly to achieving a higher quality standard by optimizing testing, streamlining processes, and ensuring a more robust end product.?
In a nutshell, AI is reshaping the software testing landscape, making it more efficient and cost-effective. As quality engineering teams, we need to embrace these changes and make the most of AI-augmented tools and AI-augmented processes.??Incorporating AI into testing is not merely a consequence but a strategic choice that promises to reshape industries and end-user experiences.?
As AI technology evolves, we'll witness even more possibilities for its application in testing, promising a future where we can deliver higher quality and more reliable software products. And hey, who wouldn't want that??
?P.S. Here's a personal tip from me: delving into the tech blogs of leading companies can be a goldmine of insights for keeping your finger on the pulse of the ever-evolving tech and engineering trends. Find the links throughout the article.?
Source:
Gartner,?Market Guide for AI-Augmented Software-Testing Tools 2022, Joachim Herschmann, Thomas Murphy, Jim Scheibmeir, Frank O'Connor, Andy Wang, 28 November 2022.?