The next evolution in QA: How AI is changing software testing

The balancing act: Speed vs. quality

Shipping high-quality software quickly is challenging. QA professionals are facing pressure to test more, faster in a world where GenAI is pushing delivery – all while trying to cut costs.  

For years, manual testing and traditional automation tools like Selenium have been the standard. But both come with challenges. Manual testing alone can be slow and prone to errors, while Selenium and similar tools require coding expertise, need constant script maintenance, and are easily broken by UI changes.  

So how do you embrace automation without adding complexity? 

Shifting from scripted to GenAI testing

Test automation has long relied on scripted frameworks, where testers write step-by-step instructions in code. While this approach ensures precision, it’s also rigid. Small UI changes, like moving a login button, can break dozens of tests, leading to high maintenance costs and delays. Low-code solutions have helped bridge this gap, making automation more accessible by reducing the need for extensive coding. However, this still requires some scripting knowledge and ongoing upkeep, limiting adoption for teams without technical expertise.  

Now, AI-powered test automation is redefining what’s possible. Instead of relying on rigid, hardcoded scripts, GenAI-driven tools allow testers to describe test scenarios using natural language. The AI interprets intent, generates tests automatically, and adapts as applications evolve – eliminating the need for scripting.  

By handling repetitive execution and maintenance, AI makes test automation faster, more resilient, and accessible to manual testers. Teams can shift their focus from script upkeep to higher-value tasks like exploratory testing, strategy, and overall process improvement. 

Scripted vs. GenAI-driven tests

The scripted method ensures precision but breaks easily. If the button moves, the script fails. With a GenAI-driven test there are no element positions or hard-coded locators. The AI interprets your intent and adapts tests automatically, slashing maintenance time and keeping tests resilient. 

Why adopt AI-powered automation now?

The role of test automation is rapidly evolving. As applications grow more complex and release cycles accelerate, traditional testing methods – whether manual or scripted – struggle to keep up. AI-powered automation is shifting the paradigm, making testing faster, more adaptable, and less reliant on human intervention for routine tasks.  

By 2028, 80% of software tests will be AI-generated (IDC FutureScape: Developer & DevOps 2024). This shift is fundamentally changing how teams approach testing. Instead of spending time writing, maintaining, and debugging scripts, QA teams can now leverage AI to: 

• Generate tests from plain language: AI translates intent-based descriptions into fully automated tests, eliminating the need for scripting. 
• Self-heal tests automatically: AI detects UI changes and updates test steps dynamically, reducing flaky tests and maintenance overhead.  
• Expand test coverage with less effort: AI-powered automation allows you to run more test scenarios, catching more defects.  
• Accelerate release cycles: By eliminating testing bottlenecks, AI helps teams release faster without sacrificing quality.  
• Scale test automation efficiently: Support teams of all sizes, from those new to automation to enterprises managing thousands of tests. 

Since adopting Reflect, we have no UI errors in production. Like, 0%. It’s like we can’t miss UI things. Any issues are caught in our staging environment. They don’t make it to production.

Merom Cohen, Developer at Monday.com

AI + human expertise = The future of QA

AI-powered automation isn’t about replacing testers – it’s about elevating the role. By offloading repetitive, time-consuming tasks to AI, QA professionals can focus on the areas where human expertise is irreplaceable.  

With AI handling execution and adaptation, testers can: 

• Define smarter test strategies: Prioritize automation efforts based on risk, business impact, and evolving application needs. 
• Validate AI-generated results: Ensure accuracy, relevance, and trust in AI-driven test execution.  
• Analyze and improve user experience: Identify edge cases, usability issues, and complex interactions that require human intuition. 

No-code, AI-powered testing with Reflect 

Reflect, featuring SmartBear AI, brings no-code, AI-driven web and mobile automation to teams of all skill levels. By leveraging GenAI, Reflect simplifies test creation, execution, and maintenance, allowing teams to scale automation without requiring any coding skills. Here’s how it can help your team: 

• Effortless test creation: Write test scenarios in plain language, and AI automatically generates, executes, and refines test steps, eliminating the need for scripting.  
• Self-healing automation: AI detects and adapts to UI changes in real time, preventing test failures caused by minor updates and significantly reducing maintenance overhead.  
• Seamless workflow integration: Connects with CI/CD pipelines, test management platforms, and bug-tracking tools, ensuring a smooth, automated testing process from development to release. 

Experience the power of AI

AI-powered automation isn’t the future – it’s happening now. With Reflect, you can scale test automation effortlessly, minimize maintenance, and deliver high-quality web and mobile apps with confidence.  

Ready to transform your testing? Try it free!