From Hours to Seconds: How QMetry Uses AI to Redefine Test Case Creation 

Testing has evolved far beyond scattered spreadsheets and disconnected tools. Yet even with modern platforms in place, teams still run into bottlenecks, especially when fundamental tasks like test case creation are handled manually. It involves combing through acceptance criteria, writing out each step, and reviewing everything for gaps. Repeating that across multiple user stories quickly drains time and slows progress – it’s repetitive, time-intensive, and prone to inconsistency.

This is exactly the kind of task AI can take off your plate. QMetry Test Management’s Auto Test Case and Step Generation, powered by Smartbear HaloAI, addresses this head-on, helping teams cut manual effort, speed up delivery, and maintain consistency at scale. Keep reading to see what that looks like in action.

Turn Requirements into Ready-to-Run Test Cases in Seconds 

QMetry Test Management uses AI to turn requirements into structured, ready-to-run test cases in just a few clicks. Whether your inputs come from Jira, Azure DevOps, or QMetry’s native module, the platform analyzes the requirements and generates a full set of relevant test cases – complete with step-by-step instructions and expected outcomes. 

For example, instead of spending 45 minutes manually translating a new user story into test coverage, your team can generate a proposed set of 6 to 7 test cases in seconds. Each test case is clearly structured, editable, and includes a defined summary, steps, and expected results, making it easier to review, fine-tune, and move forward with confidence. 

It speeds up test design, improves consistency, and shortens onboarding time. 

Built-in Flexibility – Structured Output from Any Input 

Not every team works from fully documented user stories, and QMetry’s AI-powered test case generation is built with that in mind. Whether your requirements are detailed, loosely written, or still evolving, QMetry can generate clear, structured test cases that save time and support consistency. 

The platform can analyze the content and generate step-level test cases with a single click. Even without a formal story, a plain-language input of 30 words or more is enough for QMetry to understand the context and create meaningful, editable test cases, complete with steps and expected results. 

It also works the other way around: if your team already has a test case missing steps or descriptions, QMetry can fill in the gaps using the surrounding context. 

This level of flexibility helps teams standardize faster test design across a variety of inputs – whether working from specs, short prompts, or existing artifacts. 

Keep Test Cases Clear, Current, and Consistent 

Creating test cases is only part of the challenge. As products evolve and teams scale, existing test steps can quickly become outdated, inconsistent, or difficult to follow, especially across contributors and releases. That’s where QMetry’s AI capabilities help maintain long-term quality. 

With the “Improve with QI” feature, teams can instantly refine test steps to improve clarity, structure, and readability. Whether a step needs to be rephrased, simplified, or rewritten entirely, the AI can suggest improvements in place – directly within the test case editor. No switching tools, no added friction. 

This makes test case maintenance far more efficient. Teams can clean up legacy test steps, standardize language across projects, and ensure instructions remain clear even for new testers joining midstream. It’s a simple but high-impact way to improve productivity, collaboration, and test case quality over time. 

Watch the demo to see how your team can cut hours of manual work down to seconds using AI in QMetry. 

Why This Matters More Than Ever 

AI-generated code and faster release cycles are raising the bar for QA teams. But expectations are rising without additional time or headcount, leaving less time for planning, more complexity to cover, and no room for manual bottlenecks. Traditional test design simply can’t keep up.

That’s why capabilities like AI test case generation and intelligent step suggestions aren’t just a nice-to-have anymore – they’re essential. 

They help teams: 

• Speed up test creation without sacrificing clarity or coverage 

• Maintain consistency across distributed teams and growing test suites 

• Onboard new testers faster with clear, structured examples 

• Allow senior testers to focus on strategic, high-value testing 

Most importantly, they enable QA to stay proactive. Instead of reacting to missed scenarios and late-stage bugs, teams can stay ahead of risk – without burning out. 

As software delivery gets faster and more complex, testing must evolve just as quickly. QMetry gives your team that edge, with AI that keeps quality in step with development. 

Manual vs AI-Powered: What’s the Real Difference?

Ready to move past the bottlenecks? 

Start your free trial of QMetry Test Management and put AI-powered test case creation to work for faster test design, better coverage, no extra headcount.