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May 6, 2022

How to Select Test Cases for Automation

Automation promises it's going to save you time and lower costs while raising quality, something that's seemingly impossible. As we learn and adopt automation, we find out that there are many ways that we can approach it. But only a few ways allow us to be successful long term and achieve continuous testing.

Too often, teams rush to automate everything they can. But that comes back to haunt them. And they run into a slew of problems.

Here, we break down which types of test cases to automate. We help you decide when a test case should be automated. And we discuss what test cases cannot be automated, or should not be automated.

Keep reading to learn more about automating your tests and how to prioritize them.

Related Reading: Achieve Next-Level Functional Testing with Semantic AI Validation

What Is Test Automation?

Test automation refers to the process of using software tools and scripts to know what to automate in software testing. This includes creating automated test cases that can be run automatically, rather than manually.

The Role of Test Automation

Good automation helps testers do their job. It's not there to replace them. It is a tool that enhances testing. Good automation should be baked into your SDLC upfront.

Automation should also be:

Focused
Informative
Adding value
Trustworthy
Repeatable

When Should a Test Case Be Automated?

A test case should be automated if the following criteria for automation testing apply:

The task is going to be repeated.
It’s going to save time.
The requirements, the test, or the task are low risk, stable, and unlikely to change often.
The test is subject to human error.
The test is time consuming.
The test has significant downtime between steps.
The test is repetitive.

These qualifications allow you to set standards for testing across the team and prioritize tests. This increases your chances of releasing on time. Most importantly, this enables you to get strong ROI on your test automation.

Which Types of Test Cases Should Be Automated?

Unit testing should take the top priority, followed by integration testing and functional testing. The types of test cases for which automation testing without coding applies have a lot of complex manual scenarios, especially those that require a lot of data or environment setup.

And we want to start automating the most valuable tests to least valuable tests. A simple scorecard can help you figure out where to start.

Make a Score Card to Prioritize Which Tests to Automate

Make a scorecard broken down features and test scenarios. For each one, you want to apply a set of criteria — your critical success factors — to judge these scenarios by.

You’ll want to ask things like:

Is this something on the critical path or something that's frequently used?
Do we require to actually test this because there's a legal issue?
Is there a lot of data and environmental setup?
Is this something that has a lot of reuse?

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Tally up the scores and that will tell you which tests will provide the most value when automated. By creating the scorecard, you prioritize tests. The highest-value ones get automated first.

Utilize Personas in Automation

Another way to prioritize automation is through the use of personas. These help us focus on the most valuable tests. Personas also guide decisions about test functionality and design.

Top 11 Challenges in Automated Testing & What to Do About Them

If we write personas into our automation, it helps prioritize features, focus on target users, and provide a consistent view of them. That way, your overall test coverage is improved and you're focused on that end user behavior.

Apply Insights from Marketing Data

You can also use marketing data to help drive automated tests. Keeping in mind what the customer is doing and how they're interacting with our application is key to our being successful. We use marketing data to understand:

The most popular devices people use.
The most popular browsers people use.
The most common flows that people take through applications.
Points where people jump off of applications because the user experience wasn't great.

This allows us to focus our testing on the people driving our business using the most popular devices.

And we can apply persona-based test conditions that use the geolocation that matches the time zones our customer base is in, using the network profile that matches them.

3 Types of Test Cases to Automate First

As mentioned above, unit testing should take the top priority for automation, followed by integration and functional testing. They should all be baked into your overall objectives for automation.

1. Unit Testing

Unit testing is the fastest method of testing and, therefore, should be the highest priority for your automation. That is because it's easier to debug. These are highly reusable tests. They are low-cost to fix, and there's a whole host of frameworks that you can use to implement this regardless of your programming language.

2. Integration Testing

Integration testing, where we're testing our interfaces or modules, should also take high priority. These tests help us ensure that everything is working as expected. When automated, integration tests will run more quickly for us and be able to give us that feedback.

3. Functional Testing

With functional testing, there are a whole host of tools and frameworks that you can use that will match your development code base. So, you should take an approach that values it as an upfront concern. Running those tests will help identify flaky ones. And we don’t want flaky tests.

4 Things to Keep in Mind Before Automating

When you’re considering which test cases to automate, you need to keep a few things in mind first. This ensures you’re getting ROI from your automation efforts.

1. Test Maintenance

You have to factor in maintenance costs. Every time we write a test, that means we're committing to maintaining that script for the rest of time or until we remove it. So, that should lead into your decision making of whether or not you actually write those scripts.

2. Your Toolchain

Often overlooked are the tools associated with automation. Are you going to purchase tools or go open source? You need to consider the tools, as well as the ancillary tools that support it. For Java projects, you can manage test dependencies with Ivy to keep your automation environment streamlined and build-ready.

And don’t forget about maintenance when making operating system upgrades or language upgrades. Remember, it’s another application to support.

3. Documentation/Implementation

We also have things like documentation, implementation, and onboarding that will take up our time. These things will continue to take up more time as people join and leave the team, as we make changes and start new projects, and more. So, it's important to take in to account all of these costs when building out automation. They should be factored into that return on investment.

4. Organizational Constraints

We additionally have some organizational constraints that are placed upon us from our company. That could be our delivery schedule, our project budget, as well as the technical skills out of the people in our office. So, we should instead try to automate based upon the frequency of use, criticality, and legal risks for our automation scripts in order to get the most value out of them. You can also use ALM tools to track automated test cases and report results in real time.

Agentic AI: Redefining Test Automation Dynamics

Agentic AI — AI that makes autonomous decisions and takes action — is reshaping how teams plan, execute, and maintain automated tests. Instead of reacting to failures after they occur, agentic AI anticipates testing needs, adapts to application changes in real time, and orchestrates workflows end to end. The result is faster cycles, lower maintenance, and measurably higher software quality.

What agentic AI enables:

Proactive test discovery: Continuously analyzes code changes, usage analytics, and defect history to propose (and create) high-impact test cases before regressions surface.
Autonomous workflow optimization: Prioritizes tests based on risk and coverage, allocates environments dynamically, parallelizes execution, and stops redundant runs to conserve compute.
Intelligent failure triage: Clusters failures by root cause, attaches evidence, and opens actionable tickets — shrinking mean time to resolution.
Continuous coverage assurance: Monitors gaps across devices, browsers, geos, and network conditions, then schedules targeted runs to maintain risk-based coverage.

Operational outcomes:

Reduced manual effort: Less time spent curating suites, fixing brittle tests, and triaging failures.
Accelerated cycles: Smarter prioritization and parallelization compress test execution windows and speed releases.
Improved quality: Early detection and risk-focused coverage lower escaped defects and stabilize CI/CD pipelines.

Agentic AI is not a replacement for your strategy; it is an execution engine that enforces it at scale. It complements solutions like Perfecto AI by amplifying their strengths — using autonomous decision-making to feed smarter test creation, drive self-healing with richer context, and optimize cross-platform runs in the cloud. Together, agentic AI and Perfecto AI deliver a resilient, low-maintenance testing practice built for rapid, reliable releases.

Perfecto AI: The Next Evolution of Test Automation

In the ever-evolving landscape of test automation, Perfecto AI stands out as a game-changer. Leveraging the power of artificial intelligence, Perfecto AI enhances the efficiency and accuracy of automated testing, making it an indispensable tool for modern DevOps teams.

Key Features of Perfecto AI:

Intelligent Test Creation: Perfecto AI simplifies the creation of test cases by analyzing application behavior and user flows, automatically generating test scripts that align with real-world usage patterns.
Zero-Maintenance Tests: One of the biggest challenges in automation is maintaining scripts as applications evolve. Perfecto AI addresses this with AI that automatically updates test scripts to adapt to changes in the application.
Advanced Analytics: Perfecto AI provides actionable insights through detailed analytics, helping teams identify bottlenecks, flaky tests, and areas for improvement.
Cross-Platform Testing: With support for thousands of devices and browsers in the cloud, Perfecto AI ensures comprehensive test coverage across platforms, geographies, and network conditions.

Why Choose Perfecto AI?

Perfecto AI empowers teams to focus on innovation rather than maintenance. By automating complex scenarios and reducing manual intervention, it accelerates release cycles while maintaining high-quality standards. Whether you're testing mobile apps, web applications, or APIs, Perfecto AI provides the tools and intelligence needed to stay ahead in a competitive market.

Bottom Line

Just because you can automate a test doesn't mean that you should. If you automate a whole slew of tests that are going to require a great deal of upkeep, then you are investing additional time and money that you may not have.

Instead, you should focus on adopting a risk-based approach, such that you're only automating the most valuable tests. Take great care in automating those most valuable features, and making sure that they're automated correctly for long-term sustainability.

Try Perfecto for Seamless Test Automation

Automated testing is key to successful DevOps. But you have to make sure you’re doing it correctly and with the right tools in order to reap the benefits.

Perfecto makes test automation, maintenance, and execution seamless. With Perfecto, teams can automate advanced test scenarios on thousands of devices and browsers in the cloud, from anywhere in the world.

See how Perfecto works across mobile, web, and desktop testing, scriptless automation, AI-driven execution, and analytics in these guided demos.

See Perfecto in Action