You know you need to automate your software testing. The question is no longer “if,” but “when.” So what’s the right time?
There are clear signs that your operation is ready to take this step. We’ll show you what they are, what to evaluate before getting started, and how to avoid the pitfalls that cause many automation projects to fail in the first few months.
Signs it’s time to automate
1. You’re repeating the same tests manually
If your team spends hours every week testing the same critical flows, you’re burning time that could be invested in exploring new scenarios. Manual regression works when the product is small, but it stops making sense when you realize you’re testing the same login, the same checkout, the same registration for the tenth time.
According to the World Quality Report 2023-24, teams that automate regression tests save an average of 40% of the time spent on test cycles. That time goes back to activities that truly add value, such as exploratory testing, validation of new features, and quality analysis.
2. Your releases are getting slower
When testing becomes a bottleneck, the entire development pipeline gets stuck. A developer fixes a bug and needs to wait days to confirm the fix worked. Ready features sit idle waiting for validation. Feedback takes so long that the cost of fixing problems skyrockets.
If you’re delaying deploys due to lack of testing capacity, the time has come. Automation will unlock a more consistent and predictable delivery flow.
3. The team needs to grow
More developers mean more features. More features generate more scenarios to validate. In this scenario, hiring manual testers at the same pace as the development team grows is neither sustainable nor desirable.
“I see many companies come to us when they realize that doubling the QA team doesn’t solve the scaling problem and is expensive,” explains Gustavo, CTO of TestBooster.ai. “Intelligent automation allows the team to grow in impact without growing proportionally in headcount.”
4. Bugs in production start appearing frequently
No one can test everything manually in every release. When manual coverage becomes insufficient, bugs escape, and bugs in production are costly. According to the Consortium for IT Software Quality, poor-quality software cost American companies $2.41 trillion in 2022, considering rework, downtime, and lost productivity.
If you’re putting out fires frequently, automation can work as a safety net that catches problems before they reach users.
What to evaluate before starting?
Your application has a relatively stable base
You don’t need to wait for the software to be perfect. In fact, it never will be. What you need is to identify functionalities that have moved past the phase of drastic changes. Is the authentication module already consolidated? Has the payment flow not changed in months? Start there.
You have documented test cases
You don’t need everything mapped out in detailed spreadsheets. What matters is having clarity about what needs to be tested. If your team already executes manual tests following some script, even if informal, you have enough material to get started.
Begin with the flows every tester knows by heart. Those that are executed in every regression cycle. These are the perfect candidates for the first automated tests.
There’s leadership commitment
Automation requires an initial time investment. The team will need a few weeks to set up the environment, create the first tests, and adjust the approach. This time needs to be in the planning, and leadership needs to understand that the return comes in the medium term.
Where to start with automation
Not every test needs to be automated at the beginning. Start with flows that generate the most impact if they break: login, checkout completion, user registration, financial operations. Also look at functionalities that break frequently. If a specific module always shows regressions, automate its coverage. You’ll catch problems earlier and with less effort.
Choose between 3 and 5 scenarios for a pilot. Execute, analyze results, adjust the approach. Only after validating that your strategy works should you think about scaling. The pilot also serves for the team to learn the tool, understand limitations, and develop best practices.
Depending on your tool choice, prepare to rewrite dozens of scripts. This is why many teams give up on automation after a few months. The time spent fixing broken tests consumes the productivity gains automation should generate.
The good news is that AI-powered automation solves this problem. Intelligent tests understand the application’s context. If you changed the appearance of the login button, but it still functions as a login button, the test continues working.
Common errors when starting
- Wanting to automate everything at once: it’s tempting to look at the complete suite of manual tests and want to automate everything. Resist this temptation. Automation is a gradual process, and trying to do everything at once leads to team burnout.
- Automating unstable processes: automating a feature that changes every week can be throwing money away, depending on the tool. Leave highly volatile features for manual testing until they stabilize.
- Underestimating setup and learning time: traditional code-based automation tools have a long learning curve. Your team will need to master a programming language, understand testing frameworks, learn about selectors, waits, synchronization. All of this takes time.
AI-powered platforms drastically reduce this barrier. TestBooster.ai, for example, allows professionals to create automated tests without writing code, accelerating adoption and reducing dependence on specialized technical resources.
The role of AI in modern automation
AI-powered automation understands your application’s intent. “Log in with these credentials” is processed intelligently, adapting to visual changes as long as the behavior remains the same. Tests focus on what the application should do, not on how elements are named in the code.
This means less maintenance, more resilience, and teams spending time testing, not fixing tests. According to Gustavo from TestBooster.ai, “clients report up to 70% reduction in test maintenance time after migrating to our platform. AI doesn’t eliminate the need to update tests, but it makes those updates much less frequent and simpler.”
So, when to automate?
If you’ve identified at least two or three signs mentioned in this article, it’s probably time to start. You don’t need ideal conditions, perfect software, or a huge team. You need clarity about critical flows, commitment to invest initial time, and the right tool to avoid creating more problems than solutions.
AI-powered automation exists precisely to reduce the barriers that have always made traditional automation difficult to start and even harder to maintain. With AI, you eliminate most of the technical complexity.
Want to evaluate if your operation is ready to automate intelligently? Talk to our specialists and discover how to start automating without worrying about constant test maintenance.
