It is 2024 and still the age-old question regarding test cases persists: To automate or not to automate?

Much like the mythical creature Chimera, the allure of fully automated testing promising efficiency and resource savings can sometimes be illusory.

If you are one of those who is deliberating on what to do, this post is for you. We have narrowed down so much data and listed these six most important factors that you need to consider before making a decision.

Factors that Influence Automate Testing

Understanding the factors that influence the decision to automate is crucial. Here’s a breakdown that we employ at Webomates in order to make the right decision of identifying the right test cases that can be automated.

Automation Complexity

Not all test cases are created equal. Some can be extremely challenging due to complex UI components or dynamic data, but can be easily handled through manual testing. Automating such cases may require a disproportionate effort, making it more practical to opt for manual testing.

Average Script Creation Time — Ramp up & Maintenance

Automation scripting demands a longer ramp-up time and incurs higher maintenance costs compared to manual testing. Factors like no prior automation background, tool and resource selection, and the time-consuming script creation process contribute to this higher cost. Using Generative AI to write test cases is always a better option.

Desired Speed of Regression

Manual testing, constrained by human resources, faces scalability issues, requiring a significant number of testers or extending the testing period for large test case volumes. Automation in testing excels in delivering rapid regression results. Webomates’ system, for instance, executes a huge number of test cases in just 15 minutes.

Frequency of Releases

The frequency of software releases impacts the effectiveness of automation. In agile environments, where releases are more frequent, the number of modified test cases and broken automation scripts tends to be lower. Webomates’ AiHealing technology will help you in maintaining your test automation up-to-date.

Build Stability

The stability index of the code being regression tested is crucial. If automation scripts consistently break due to significant build instability, their value diminishes. Continuous breakage becomes a bottleneck, consuming resources without providing commensurate benefits.

Addition of Test Cases

This metric gauges the development stage of the product. Early in the life cycle, constant changes and additions may make automation less cost-effective. As a product matures, certain areas stabilize, impacting the value of automation. Constant rework on brittle automation scripts may outweigh their benefits.


If the question “To automate or not to automate” your test cases is still lingering in your mind, then perhaps my blog post could provide the clarity you’re looking for. Check it out!