If you remember a decade ago, test automation was all about defining locators, managing test data, and writing scripts to mimic user interactions on browser. Fast forward to today, nothing has really changed.

We are still doing same but we replaced excel with a fancy interface.

Honestly, AI-powered automation tools have turned into a gimmick, it just wrapped the same old process in a fancy UI and took us right back to where we started. Its a joke that no body admitting it in the industry and silently accepting it as innovation.

Back in 2010, the automation frameworks were designed to work with keywords stored in a excel. It served as a facade to selenium code. Though this had a few cons but conceptually it was doing same which we are doing now in so called AI-powered automation tools.

The fundamental problem remains unchanged, browser based test automation is still about executing predefined scripts, whether stored in an Excel sheet or an AI-generated workflow.

The industry keeps rebranding old solutions with new buzzwords, throwing in machine learning, AI, and low-code/no-code platforms, but in reality, these tools still rely on the same principles established years ago. The marketing departments push these as innovations, when you use these solutions, you face same challenges.

We have spent nearly two decades buying the buzzwords: scriptless automation, AI-driven testing, self-healing tests, autonomous test execution. But ask any test automation engineer, and they will tell you, none of these have eliminated the fundamental manual effort required to build, maintain, and debug automation suites. In fact, none of these solution tackled the flakiness problem.

So, what has really changed?

Not much. We are still babysitting our test suites, fixing flaky tests, dealing with element locators breaking, and struggling with test data management. AI hasn’t solved these problems; it has made it worse by making tools unintuitive.

My humble request to managers and decision-makers, please understand that AI isn’t mature enough yet to solve software testing challenges. Right now, it’s too early to invest in these tools. These are mostly the same old tools repackaged with fancy AI taglines that don’t actually make a QA’s life better. In fact, they often make life harder. Because after a certain point, these tools become obsolete, hard to maintain, and more of a burden than a solution.

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