Automation testing has evolved from fragile scripts and brittle frameworks to AI-assisted, self-optimizing systems that genuinely reduce maintenance overhead, cut flakiness, and accelerate execution cycles. In the enterprise and mid-market, smart teams are stacking tools not just for automation coverage, but for cost efficiency, speed to release, and quality confidence . The tools below reflect what’s working in 2026. Why AI Matters in Automation Testing Today Traditional automation frameworks like Selenium or Playwright are solid foundations, but they still require manual script maintenance , frequent locator updates, and significant engineering effort for complex flows. AI changes that in four key ways: Self-healing locators and scripts — detects UI changes and adapts without manual edits.  Automated test generation — creates test cases from specs, PRs, or natural lang...

Selenium is often introduced as a simple browser automation tool. Click here, assert there, move on. But once you start working on real-world enterprise applications , Selenium reveals its true personality. Flexible, extensible, and surprisingly powerful when combined with the right tools. Over the years, I’ve used Selenium not just for UI automation, but as the central orchestrator in complex automation frameworks spanning image-based testing, OS-level dialogs, backend systems, performance testing, and even mobile OTP workflows. In this blog, I’ll walk you through some of my hands-on Selenium experiments , explaining the why , the how , and sharing code snippets you can adapt in your own projects. 1. Automating Conversational AI Agents Using AI Evaluator + Selenium The Problem Conversational AI agents introduce a new class of automation challenges . Unlike traditional UIs, AI responses are: Non-deterministic (responses vary) Context-dependent across turns Hard to validate...