Scaling Mobile Test Automation with Appium and AI: Real Lessons from KINTO Technologies

When KINTO Technologies scaled mobile test automation infrastructure, our Appium-based testing
reached a breaking point. Each test run took two hours per platform—resulting in four hours of test
execution per project across both iOS and Android. With three projects, this amounted to twelve hours
of test execution per full run. This created a release bottleneck: flaky tests eroded developer trust, and
our QA team was overwhelmed with maintenance work instead of exploring new features.
This talk reveals how we transformed our testing infrastructure—not by abandoning Appium, but by
evolving it. Through systematic refactoring and architectural improvements, we made our test suite
faster, more reliable, and significantly easier to maintain. In 2025, we amplified these gains by
integrating AI tools such as Claude, GitHub Copilot, and DevinAI into our daily
workflows—streamlining code reviews, automating documentation, and improving our feedback loops.
However, this journey was not without setbacks. We will share our failures: the AI hallucinations that
generated broken test code, the over-automation that initially slowed us down, and the cultural
resistance we faced when introducing AI into established workflows. These hard-won lessons shaped
our approach to building scalable quality systems.
Attendees will learn our framework refactoring strategies, see real examples of AI-augmented QA
workflows, and discover how we built a sustainable testing culture that scales across time zones, teams,
and technologies. This is not theory—it is battle-tested experience from real production mobile testing
across Android and iOS.