Report: The State of Test Automation
Updated with new AI in QA insights for 2025
Prepare your team for the rapid shifts in QA as AI becomes ubiquitous. Move from AI "tests" to practical workflows that drive productivity.
Download the report now and learn what has shifted in AI for QA over the last year.
Trust in AI is surging alongside productivity gains.
Lean teams stand to benefit the most from a
no-code, AI-enabled approach to QA.
What you'll learn
Why AI in QA went from “nice experiment” to proven productivity driver in a year—and what that actually looks like in real teams.
How small dev teams are really automating E2E tests—and when they move from unit tests and manual checks to full coverage.
Why AI isn't yet saving time for most open-source QA frameworks—and where it is quietly helping teams keep suites reliable
How no-code test automation statcks up against Selenium, Cypress, and Playwright—especially on speed, maintenance, and coverage.
Why QA ownership shifts as teams grow—from devs doing everything to a mix of QA specialists, no-code users, and AI copilots.
What these patterns mean for your roadmap—how to design a QA strategy that uses AI and no-code to keep velocity without sacrificing trust.
Key insight
AI for QA isn't magic—but, used right, it removes the hardest parts of testing.
Lean teams that pair AI with no-code see meaningful velocity gains
long before they need to hire QA.
Download the guideLean teams that pair AI with no-code see meaningful velocity gains
long before they need to hire QA.