News & Insights
Exaggeration and Misinformation: Generative AI in Software Testing
Not everyone is optimistic.
Blake Norrish a Sr Director of Quality Engineering at Slalom Build warns about “exaggerations and misinformation” in the AI + QA space.
He critiques statements like:
- “AI does all the testing”
- “AI can fully generate your test base” … and reminds us to separate exciting speculation from practical reality.
His key message: AI is a powerful assistant, not a replacement. Testers still need critical thinking and domain understanding to be truly effective.
From QE To AI: Leading The Future Of Software Testing
How do you transition from traditional quality engineering (QE) to an AI-driven testing strategy while ensuring long-term sustainability?
Great article from Srinivasa Rao Bittla that discusses how AI is transforming software testing by enabling dynamic generation of test scenarios, enhancing accuracy, and covering edge cases that might be missed by human testers.
How are you using AI in your testing? - Reddit
Interesting discussion where testers shared concrete, time-saving examples:
- A Playwright script refactor that used to take a full day was done in 1 hour using ChatGPT.
- One QA pro generated 30 test cases with GitHub Copilot, in the time it would take to manually write 10.
- Microsoft’s Doc Intelligence tool helped validate documentation and even found bugs during regression testing.
These are tangible examples of how AI helps augment productivity, especially for repetitive or documentation-heavy work.
Deep Dive
The Evolution of AI in Test Automation: From Locators to Generative AI : The Foundation of Test Automation
This article is a great introduction to understand the need for AI in test automation. It walks through traditional locator strategies (XPath, ID, etc.) and highlights their limitations. It sets the stage for why AI-powered solutions like self-healing locators and computer vision are not just hype, but a natural evolution that fulfill a painful need..