Nandini Srinivasan has spent 25 years in the quality industry and leads a global QA organization of over 150 engineers across the US, Canada, India, and Pakistan.

In this episode, she breaks down exactly how she built a QA AI acceleration charter, ran a train-the-trainer model, and used a phased proof-of-concept approach to separate real AI from what she calls "powerful automation dressed up as AI. 

We get into:

• How she frames quality metrics for executives
• Using language around revenue protection
• Risk mitigation
• Feature velocity instead of test coverage percentages.

She talks about the four pillars she uses to present her team's value: quality, scalability, performance, and availability.

Nandini also shares her take on the future of QA hiring, why the judgment layer will always require a human, and what skills testers need to stay relevant as AI agents take over the more mechanical parts of automation.

She is also writing a five-part LinkedIn series called "The Voice of QA in the AI Era" if you want to follow along.