Join us on November 9 to learn how to successfully innovate and achieve efficiency by upskilling and scaling citizen developers at the Low-Code/No-Code Summit. Data protection isn't something organizations can take lightly. With high-profile companies like Sephora, Meta, and Google [subscription required] getting hit with millions in data protection fines over the past couple of months, it's clear that regulators can and will penalize noncompliance. However, many organizations are still failing to keep up with their compliance obligations due to the complexity of identifying data due where it lives in the environment. The good news is that is a challenge that many providers are looking to address with artificial intelligence (AI).

Two years ago I spoke at the Women of Silicon Roundabout Conference about machine learning (ML) startups and why they were a trend to watch. It occurred to me recently that I never got to share with the wider world the interesting cases we discussed, and, alas, I am not allowed to share the full recording of the talk. It also sounds like I've been remembered more for the yellow platforms I stomped around the stage with (evidence here), rather than the actual content. So I've decided to revisit the topic, re-examining some of the original cases alongside newer startups that have since come out of the woodwork. I also work at an ML startup, meaning that we sell predictions from ML models (specifically, predictions about which customers are committing fraud).