Data scientist-turned-product person Noelle Saldana has experienced the "sprinkle some AI on it" request more times than she'd care to remember. Our Senior Content Advisor Q McCallum met up with Noelle to explore this phenomenon. How does this happen? (Hint: "corporate FOMO.") What should you do when stakeholders insist on implementing AI that isn't actually going to help? What about when your data scientist peers seem like they're doing this for the sake of "résumé-driven development?"
If you've been in the data game long enough, you've probably seen this before: a stakeholder or product owner approaches you with a project that's 95% done, and they'd like you to … "sprinkle some AI on it." They've heard that this "AI" thing can be useful so they want some of it in their latest effort.Data scientist-turned-product person Noelle Saldana has experienced the "sprinkle some AI on it" request more times than she'd care to remember. Our Senior Content Advisor Q McCallum met up with Noelle to explore this phenomenon. How does this happen? (Hint: "corporate FOMO.") What should you do when stakeholders insist on implementing AI that isn't actually going to help? What about when your data scientist peers seem like they're doing this for the sake of "résumé-driven development?"Ultimately, the pair work through the bigger issue: how do you make peace with companies throwing money at AI like this? And how can these companies use this approach to their advantage?As a bonus, Noelle shares how she made the move from a data scientist role into product management. If this path sounds interesting to you, take a listen.