#310: A Multi-Stop Tour of AI in Data and Analytics
Notas do episódio
It can be hard to hear an AI story these days without wondering how much of it is sensationalized. So, we went looking for some reality on the ground. Moe rounded up four of her colleagues from Canva—Christian Sullivan, Nina Kumagai, Jack O'Hagan, and Flynn Alexander—and we made a series of short stops with each of them: an agent that investigates metric alerts (and cut the mean time to investigate from about two and a half days to about two hours), a prompt analytics platform prototyped during an AI Discovery Week (after a year of privacy and legal groundwork), a skill that synthesizes what a company has learned across its experiments (neutral results included!), and an LLM serving as the "resident expert" interface to a Markov chain model of user journeys. A common thread? Each of them found that the AI worked a lot better once they took some of the work away from it. And, no, AI did not get final say on the episode title, despite its insistence that a certain Antipodean phrase would land just fine.
This episode is brought to you, in part, by our sponsors, Stape and Prism from Ask-Y.
For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page: https://analyticshour.io/2026/11/10/310-a-multi-stop-tour-of-ai-in-data-and-analytics/