Noelle Russell uses a tiger analogy to explain AI adoption: the "baby-tiger" phase of excitement after ChatGPT's launch skips practical questions about scale, data ownership, and security. Asking these questions early lets organizations build responsible governance before deployment.
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I do think it's about making AI work for us responsibly, which is the theme, the crux of your book. And I love the subtitle, "From Enthusiasm to Execution." Tell us a little bit about that.
Yes, absolutely. And you'll notice on the COVID of the book is a tiger. I have this analogy that actually came to me when I was working at Microsoft. My role was to really help researchers take their products and put them into production. And what I saw in those early days of taking products and giving them to users is exactly what we ended up seeing. We saw the same thing happen as ChatGPT unleashed into the world. People got excited. They were like, you know, I always encourage people to just think about the first time you used a large language model. You're like, well, that's pretty good. I can't believe it did that. That's pretty awesome. And I call that kind of baby tiger mode or like the peak of enthusiasm. Like you're like, This is amazing, everything's awesome. But very few people— we're actually starting to see this happen now at scale— is like, very few people in this stage of like baby tiger mode, they're not really asking important questions like, hey, you know, how big is this thing going to get? And where is it going to live? And how— what does it eat? And how much data is it going to need? And where, you know, what happens if I don't want it anymore, right? We can think about many organizations that are failing and they have massive amounts of critical personal data, what happens to that data? Who owns that now? But if we ask those questions at the beginning, we can create mitigations, we can create security.
