Over the weekend, I spent 45 minutes FaceTiming my mom to help her sign into HBO to watch NCAA men’s basketball. I felt like a mechanic explaining one-time passcodes, the online-streaming model, and so on. 

But once she got in? Literally no stopping her. She watched the game live while texting with family. She immediately built out her queue of films and TV shows. It’s an example of how adopting new tech, even if intimidating, can be worth your while.

Today, we go over insights into adopting AI technology with Kellogg faculty. Then, Guy Aridor pulls back the curtain on Netflix’s recommendation system.

Automation, answers, and advice. Oh, my. 

Business leaders are increasingly asking, how do we drive AI adoption across our organization? Adopting and advocating for any new technology has its pitfalls. 

Luckily, Kellogg professors and AI experts Matt Groh, Julio Ottino, and Brian Uzzi recently sat down for The Insightful Leader Live webinar to offer tips for using these tools more effectively on three levels.

First: automation. Think “set it and forget it” tasks, like scheduling social-media posts or sending email reminders. “AI can just do stuff for you without any supervision. And that’s often what many people think about,” says Groh. 

In one success story, Groh points to the way Amazon uses AI for basic coding. “[Coding] would often take, let’s say, 50 days to do certain specific tasks. That goes to five hours [with AI]. And because that happens for many, many employees, they essentially estimate a quarter-billion-dollar annualized savings,” Groh says.

Next up: answers. Yes, AI seemingly can answer any question you throw at it, but you should still verify and reflect on each one. In other words, treat AI as a collaborator that can ideally widen your thinking. When Uzzi was researching a rebuild of his home’s foundation, he kept coming up short when discussing the project with contractors. So Uzzi turned to AI. “I basically gave a lot of textual information to a chatbot, and it came back with a detailed engineering estimate,” he says. “It was pretty close to what the engineer gave me two months later.”

And lastly: advice. Instead of deploying AI to expedite a process or fill in holes, now we can ask AI to help solve problems. But you have to ask the right questions. Take Groh’s research into how managers use AI to help them communicate difficult news, like layoffs. AI gives us a way to rehearse tricky conversations before they happen, while getting feedback to improve, which “can significantly increase people’s ability to communicate such that others feel heard,” Groh says.

For more, you can watch the full webinar or listen to a podcast version at Kellogg Insight.

The lure of Netflix

Like my mom with her adoption of HBO, my four-year old has taken to Netflix like a duck to water. And he’s in love with KPop Demon Hunters, the streamer’s now Academy Award–winning movie of 2025. But what exactly made it such a hit?

Was it the content itself? Or was it Netflix’s algorithm giving the movie a boost?

Guy Aridor developed a mathematical model that disentangles the influence of the platform’s recommendation service from the underlying value of the content. The model helps Netflix determine how many additional viewers different shows and movies attract and offers a data-driven perspective on which recommendation systems help the most.

Unsurprisingly, the current Netflix recommender beat alternatives such as random suggestions that show only the most-popular content. But the current system also performed best on another measure that Netflix values: increasing content diversity, or the overall variety of shows and movies that users watch.

“Research from other streaming platforms shows that more diverse consumption is strongly correlated with good long-run outcomes from a consumer-satisfaction point of view,” Aridor says. “So it’s important that the recommendation system isn’t just inducing people to all watch the same types of titles.”

The model also revealed that proven hits like Emily in Paris and Stranger Things don’t need much additional promotion and that obscure shows and movies don’t connect outside of very specific audiences. Instead, it’s the shows and movies in-between that get a lift from the recommendation system.

Read more in Kellogg Insight.