Why do AI transformations depend on people, not just tools?

Short answer: Jennifer Dulski cites BCG data that 70% of whether an AI transformation succeeds depends on people adapting to the tools and working together. She says Rising Team's trainer coaches, runs working sessions, role plays by voice and runs team building.

Watch this answer from Episode 52

Watch this answer from Episode 52 (starts at 6:43) · Episode 52 notes and transcript

What was said on Built This Week

From Episode 52: She Sold Her First AI Company to Google in 2009. Now She Is Fixing How Teams Work., starting at 6:43.

Jennifer Dulski [6:42]: Okay. So one of the things that's been really interesting about this space is, you guys talk about AI all the time, and we see how rapidly the technology is changing. The thing that most companies have missed is that it's not enough to just throw tools at people. And this summer, a ton of research came out from BCG and McKinsey and Gartner and everyone who says it actually isn't only about the algorithms, the models, and the tools we give people. It's about the people. And the BCG data says 70% of whether your AI transformation is successful or not lands on whether the people are able to adapt to these tools and still work with each other. And that's what we see is that the marketplace and the workplace is just so difficult right now because every company's drive to efficiency, intense pressure around adapting to AI. So you have all this intense pressure, this workplace tornado we talk about. The amazing thing is that the science of high performing teams has not changed. So I also teach at the GSB at Stanford, and my class of what it takes to make a great leader is no different.

Jennifer Dulski [7:52]: I mean, it's different because now we use AI to help us, but the science of high performing teams are still the same. People who can give and receive feedback well, who are clear on what's expected of them, who make people feel valued and appreciated. Every company also has their own sort of values and frameworks around that. The problem is that the tools up until we had AI are just not sufficient. Right? They're they're so periodic. And the way I think about it is so I use sports analogies for a lot of things. I think about it if best in class leadership looks like some sports outcome, like running a triathlon. If I took a group of 30 people and said, I want you all to get to the same outcome, no one starts at the same point. Right? We have some good swimmers. I have some people who love to run and hate to swim, and yet what we do all the time is this. We take everybody, we put them in a single classroom, virtual or in person, we teach them all the same thing at the same time, and that's problematic because, a, they don't start at the same place, and, b, it doesn't get them out to practice with their team. So the way we thought about Rising Team is can we give people effectively a trainer that gets to know them, does an intake with them? And what we find is that we, as I said, we use these different modes to do that.

Jennifer Dulski [9:10]: So your trainer can coach you. It can do a working session, which is creating some deliverable, a script, a review, etcetera. It can role play with you voice to voice, and it can do these team building sessions. So what we have is a personal trainer who has these different modes that it can use with you depending on your need, what goal you're trying to solve, what challenge you're facing, and the system works together. So as you do more and more team building, it gets to know you, it personalizes its coaching to you and your team and your company, And then the amazing thing is that the business metrics move.

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