“What we’re seeing now is that when we think about some of the friction and challenges of adoption, this isn’t a technology issue, per se. This is a people opportunity.”

–Jeremy Korst

About Jeremy Korst

Jeremy Korst is Founder & CEO of Mindspan Labs and Partner and former President of GBK Collective. He lectures at Columbia Business School, The Wharton School, and USC, and is co-author of the Wharton + GBK annual Enterprise AI Adoption Study, one of the most cited sources on how businesses are actually using AI. Jeremy also publishing widely in outlets such as Harvard Business Review on strategy and innovation.

Website:

mindspanlabs.ai

Accountable Acceleration:

LinkedIn Profile:

Jeremy Korst

What you will learn

How enterprise AI adoption has shifted from experimentation to ‘accountable acceleration’
The key role of leadership in translating business strategy into an actionable AI vision
Why human factors and change management are as crucial as technology for successful AI implementation
How organizations are balancing augmentation, replacement, and skill erosion as AI changes the workforce
The importance of intentional experimentation and creating case studies to drive value from AI initiatives
Early evidence, challenges, and promise of digital twins and synthetic personas in market research
Why a culture of risk tolerance, alignment across leadership layers, and clear communication are essential for AI-driven transformation
The emerging shift from general productivity gains to domain-specific AI applications and the increasing focus on ROI measurement

Episode Resources

Transcript

Ross Dawson: Jeremy, it’s wonderful to have you on the show.

Jeremy Korst: Yeah, hey, thanks for having me.

Ross Dawson: So you, I think it’s pretty fair to say you are across enterprise AI adoption, being the recent co-author of a report with Wharton and GbK Collective on where we are with enterprise AI adoption. So what’s the big picture?

Jeremy Korst: Yeah, let me start—now that I’ve reached this stage in life, in my career, and I look back over what I’ve done the last couple decades, it’s actually been at the intersection of technology adoption and innovation. I spent a couple of careers at Microsoft, most recently leading the launch of Windows 10 globally. I worked at T-Mobile, led several businesses there, and more recently, have been spending time really with three things.

One is through my consulting company, GbK Collective, working with some of the world’s largest brands on market research and strategies for consumers and products, working with academic partners who are core to that work we do at GbK—so leading professors from Harvard and Wharton and Kellogg, and you name it—but then also very active in the early stage community, where I’m an advisor and board member of several of those.

And so I’ve had this bit of a triangle to be able to watch technology adoption unveil both inside and outside the organization, whether it’s inside the organization, how people are using it and effectively, or outside, how it’s being taken to market. So fast forward to where we’re at with Gen AI. It’s been fascinating to me, because all of those things are happening and all of those communities. Where we started with the Wharton report was three years ago. Stefano and Tony, one of the co-authors, and I were literally just having a conversation right after the launch of ChatGPT. And of course, there were all the headlines and all these predictions about what was going to happen and what could happen. And we said, well, wait a minute, why don’t we actually track what actually happens?

And so therein started the three-year program. It’s now an annual program sponsored by the Wharton School, conducted by GbK—my research company—that looks specifically at US enterprise business leader adoption. We decided to focus on that audience because we believe they were going to be some of the most influential decision makers around budgets and strategies as this unfolded, so that’s been our focus. We’re now in our third year, and there’s lots to dig into.

Ross Dawson: