AI didn't cut the work. It revealed more | Andrew Weaver, VF Corporation

Russ Fradin (0:00)

How do you think about kind of measuring productivity in this AI world?

Andrew Weaver (0:03)

There's a lot of upfront excitement, and then you have to kind of step back and say, are we just trying to reinvent what we're already doing? And then, should we be doing that, right? We're kind of seeing some companies look at it like, where can we just deploy AI? Where can we deploy this technology? And what we're trying to do with VF is like, how is work, you know, breaking down, and where can we use AI to help with that, versus just this broad, like, just go use it kind of approach? So the goal isn't really just to deploy, but to create better work outcomes for the employees.

Russ Fradin (0:37)

Welcome back to AI Impact. Today, Andrew is joining me. Andrew, thanks so much for joining us. Could you tell me a little bit about yourself and your role at VF?

Andrew Weaver (0:46)

Yeah, sure. Thanks, Russ. So I'm based in Raleigh, North Carolina. I lead the Workforce Intelligence team for VF, and that includes people analytics, employee listing, workforce planning, and now AI transformation. So I've been in the people space for over 20 years, seeing the space really evolve and transform over the last few years. And at a high level, my team's focused on how we use AI and data together to really drive decision-making. I think like a lot of companies, we're still in the early stages of our AI journey, but really optimistic about the future of it. Even, again, just the changes in the last few weeks and months have just been incredible. So really looking forward to the conversation. I think it's super relevant as companies are trying to just navigate this stuff, right? I mean, how do we implement these tools?

Russ Fradin (1:32)

So you've worked in a lot of different types of companies, some kind of modern founded within all of our collective lifetime. VF is, I think VF was founded before 1900, if I remember correctly, owns a collection of amazing iconic brands, North Face, Timberland, things like that. What has it been like going from a kind of relatively more modern technology focused company like Red Hat to a place like VF that's been around for so long in a very different type of industry for your role?

Andrew Weaver (2:01)

Yeah, honestly, I think it's a lot more similar than people might think. I mean, yeah, retail is different from health care, right? And manufacturing is different from technology, but it's kind of like just on the surface level. I mean, in our space, every organization is really built on workflows, processes, decisions, data, which is our world. Communication, knowledge sharing, and AI shows up differently in those depending on the company, but the building blocks are all the same. So it hasn't really been too different. I think, especially with this role and looking at AI transformation more broadly, a lot of those components, again, don't change. You have the human factors, right? With any transformation that's basic transformation, which is kind of funny to say, because transformation is really hard. You've got some of these common elements, right? You still need leadership buy-in, executive sponsorship, change management. That's super big in this AI transformation world that we're living in. Looking at different things on learning and enablement and communications. So I feel like over my career, I've worked in a lot of different industries, but the audience changes, but the core narrative really doesn't.

So I kind of just navigate from different operating models a little bit, and then the technology is just changing along with it. So it's not too different in our world.

Russ Fradin (3:23)

For your company, for VF, kind of very large company, people all over the place, has AI transformation been something top down, your CEO and board said, hey, we have to do this? Was it bottoms up or kind of some departments more AI forward than others? How has that really played out in practice and how do you support it centrally?

Andrew Weaver (3:40)

Yeah, that's a great question.

You know, broadly speaking, I think AI is really this large enterprise initiative, right? It requires a lot of stakeholders and I'm not sure that any company has like the single owner because you see this stuff just showing up in every function. It kind of just touches all this other technology. So it's almost like trying to hold on to water sometimes. You're just, you know, how do you get your arms around something like that? Something that changes so quickly. So I think a lot of organizations still have kind of the top down and they have the enterprise level, but they're starting to do what we're doing and spinning up these like domain experts in functions, right? And especially in our world where you take Workforce Intelligence and then combine it with AI, it's a really interesting, you know, combination because the people analytics teams kind of sit in this unique intersection, right? They're kind of like almost a control tower because we've got access to the people analytics data and you're kind of doing basic attrition analysis, things like that. We've got workforce planning, employee listing and now AI.