Don't wait for a mandate: How to lead bottom-up AI adoption

Sarah Heller: Where we are most challenged is not having an enterprise mandate and we're not waiting for an enterprise mandate of you're going to use AI for this thing in this way, or we have a very deeply convicted hypothesis about how AI is going to shift things, and we're able as a company to move that way. My work started way before we even had a single LLM-approved tool that we could be using.

A lot of it is asking the powerful questions to get them thinking differently because it started with, oh, AI is helping me with this thing, and then to get to that more operationalizing AI, it's how is your team using it? What does that mean for how work needs to shift? How does that change where you need the product managers to focus on, especially if they now have insights much more frequently that they would never have had the capacity to do before?

The practical execution of that is designing the sessions to meet the groups where they're at, and that goes back to the leaders as the force multipliers, and so all this work is creating that container for leaders to think through these things so that they can bring them to their team.

Dan Hibberd: Sarah, welcome to the Shapeshifters Transformation Series. We are excited to have you with us. I'd love to start with a couple of quick questions, if you could give our listeners a sense of who are you and what's your role at Dolby Laboratories?

Sarah Heller: Thanks so much for having me, Dan. It's such a delight to be here. I lead organizational effectiveness at Dolby, and that really sits at the intersection of strategy, leadership, and org design. So a lot of my work is helping leaders navigate complex changes, which could range from organizational strategy or designs needing to change because the strategy is changing, or going downstream and looking at how teams operate, or thinking about the capabilities that they need to deliver work in the future.

So to do this, I partner closely with our People Business Partner team, as well as their senior leaders, and I also have the pleasure of leading select strategic talent and leadership initiatives that are tied to business priorities like

Sarah Heller: setting leadership expectations for the company. And more recently, and not surprisingly, a lot of that work has shifted to helping leaders think through AI and how AI is actually changing their work and their teams. And where I'm starting there is, how do we help leaders think about AI's impact and the value that they can get from it?

Dan Hibberd: Fantastic. And I'm looking forward to double-clicking and going deep on the work that you're doing to support the transformation there. And given the amount of change that organizations are experiencing, my sense is there's no end to the work that you could be doing at the at any given point in time. Before we dive into the work that you're doing to support AI adoption, how would you explain what you do to a fifth grader?

Sarah Heller: I work with engineers. They're people that build things, like the technology in the cell phone that you have, but my role is a little bit different. My role is to help make sure that the people that are building that technology are getting what they need to be able to do their job well. And there could be a whole bunch of things that I work on, but the most exciting part is that I get to work with leaders, the people that are responsible for making all of these new innovations come to life.

Dan Hibberd: That's a fantastic articulation. As a father of three young girls, I feel like you've done a good job in explaining that.

Sarah Heller: I have a four-year-old, and she's never asked what I do, but I have had the opportunity to bring her to my office. Highlight of her whole year. It's one of the few things I think she remembers, is coming to my office and getting to watch a movie, because Dolby enables amazing entertainment experiences through different technology and formats, including the movies, of course, which most of us remember from our youth. And so we have a cinema on-site, so the kids got to come and watch a movie. They got to eat snacks and see our beautiful building. So, that's how she thinks about my work, is I help make something about the movies, even though my day job is far from that.

Dan Hibberd: That's awesome. I was going to mention, most of my interaction with the Dolby b-

Dan Hibberd: and has been exactly that, the star of movies. Um anyway, let's jump in. So, at the moment, AI is just reshaping how every organization operates, how work is done. There's a huge transformation taking place and every organization is at a different kind of point in their maturity. And one of the biggest challenges I think a lot of organizations are facing is just where do you begin? Where do you focus your initial efforts? And so I'd love to hear from you, Sarah, where have you begun and where has been the, I guess, the direction of focus and what drove that choice?

Sarah Heller: I love the question because there are so many things you can do. And initially, with every company being on their own journey, our company, I think, is further ahead in the sense that we are a technology company. A large proportion of our workforce are engineers and researchers with advanced degrees that were really early users of AI. But overall as a company, we didn't have a company strategy, a company tool, a set of expectations.

So, where I started with is the angle that I knew best was leaders. And what how is this impacting leaders, and more specifically, what do we need from our leaders? And so I was coming off a body of work that was looking at leadership expectations and what does it mean to be a leader at Dolby. And that was all really before generative AI took off that we were focusing on that work. And so I asked, "What is the current state, and what do our leaders need?" And that's really where I started.

And what I learned was that was not actually, now in hindsight, not that different at my company than what I think other companies experienced a year ago, which is that you're reading about AI and all of its advances in technology, possibilities that were not there before that are allowing more growth and potentially impacts on the workforce. But then your experience day-to-day is, again, no tool, no mandate, no set of clear guidance of what AI is for, for example. And we saw fragmented experimentation. AI largely used for individual productivity, not for rethinking or re-

Sarah Heller: imagining work. And I also saw a difference between what the people team was focused on, which was reimagining the work in service of achieving the business strategy and growing the business, contrasting that with where the business actually was, where most people were just trying to figure out what it even meant in terms of efficiency or very specific things in their role. So we had uneven adoption and there was a lot of confusion on what to do. And anyone listening to this podcast won't be surprised, but it was really the theory of leaders as a force multiplier that's been the through line of all this work that I've been doing is that we're only as successful as our leaders. And so that's why we set the leadership expectations and that's why we're constantly looking to define what who are the leaders that we need to build the future.

And with AI, it becomes especially important. And the question I asked is, how do we build AI driven leaders who can meet the moment? And really, what is AI driven leadership even? So that's a long winded way of saying I got started with just really trying to take a small parcel that I felt I was equipped to tackle. And I also worked in partnership with our counterparts in IT as they were thinking about what's the tooling and enablement. So I helped ensure that leadership was a horizontal to our enablement strategy. As we're thinking about all the tooling and the different trainings and things that would need to happen, I pushed for leadership as a horizontal.

And that work was in some sense not that different than any leadership development effort where I spend a lot of time listening to the business and I actually took a step back, had a lot of conversations to learn what their perspective of AI was, and to help hone that story around what are the gaps that I'm seeing. And also figuring out where is there points of energy that we could latch onto, and I can come back to an example of of how we use that.

But the other side was spending a lot of time with external folks and really understanding how AI is changing the work, changing leadership, what other leading companies are doing. And it was my own learning curve using AI differently just alongside all the leaders. And so there's that personal learning journey as well as practical that might be a little bit different

Sarah Heller: than I think some leadership developments efforts that myself and my peers have led before. So an example of where I started is when I said follow the energy, is we had one leader especially that was in a different part of the business that had much more urgency around AI adoption in service of meeting their business numbers. And so he made a goal that said we're going to be an AI-native organization without necessarily knowing yet what that meant or what they had to do. And so that's the leader I started with engaging. And I knew some people that had done work innovation with AI at other companies, and I was actually able to bring in an external thought leader to help him leader to leader think about how he should be framing the work and what he needed to be doing to really enter into this longer journey where there's not an end in sight.

And so that first step was just having that first set of conversations, helping him bring his leadership team together. And I will say it would not have been possible without this partnership between HR, IT, and the business working together. And so I think that's always the ideal when IT and HR especially are able to come together and help a business leader like that.

Dan Hibberd: And I think with something like AI, it's touching every part of the business. It's one thing to understand what it is and have tools available, but the real efficiency comes when teams are working together using AI and also when you're thinking about the entire ecosystem when you're designing your change process and supporting adoption.

I'm curious, a lot of organizations would resonate with the maybe ad hoc nature of the experience to start with. Practically speaking, what was the process of building alignment and creating that initial strategy about AI adoption?

Sarah Heller: Everyone will appreciate that there's this healthy tension between the scale and the more bespoke custom nature. And so we've had to play both of those and what we saw was going to work best for our company

Sarah Heller: given the size that we're at and the leaders that we have is something more bespoke that's going to be very custom to what each business needs is going to be less efficient, but the way to actually get our foot in the door. And so when you think about this ecosystem approach, what I had in my head is a bunch of bubbles and arrows and all of these different interventions and things that myself and people across HR and IT were able to deliver that would all be self-reinforcing.

And it helps that Dolby is an ecosystem business. We help enable the entire content ecosystem, from content creation to distribution to ending in a device. And so I was trying to think about how you can design a leadership development ecosystem that is also tackling the bottoms-up, the tops-down, and going where the most work is needed to get to the result. And it's messy, and it may look different than you thought. But where we landed was, what's about 60% shared spine of certain language, or expectations, or tools that you would expect everybody across the company or all leaders to be thinking about? And then what percent is tailored? And it might even be like 40% of what a certain business needs is 40 40% of that is going to look really different. And, as I mentioned, we have engineers and researchers that we can't come to something too basic with them on the leadership front in AI because they think that they've already done that or they've surpassed it and they're doing a lot of their own work there. And then we have other corporate functions that have barely acknowledged that AI exists. So you have to run the gamut, and, again, going with where the energy is, but also figuring out what are the questions that leaders need to answer?

And that's where that first strategy is starting to form is creating the container for each leadership team versus a horizontal ELT at the top, answering their set of questions and bubbling that up versus, again, the traditional, and sometimes most efficient way is, you get an ELT aligned, they have a clear perspective and a set of things, and they all go off and work in their own ways.

Sarah Heller: have to create the energy within each group, and help bubble that up to the top level.

And so some of the questions, the the simple-to-say, but really difficult-to-answer questions that we've been looking at are, how is AI changing my business? Where does AI have the potential to generate new value? And really focusing on the augmentation side of what can we create new, better, different, versus efficiency and productivity.

And then, where we still need to make more traction, but we're trying to set the stage for, is, okay, where does our then our work need to change to realize those gains? And then you get into the, what do we need to completely rethink: talent, skills, and culture?

So we're still at the top of that funnel of, how is AI changing and, based on the external as well as what's happening internally? And then, where are the innovations paying off, and what does that tell us about the work of the future?

So it is not linear. Some of the strategy is just starting with the big questions. But, again, I'll go back to creating the container. And, Dan, I can say a little bit more about the approach, or if you have a follow-up question.

Dan Hibberd: I'd love to know a bit more about the approach, and I think it's interesting as you're building alignment, so much of the execution and the impact is down to what does it look like as it translates into day-to-day business and teams. And I love how you're in this approach of, not a one-size-fits-all, but helping each business unit or function, meeting them where they're at, and helping them contextualize where there is opportunity and value at each level.

So, yeah, I'd love to hear a bit more about the practical execution and how it's impacting with day-to-day.

Sarah Heller: Yeah, and that goes back to the leaders as the force multipliers. And so all this work is with leaders in whatever organization, whether it's at the very top or in the middle, is helping them set their team up for success in the future.

And so where we're most challenged is not having an enterprise mandate. And so I'd say the approach is we're not waiting for an enterprise mandate of, you're going to use

Sarah Heller: use AI for this thing in this way, or we have a very deeply convicted hypothesis about how AI is going to shift things, and we're able as a company to move that way. My work started way before we even had a single LLM-approved tool that we could be using. So, the work starts even when you don't have that. It makes it harder. And a lot of it is that I think being part of the business partner team is taking a cue from them, which is asking the powerful questions to get them thinking about AI differently, because it started with, "Oh, AI is helping me with this thing." And then to get to that more operationalizing AI, it's how's your team using it, and more of the questions going deeper into what does that mean for how work needs to shift? How does that change?

If you look at a product management role, you're telling me that AI has these potential engagements with customers, oh, how does that shift where you need the product managers to focus on, especially if they now have AI pulling insights much more frequently that they would never have had the capacity to do before? What does that say about the role? And oftentimes, there isn't answers, but we've at least planted the seeds. And if you have enough people continuing to repeat that while they're also getting the external info from their peers, in the news, it starts to trickle down.

The practical execution of that is what we mentioned, is designing the sessions to meet the groups where they're at. And so, again, creating that container for leaders to think through these things so that they can bring them to their team. And I think that if we actually get to a place where we have a clearer set of expectations, that continues to help, again, reinforce leaders to understand what is expected of them. But we did start this approach without a clearer sense of knowing, "My role as a leader is to do X, this means Y." It's a lot of helping them shape the narrative. But we're there as thought partners at the top level to help them think about that and cascade it down.

Dan Hibberd: I love this idea as leaders as

Dan Hibberd: multipliers because I think they are pivotal to the success of any transformation. And at the end of the day, you know, AI can help to create efficiency and help with speed, but it's also dependent on how well teams are working together to use AI, how aligned they are about the use of AI, how they're surfacing opportunities as a team to build efficiency and improve the way that we work. So I want to use that as a bit of a pivot point. Obviously, there's all of these amazing gains that organizations can get with AI. At the same time, sometimes AI can make work feel more individual. I'd love to hear about how intentional are you about maintaining human connection and shared learning as part of the strategy.

Sarah Heller: Yeah, we're very intentional. And if our goal is to help leaders continuously adapt to all this change that's happening, it's all about tapping into their innately human strengths. That's curiosity and learning. And yes, a machine or a computer, it can teach you anything and everything, but connection still plays that critical role of the learning by doing and role modeling. And again, I think a lot of people listening are familiar with or thinking about how AI is something that you actually have to learn from doing. You've heard a lot of analogies of if you're trying to lose weight, you can't watch a video about running on the treadmill, you actually have to get on the treadmill. That's not my favorite, but that's just the one that comes to mind that I heard a very wise person say.

And I think that the learning in a collective is going to be really powerful because learning has been super fragmented. And so if you just have individual learning, it stays isolated and it doesn't scale itself. Whereas you have leaders coming together, they're not only helping each other, but they're also getting practice role modeling some of the behaviors that they need to be bringing to their team. And they're also getting a positive peer pressure influence of, "Oh, this person is doing this thing. That's something interesting I could try." So it does create

Sarah Heller: much more possibility when you bring people together. And so a lot of this thinking around AI capability building for leaders in particular, the connection is super important.

Dan Hibberd: I love that, and I think there is something really powerful about with something like AI that is evolving rapidly and constantly changing, having a group environment for people to be engaging regularly and thinking about this at a team level really does allow for the constant sharing of best practice and as the tools evolve, sharing how different people are using the tool. Because there's just so much learning that it's impossible for us to stay up to date with, and to harness a group environment where people are all at different stages becomes quite a powerful way to ensure that you're sharing knowledge within a team, across teams in a really efficient way that's not necessarily relying on an updated curriculum.

Sarah Heller: Absolutely. And with that change, you're going to have to be people learning much more quickly. There is no static curriculum. And so learning by doing and sharing and building on the other idea is a really nice way to build the capability. And these are low-investment ways. So I guess I'll say the other thing is I've found with some of these human connections and bringing people together, we're able to do that at a relatively low cost.

And so one example of something I've been experimenting with over the last quarter is something I've called the Leader Roundtable, which is essentially a peer forum where we've hand-selected leaders from every part of our business and corporate functions to come together. And it's a leader-driven session where they're sharing on specific topics with each other, and we on the leadership, people, IT team are lightly facilitating and potentially getting their feedback and read on things that we're building, but the idea is that it's for them.

And so when I set up the first one, I said, "Let's try it and if there's energy, we'll keep doing it." Did it again, people get something from it, and it's a really quick hit, but it's an hour of the leader's time once a month, and we're going to continue them for the rest of our fiscal year with a

Sarah Heller: rough agenda of topics that align with what do we as a company want to do in terms of AI creating value and process redesign. Culturally, it's interesting. You have to get the right people and create the right space, I find, to have that open conversation. And so that part of that was in the selection. So, we had people that were generally much more leaned in, more outspoken. We knew that they were leading the way with AI, or they were curious about AI. And so we were able to start with that group, and honestly, I'm sure they could have talked for hours. I feel like everyone would stay in the meeting for 3 hours, but if I scheduled the 3-hour meeting, they would never come.

I think the hardest thing is keeping them focused on the higher impact use cases and thinking about what could be and what they might do differently as leaders, versus a cool thing that AI did for them. And so people really want to get into the nitty-gritty, technical details. So there was a lot of energy there. "Oh, someone built this whole collection of agents to go do this research, and I want to know how to build it." But if you only focus on that, you won't get to some of the richer conversations. So, in some ways, we're creating the trust to build the deeper conversations.

Dan Hibberd: I think you've touched on a challenge there, and that is uh is finding the balance within a peer-to-peer environment of organic discussion and sharing versus structure and consistency and guiding the group towards a specific outcome, and I'm excited to see how those round tables continue to evolve, and we would love to talk more in the future as they really start to to come to the fore, because I think there's a lot of opportunity in everything that you're doing around building connection to support AI enablement in that transformation.

Sarah, I've loved this conversation. I enjoyed our first conversation. I've enjoyed this one just as much. As we wrap things up, I'd love to put a bow on things and go, what's one thing that you would like to leave our listeners with? One piece of advice or reflection?

Sarah Heller: At the meta level, as we

Sarah Heller: been alluding to and so much changing so fast. I think what was really different in all this work is that you really do get out of date fast and it's really easy to be working from out-of-date information. So going and doing a whole needs analysis with business leaders, they could be in a completely different place in two months with AI and need different things. And so figuring out a way to pilot and get things out there super quickly is really important, because otherwise we're always going to be chasing our needs. And that was some of the learnings I had is in trying to get the needs, and get approval, and prioritize what needed to be done, by the time I got there, some leaders were already in a different place and needing something different.

Dan Hibberd: I love that. How do we move quickly? And I think some of the old approaches are just too slow in order to keep up with the rate of change. Thank you, Sarah, for joining us again. It's been great to have you with us.

Sarah Heller: Thank you so much, Dan. It was a pleasure joining you today.