Episode 280: How HR Can Lead AI and Workforce Transformation Across the Enterprise (with Eric Dozier)
How do you bring AI into an organisation without losing what's made it work for 150 years?
In this episode of the Digital HR Leaders podcast, David Green is joined by Eric Dozier, Executive Vice President and Chief People Officer at Eli Lilly, to explore what it takes for HR to lead AI and workforce transformation at enterprise scale.
Join them, as they discuss:
Why HR has to transform twice over in the AI era, first as a function, then as an organisation
What prompted Lilly's AI journey, and how the friction points that came up shaped the approach going forward
How the role of the manager is changing as AI becomes part of everyday work
What separates AI capability from simply increased AI usage
The principles guiding Lilly's approach to responsible AI, including where it supports leadership judgement and where it shouldn't
How employee feedback has reshaped Lilly's AI strategy, and what Eric believes HR leaders should prioritise as they lead their own transformations
This episode is sponsored by Valence.
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This episode of the Digital HR Leaders podcast is brought to you by Valence.
[0:00:08] David Green: If you're leading HR in an organisation with a lot of history behind it, you'll know the challenge isn't really about the technology, it's about not breaking what already works while you bring something new in. That's exactly the situation today's guest has overcome at a company that's been around for a century and a half. Eric Dozier is Executive Vice President and Chief People Officer at Lilly, where he's been at the centre of the company's AI transformation, helping shape how thousands of employees adopt and build effective capabilities with these new tools. And today, he's going to give us an inside look into the principles behind Lilly's successful transformation, including where the journey started, how the manager's role has changed, and the principles behind Lilly's approach to responsible AI, among other things. I think there's a lot in today's episode worth taking notes on, so make sure to press save and let's get straight into the conversation.
Eric, welcome to the Digital HR Leaders podcast. It's great to have you on the show. Can you introduce yourself to our listeners by sharing your background and current role at Lilly?
[0:01:20] Eric Dozier: Yeah, sure thing, David. It's a pleasure to be on this podcast. Thank you for allowing me to be here and thank you for hosting. I am currently the Chief People Officer for Eli Lilly and Company. We're a medicine company based here in the US, but certainly we're global. I've been at Lilly for a little over 25 years now, so it's been more than a minute. I didn't start my career in HR, I've been more of a commercial operator. Started off my career in marketing, market research, helping us manage various brands across our portfolio. Had the opportunity to work in our international business areas, was in Puerto Rico, was in Japan, worked in Europe, managing global brands as well. Then had opportunities for some functional roles like ethics and compliance. And then, prior to this job, I felt like I had my dream job actually. I was the commercial leader for our oncology division. I was there about four-and-a-half years and felt like that's kind of where I'd probably end up and be. And then, as careers go, my boss, CEO, Dave, said, "Have you ever considered HR?" And I hadn't up until that point. And he said, "Hey, we'd like you to give it a consideration". And I said, "Well, you know, I have no HR experience". And his point was, "No, but you've worked for people your entire career. You understand our business, you understand our people, you have an experienced team. I think this would be a good next role for you.
So, my predecessor was retiring, and I came into this job here about four years ago, and it's been a great journey. I get a chance to work with a great team of people that are super-experienced, and we've done some good things over these past four years.
[0:02:55] David Green: That's fantastic. Thanks, Eric. And it's been an exciting time to be in HR. So, you've picked the right time to come in and lead the function, I think, because we've seen, in the work we do at Insight222, we've seen HR over the last sort of 10, 15 years move from being what was a traditional support function into being much more of a strategic partner to the business. And I'm guessing that your commercial background and time in the business is really helpful in that.
[0:03:22] Eric Dozier: I think it's been helpful, and I've got different views on some things, but also I think it's been a good mix. My leadership team is very experienced, so they understand the operations of HR, and together we understand the overall business. And I remind ourselves that the business of HR is the business, and making sure that we have the available talent and people available in the organisation to kind of meet the needs that we're trying to serve within a marketplace. And so, it's important to keep a throughline towards what's the mission and purpose of the company. That needs to be the mission and purpose of HR as well.
[0:03:57] David Green: Well, obviously, as we kind of prefaced here, there's a lot happening at the moment. And I know Lilly has been on an AI transformation journey for some time now. Maybe take us back to the beginning of that. What prompted that journey, and how have you introduced AI while preserving the values and cultures that have defined Lilly for 150 years?
[0:04:19] Eric Dozier: I think it's important to maybe divide this in two categories. I think first and foremost, I mentioned earlier, we're a medicine company. Our core business is that we discover, develop, and make medicines. As AI is coming to the forefront here, we wanted to make sure they were integrating AI into their overall strategy of the company. It's something we don't talk a lot about. We talk a lot about our partnerships with some of the leading AI vendors and technologists in the area, and that's been more in the realm of saying, "Well, how do we help us get better at discovering medicines, discovering new chemical entities, that can help meet some of the unmet needs in the overall marketplace?" And so, really, part of HR's role at that point in time is how do we make sure we have all the right talent in the organisation, and making sure we get some of the key talent that can help us lead this bit of AI revolution in our overall kind of core business.
So, really, the first, I would say, year-and-a-half of this innovation has been that. Like, how do we make sure we're sourcing all the right talent, getting the talent in the right places? It's been now these past probably couple of years, we've started to think more about how is AI going to really transform the workplace and transform the people of Lilly overall? We feel good about the way the strategy is integrated, how we're getting our business done, but how do we think about it within that particular context? And it's probably important to note that I know every company probably says this, but I do believe it's uniquely true to us, in the sense that we really believe in our culture, and the way in which we support and develop our people is actually pivotal and key to our overall success.
We're based here in the Midwest. You know Midwestern culture. It's a little more of a humble culture. It doesn't have as much edge as maybe the coast do within the US. And I think that humility, it just creates a certain ethos and work ethic that the company has, and just that we really collaborate well together. And so, we want to make sure that as we think about AI, that we continue to keep the human in AI, that we continue to make sure that is supportive of our people, supportive of our culture, and how we're leveraging it to where it's helping make people better, at the same time helping them develop better. Because at the end of the day, speed matters to what we do. The faster we can get to our solutions, the faster those solutions can get to patients, the better people are. And so, we believe in the axiom that if you help people grow faster, it helps the business run faster. And so, that's the way we kind of thought about it.
So, with that being said, I think we did a couple of pivotal things early on that I think have been, I think, super-helpful to our journey, and I'll just frame a couple of them for you. One is we didn't limit the utilisation. I think a lot of companies started with, "How do I control this and how do I limit it?" I mean, we're concerned about IP protection, we're concerned about compliance, sure. But we almost let the tools -- they were made available. And we created some guardrails around them that our tech group could do, but anyone across the company could leverage and use the tool. So, we kind of had more of an open-source format, if you will. We didn't try to constrain people from being able to leverage AI. And so, I think that just in and of itself created a more open adoption. We weren't doing that. And then, the second thing we did I think was useful, I do think change management should start across the entire organisation, but it's pivotal if your leaders are kind of leading the charge, if you will.
We have an amazing CEO. Dave Ricks was actually probably one of our heaviest users of AI. And he encouraged us, charged HR with actually creating essentially an executive ed course, if you will. And what we did is we kind of took a portion of our top 100 leaders and we paired them up with a person from our tech group. We paired them up with a world-class scientist from Purdue who was an expert in AI, and then themselves. And then we said, "What are problems that you're trying to solve? Just bring your problems. We don't need you to think about what's AI-enabled, just bring your problems". And then, through that group, we were able to identify a couple of key projects that we actually delivered solutions to that were AI-enabled. And then, we did that over the course of these past couple of years, and so there were several initiatives and several projects of the company where people can truly see the power of AI. And so, those two things combined is how we kind of started on this transformation, this revolution to kind of get things moving forward.
But I do think it's important to remind ourselves that part of this journey needs to be about how we're investing in people and how we're supporting them and their growth, and then adopting these new tools. That remains, I think, foundational as to how we think about it.
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So, let's look at HR. Now, AI is changing every function, I think we'd agree with that. But HR arguably must transform twice, first as the function itself, but second as the organisation helping everyone else to adapt within Lilly. How are you thinking about that dual responsibility, and how do you decide what efforts to prioritise?
[0:10:46] Eric Dozier: Yeah, that's a great question. And I love that frame of we're having to change twice. That is true to a certain extent of how do we continue to transform our function in a way in which we serve our business partners; at the same time, how we're thinking about it, how we're serving over our company. So, let me start with the first part. How do we help kind of transform HR? And for my colleagues that may listen on this call, we're still early in this journey. We certainly have several different power users within our organisation and within our function that are fully kind of embedded. And to my previous comments, we had those same tools available to all of our HR colleagues. And so, that, we've kind of done. We did a couple of unique things.
One is, maybe if I can frame this maybe in like a three-year journey. Year number one, everyone had access to the tools, they were available, we didn't discourage, we weren't adamant around using X or Y. I think year two, we really started to think about like, how do we put more emphasis on it, more expectations on it? How do we make sure we integrate this into our overall expectations from a learning journey perspective? And we actually developed a bit of a curriculum, if you will. And I would say that was one mistake actually, that I probably wouldn't do that again. And the reason why, the minute you develop an AI curriculum, it's already out of date. So, it's like you're constantly trying to catch up with something that's just impossible, as opposed to setting expectations in terms of utilisation, the ways you'll use it, and then maybe pointing people to resources. That's probably a better path that I know now, but we would have probably started with that. But in respect of it, that certainly helped to kind of cultivate a bit of a an expectation.
Then, when I came to this job, and maybe one change that me and the leadership team did together was, you probably heard the old adage, "The cobbler's kids probably had the worst shoes". And so, the same here, like HR, we spend a lot of time helping support each other, we really don't develop ourselves. And so, we actually dedicated a day, we call it HR Day of Development, where we come together as a function, as a team, and we focus on ourselves for that day. I know it's not a lot of time, but I think that moment creates an opportunity for us to come together as a community. My lead team members do different development functions throughout the year, but that's when we come together as a function. So, these past couple of years, we've actually dedicated that day to AI engagement. And this past year, we did a bit of an AI hackathon, like what are our current problems within the HR function that you're trying to solve, how AI can help that. We've done a lot of learning and skill development. So, that's been a way in which we started to cultivate a need to accelerate all of us on our AI capabilities.
Then, we continue on that path moving forward. We've got all those tools available to us, we've got a great tech team that truly has all the models, essentially, you could name, plugged in to the key things that are there. We have some preferred models that we use within the context of Lilly, and they're able to connect with all the key things that kind of matter for us. And then, really, what I've kind of been most concerned about though is what you said, is how do we think about AI in a way in which it's kind of transforming the workplace, in a way in which we're leveraging this for good, the way in which we're helping it make the organisation, the company kind of better? And so, I think what's key, and I've been to a lot of courses, talked to a lot of people, I think what's key is you have to actually have a fundamental understanding of your organisation and all the jobs and tasks. Because if you think about any AI model, it's only as good as the prompts you give it, or it's only as good as the specific thing you're asking it to do.
So, we've actually embarked here this year on some work that doesn't sound super-glamorous, but I think it's super-important, which is to say we need to get a much stronger fundamental understanding of all the jobs across Lilly and what are the individual tasks associated with that job. So, not a job description, but actually, what does this job do? What are the tasks that you're performing? Because then and only then can you start to think about what are the ways in which we can kind of transform this work from an AI perspective? And so, we're kind of halfway through that journey. We're going to get done with that journey here really this year. And then, we're going to be able to aim ourselves towards the fourth quarter to start to say, okay, so we can look at each individual job and look at what parts of those jobs could be more kind of agentified, if you will. But more importantly, we're going to kind of pull up, look across the entire organisation, understand what is our AI potential, if you will, across the entire organisation.
But more importantly, with that fundamental understanding, we can actually ask ourselves questions, even beyond just AI, what tasks are being done today that don't even need to be done anymore, because our business model has moved pass that? How do you redesign your processes so that they're more AI-enabled? And then, how do you design people around that? I think too often, we're starting with a people-first process and laying AI over top of it, as opposed to thinking through how do we design an AI-enabled process, and then plug people in where you need to. So, we're on that journey. That's kind of, I think, how my role and our team can be the most service to the organisation, if you will. And then, by the way, we're going to do that work on ourselves as a function first. How do we take our own jobs and how do we redesign the work that we do in an AI-enabled workforce?
[0:16:38] David Green: There's lots of stuff in the press about HR and IT combining, and we've seen that happen in one or two organisations. But the reality of AI, when I speak to your peers in organisations a similar size to Lilly, it's actually about better partnership rather than necessarily HR and IT combining. So, I was wondering, obviously, as the CHRO at Lilly, what have you learned about partnering between HR and technology and the business, frankly, on the AI transformation?
[0:17:10] Eric Dozier: Yeah, I love that word, 'partnering', kind of partnership. Our Head of Tech, his office is really a couple of offices down. He's down in my office every day, I'm down in his as well. We're often talking. I think what I've learned is it's important that we integrate effectively with each other. I think they're the ones that are bringing the kind of tools and the technology. We're certainly bringing the overall strategy from an organisational standpoint, and where the opportunities are. And the data we have available now for them is going to be pivotal as we think about tool development, I think. So, that's been crucial. I know some organisations have combined their role. I won't make any comments as to whether that's good or bad. I do think it's helpful though, as you have these positions separately, it allows a certain focus to continue to be there. And I think there are things in my role as the Chief People Officer, I think about a broad set of things.
But first and foremost, I need to think about how I'm helping to create the environment in a workforce that wants to continue to stay engaged with us. How do we keep our culture strong, the environment strong? How do we continue to grow and develop people? Versus maybe through on the technology side, you're only thinking about effectiveness, maybe productivity, and you might lose the people element. I think us combined, we can kind of bring those two together, which then allows us to do what I said before, is we can continue to pour into people, help them build their skills and capabilities as they adopt these new tools, and then they can become more effective in the work that they do. And then, as they're more effective, we're more effective as an overall kind of organisation.
But I do think the partnership is absolutely crucial in making sure that we're prioritising the right opportunities. And one thing I'll say is, I think we've had our tech teams, I said earlier, more focused on how do you make sure we're integrating AI into the ways in which it supports our core business? So, how do we have models that help us better understand discovery? How do we have models that make us more effective in developing our medicines? How do we have models that make us more effective as a way we're kind of getting to deviations with our manufacturing organisation? Those are pivotal, right? And then, now we're at the stage of saying, okay, how are we fully integrating this across the workforce? And that's where we've been working together effectively on.
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How are you seeing the role of the manager change as AI becomes part of work? And what are you doing maybe to help managers with what's quite a difficult job, because again, they've got to upskill themselves and use the tools, but they've also got to help their teams to do the same?
[0:20:52] Eric Dozier: Yeah. So, a couple of things. Number one, I think we're very early in, I would say, this evolution of AI. All the models that are out today, this is the worst they'll ever be. And so, they'll get more and more effective as we kind of move forward. And there's not many organisations, I think, that are fully agentified to any great degree. We're not yet. And so, we have several kind of AI agents operating within the company, but nothing to any sort of scale yet. We'll get into that, I hope, as we move towards later this year, kind of early next year. But I do think it's important though to take us back to kind of first principles, which is, and this is our belief as a company, I think there's a fundamental role of a manager that is supporting and developing people. And it's to be a coach. How do you make sure that you're coaching and developing your people to be their best selves for the organisation? And so, that means you're supporting them with understanding expectations and ways in which they can grow, providing timely feedback, giving them the ability to grow and develop as an employee and kind of grow them. So, that's foundational to me, that's important. So, the coaching elements there.
I think we are asking managers, as my boss, who's my manager, Dave, is leading by example. So, you can imagine the role of a CEO and how busy they are. But if he's taking time to grow himself in this area, how much more should I be doing the same thing? And so, I think there is a set of, how do we encourage our leaders or managers to set that example? And then, I think we do want our managers to access the tools and capability development that's available to them, so they can grow themselves, so they can help grow their people. And so, that's been important. So, maybe one role that we've seen that we are asking for a change on is, we're encouraging everyone to just be better coaches for their people. And we actually essentially have focused on coaching these past several years within my tenure here as the CPO. And we've basically, through AI, scaled coaching essentially across the entire company. So, you as an employee can have access to an AI coach, as well as to your supervisor. I'm going to be very clear here. This is not a replacement for your manager, but it's more of a supplement to that.
Then managers, you have the opportunity to leverage tools and capabilities to make you a better coach for your people. One of the things we've done is we have an app that's integrated with our AI tools. So, you can actually model a PM conversation prior to it happening. You can actually do a writeup to make sure it's clear and concise and it's communicated effectively. So, there's things that you can do that actually takes upon best practices across the organisation, and makes you just a better leader in a way in which you're supporting and giving to your people. So, expectation-wise I am expecting them to adopt those tools and to use them so they can be better. In the future, and that future is not far away, we'll be having the challenge of saying, how do we help support managers with managing AI agents and agents managing agents, as well as managing people? How do we think about that dynamic and how that works? We're not there yet, but those are things we're starting to think about now. And maybe a year from now, I can give you some feedback as to how that's going here.
[0:24:12] David Green: So, looking back on the journey so far, and as you said, you're still early in that journey -- listening to you, Eric, I'm not sure how early you are in the journey compared to other organisations I'm speaking to, I think you've made a lot of progress -- but looking back on the journey so far, what has surprised you the most? And have there been any unexpected wins or success stories that really stand out?
[0:24:31] Eric Dozier: We've had several different wins, I would say, at the technology level in terms of integrating the technology and ways we get things done, making us more effective. As I mentioned earlier, we did some of those projects, several of those things that have become real business tools that in a short period of time, have made us more effective as an organisation. And those are powerful stories to tell across the organisation. And so, that's been pleasant. The thing that's been surprising to me though is we need more kind of cross-pollination. We're a large company, but we think we're small. And so, I think we can probably still do a better job of this concept or idea over here. As an example, an AI tool that can identify a deviation before it happens, that same tool can be applied to finance. So, why haven't we cascaded that faster and vice versa? So, some of that, this past probably year-and-a-half, we've been doing more of that work, because it hasn't spread as fast as we'd like it to be.
The other key thing, I think, is the feedback. I think the feedback has been overall positive from an employee perspective. It's been more of the younger generation and more of the people that we're recruiting new to the organisation. The one surprise I had, I love to talk to all of our new, or at least interns within the organisation, and that's the highlight of my year. I sit down with them for an hour or so and they ask me tons of questions, and I've been doing this now for four years. It was interesting this past year, all their questions were about AI, like every one of them. And it was a fear factor in terms of how we're going to be integrating AI, how we're thinking about it, what does it mean for them in the future, their jobs. And it was interesting to me. It kind of caught me by surprise, and it probably shouldn't have. But I think there's more work that we probably need to do as an organisation, especially here in central Indiana, and we have with partnerships with universities to make sure that they know that we're still a readily-available workforce to continue to support and develop talent.
Then, maybe the other thing is just we are in a complex business, IP protection is important. Making sure that we protect our data in a world of AI has been crucial. And quite frankly, that's a bit of our secret sauce. And so, we've had to make sure we have all the right controls in place around that. I mentioned earlier, we're pretty much an open system in terms of you can use the tools, but we've got some governance now as we're starting to adopt more AI tools across the organisation. We had to put a little more governance around it in terms of ways in which we're doing that, to make sure that we're doing it in an effective way that's safe for the organisation, safe for the people, and allows us to be more effective kind of moving forward. So, that's been a bit of a struggle, if you will. At the same time, you're trying to move fast, but you're putting some governance in place that forces you to move a little bit slower. So, that's been a little bit frustrating, I think.
[0:27:30] David Green: How has employee feedback, both that feedback that you talked about and other feedback that you get from employees, how has that changed the way you've implemented AI within Lilly?
[0:27:39] Eric Dozier: Yeah. So, maybe I'll talk about it from two points. I think we take feedback very seriously, it's an important component. We think it's really important to give people an outlet to provide their point of view, provide their perspective. We take what we kind of call a Lilly pulse survey, which is basically our entire organisation. We do that essentially twice a year. And then, we have some kind of micro-pulses we sprinkle in throughout the year as well. And then, we do a leadership compass kind of once a year. And those are two opportunities to provide good feedback kind of in general. By and large, our employee sentiment has remained strong through this kind of early period of AI in general. There's been no huge shifts that I think people can actually see. I said earlier, it's been more of the people that are newer to the organisation, people I meet on college campuses. There's been more concern there than is people that are currently within the workforce if you're working for us.
Now, it's important to note, we haven't had any major transformations of department areas based upon AI. I think there will be more of those opportunities as we move forward in the future. And people will have opportunities. So, we're a relatively lean organisation, we're at about 50,000 people. We want to stay relatively lean. And so, we're going to leverage technology to help us do that. And so, that's been a message we've been trying to reinforce across all of our team members, is to embrace AI as this solution so that you can grow and develop, so that you can continue to reach for those opportunities. So, the key thing we continue to do though is how we're trying to encourage utilisation, encourage adoption, and provide every avenue available to you so that you can grow better within this particular function.
[0:29:32] David Green: What tells you that your workforce is becoming more capable, not just using AI?
[0:29:37] Eric Dozier: Yeah, that's a great question. I don't have a good measurement on that. Like I said before, I think we can look at utilisation, we can look at kind of token utilisation, and we know the different parts of the company and ways in which they're leveraging internal models that we have developed. I think the real shift will happen as we're in this next stage of our own workforce architecture work, which is understanding given all the tasks, what are things now that quite frankly should be done by more AI agents, if you will? What are those tasks we want to make sure can stay human-integrated? And what are those tasks that quite frankly we should just do differently? And so, to your earlier question, I think that's the work that HR can lead and to kind of help, how do we help drive forward across the company what that workforce transformation looks like in an intelligent, thoughtful way that is both respectful of people, but also is true to what the capabilities can leverage themselves around?
So, I think we'll be able to look back, David, in terms of that sort of analysis and say, well, I don't have this data in front of me right now, but if you look at our overall tasks across the company, we're going to be able to know relative to these tasks things that AI is really good at right now. And I would say that for the most part, those tasks are being done by humans. And that's probably work that should be done by an AI agent. So, then, how do we redesign that work to where AI can support it and humans can be engaged in that? That's the work that we're embarking on here in the second half of this year.
[0:31:07] David Green: As obviously Lilly scales AI quickly, and also you're obviously taking that regular feedback, employees may have questions around things like transparency, fairness, and trust. And you talked about putting humans in AI really right at the centre of your strategy around this. What principles have guided Lilly's approach to responsible AI in the workplace?
[0:31:33] Eric Dozier: Yeah, so a couple of things. I think we're rooted in our values, respect for people, excellence, and integrity. And so, that kind of governs the foundation of who we are. We do believe in responsible use for AI. We've got core principles that we have developed as an organisation. Those are how we're leveraging it. From an HR perspective, I do think it's important that we're very transparent with our people as we're going through workforce innovation and work, if you will. We'll make sure we engage with the leaders in ways in which the organisation could and should transform, and we're making sure that those are decisions that they get a chance to make, and how we're engaging with them. At the same time, if maybe your job is far more AI-enabled than other jobs are, how do we help make sure that you have other capabilities that allows you to grow in other areas? We're going to always have need in terms of people across the organisation, but how do we do that in a responsible way that allows you to continue to grow?
I think those that are willing to invest in themselves, those are willing to continue to grow their capabilities, we want to make sure there's at least opportunities in the consider. So, I do think that's important as we think about it. And I do think it's important that as an organisation, we need to make sure that we continue to grow and develop, that we get better and better. And then finally, at the core, I think we need to continue to keep in mind respect for people. And I think that doesn't mean I can guarantee you a job for life or I can guarantee that. But what it does mean is I'm going to be open, I'm going to be honest, I'm going to support you, I'm going to help coach and develop you, and to try to provide options for you to consider.
[0:33:16] David Green: Very good. And obviously, you talked earlier at some length about how Lilly is using AI increasingly to support coaching and performance conversations. So, it's a two-part question on this. Firstly, where do you see the line between AI augmenting leadership and replacing human judgment? And maybe the second part to that is, where do you see AI supporting coaching in other areas as well, of a manager and a leader's job?
[0:33:47] Eric Dozier: Right, you're getting to the difficult question here, a dangerous one, I think a really important one. Let me make a comment because I've had this discussion. I'm going to answer your question, but I'm going to ask a different question. If you ask me in the area from HR function, "Hey, what are you most excited about for AI?" it's actually in our recruiting space. As you can imagine, we're a company that gets lots of different resumés, lots of opportunities. We try to look at every one of them. And that's right now as a human process. We're integrating AI much more in that area, and I'm very excited about it. Why? I think there's this basic assumption that we make that humans aren't biased, and that's a false assumption. Humans are biased. And so, I do think if you can manage it appropriately, I think AI has the capability to actually be much more objective towards, "This is the profile you're looking for", and objectively looking at tools and things of that nature.
Now, having said that, we need human judgment. We have to have humans in the loop, period. There's not anything I'd want to do in an HR function, especially around hiring, especially around coaching, that would remove the human element. I think that's just not going to work effectively. But I do think it's important, how do we augment you to make you more effective and to grow as an overall coach? So, I think, to me at least, the best coaching conversation is going to be a live, in-person, one-on-one coaching conversation, where you can demonstrate the fact that you actually see the person, you care about them, you have their best interest of the heart, and you can convey that effectively. I think that's important. And you're given the right feedback and the support that's there. Will AI be able to do that? I'm sure it will, but is it going to feel the same as coming from David? Probably not. And so, I think that's going to be important. Now, can we help you with how you can prepare better for that conversation so that you're more effective in front of Eric, so that he's actually taking your feedback and hearing effectively? Yeah, I think so. And so, that's the path where we see these things as integrated together, if you were, from a coaching standpoint.
I think those tools can be developed to a multitude of other uses probably that's there. But within our function and way in which we serve the organisation, our recruiting area, it is our area where we have the most innovation right now, because that's an area where it's a lot of repetitive activity and there's an opportunity to actually create a better candidate experience, if you will, and not only be more effective for the organisation.
[0:36:16] David Green: I love that, using AI to augment the processes to make them more human, and actually, as you said, keeping the human in the lead, so that the actual decision or the judgment is the human piece, but the AI helps people get ready, for example, for a performance conversation. It helps to maybe improve the recruitment process and improve the candidate experience, which is ultimately what you want to do, because I guess these candidates could be customers as well. So, it's important to provide that great candidate experience and persuade the best that Lilly is the place for them to develop their career.
[0:36:53] Eric Dozier: And it's also this element, you think about it, AI can make you more effective, AI can give you more time. So, what are you going to do with that time? I would hope, to your early question, if you're a manager, take some of that time for yourself in the ways in which you're thinking about making yourself better. But also, that sets you up to actually be a better coach, a better supporter for your people as well. So, that's another aspect I think is important from an HR lens, how do we think about the way in which people can leverage their newfound productivity with some of the time they may have available through more effectiveness with AI tools?
[0:37:28] David Green: So, based on what you've learned so far, Eric, what are the key capabilities you believe they should prioritise to successfully lead in an AI-enabled workplace? And again, you've talked about this, but how would you recommend that they balance the technology with the human element?
[0:37:44] Eric Dozier: Yeah, that's a great question. I think number one, I think not necessarily capability, but I would encourage other HR leaders in my position to make sure you have a fundamental understanding of all the jobs within your organisation. It's got to start there. If you don't have that understanding, you need to go out and get that data, because that's the only way that you can really better understand ways in which AI can help you at a kind of writ-large scale. That, to me, is foundational work that needs to get done. It then allows you to think about how you can reorganise work around AI and then how you can put the human element in it. The second piece is, I think you have to continue to prioritise coaching. Coaching as a capability, I think, remains pivotal to this journey and remains pivotal to the future journey here as we think about the way in which AI is going to continue to adopt. Or said another way, you want to continue to invest in your people's capabilities. And I think the coaching capability to me is an important component.
Every organisation has different technical things that they're really focused in on, and so I won't go into that. But I do think to me, and I've heard this said by others, and I agree with it, it wasn't me that said this, so your hard skills, which were probably paramount in the past, they'll remain important. Your ability to effectively have a strong analytical ability. If you're strong in stats or accounting or finance, those hard skills will continue to be important. But what perhaps erases a little bit what I said, I think what's more paramount in our future are more of the soft skills, actually: your leadership capabilities; your ability to connect and engage people; your ability to inspire; your ability to demonstrate empathy; the ability to provide understanding; the ability to make sure people are seen. In a world that's technology driven, I think people will hunger more for that and our leaders that can kind of blend those two together will be pretty effective. And so, I think we'll probably need to spend perhaps more time on our EQ than our IQ. I think AI will allow us to do a lot more of the IQ activities faster, easier, cheaper probably, but it won't be able to do the EQ activities as effectively. So, I think you have to rethink that a little bit more and how you're valuing leaders of the future.
Then, the final thing I would say is, we think about this a lot at Lilly, is how do you continue to encourage people to take risk? How do you encourage people to be bold in their thinking? How do you encourage people not to be afraid of being wrong, really creating an atmosphere where it's okay to fail, fail fast and then learn from it, because the next time you'll be better for it? I think, to some extent, in a world of AI, and potentially you may think it's giving you perfect answers, it's only as good as your critical judgment and thinking that you can provide it with, but how do you encourage people to not be fearful of the future and where they're going? Those are the things I would think about.
[0:40:46] David Green: Really good. I mean, it could appear counterintuitive that the soft skills, the EQ skills, become even more important in a technology-enabled world. But actually, the way you've explained it there makes perfect sense, and I hear that from your peers in other organisations as well. So, two questions, Eric. I'm going to go to the question of the series first, and I'm going to come back for you to look forward to how things may develop at Lilly. So, this is the question of the series, so this is the question that we're asking every guest in this particular series of the podcast. And you're probably going to be maybe referring back to some of the things you've already mentioned. But again, good advice maybe for those listening. How can HR own workforce transformation in the AI era?
[0:41:32] Eric Dozier: I love that question. I want repeat anything I've said before. I would say you're only as good as your system or process that's in place. And so, for us, it's actually doing the workforce innovation work that we're doing, and then making sure that we're a good business partner strategically with all our areas, helping them better understand the current makeup of their workforce, and the ways in which given that current makeup, given the tasks they're performing, here are the opportunities that AI can offer you. Then, how do we then reconfigure that moving forward? I think it does come down to fundamentally, as an HR function, helping them get out the data. We can think much more strategically about where we can be, but also is it actually this tactical activity saying, okay, how do we now redesign the way in which this work looks? So, I do think this will be an opportunity for us to kind of redesign work across organisations in a world that's AI-enabled and comes with a people-first mindset.
[0:42:26] David Green: So, last question, Eric, I'm going to ask to look into your crystal ball. If we were having this conversation three years from now, and I won't hold you to it, don't worry, what would you hope is fundamentally different about how work happens at Lilly?
[0:42:42] Eric Dozier: Wow, I've got to be careful how I'm framing this, but I would hope, to some extent, I wouldn't recognise it actually from where I am today, because I would hope that we fundamentally transform the way in which work gets done. It's getting done faster, more efficiently, more productively, people are more engaged in the work that they're doing. I think there'll be some areas that we won't even recognise it. And I hope that as an HR function, the way in which we're showing up to our business partners, I would hope it's more consumer-grade. So, if you will, imagine all the employees that engage with HR processes. I hope that's as seamless as the way in which they gave with digital banking today. For us, we're not there yet. So, I think there's an opportunity for us to actually transform the way in which HR, from a customer perspective, is showing up, that we can create more consumer-grade processes. But I would hope I wouldn't recognise it actually, David.
I think fundamentally, it should be transformative. As I said before, these tools available, these are the least effective they'll be. They're going to be more effective. And so, I think we have to really be excited about that in ways that we can adopt how we're moving forward. So, I would hope that our recruiting strategies are vastly different, I would hope the way in which we're getting feedback is vastly different, the way in which our strategic business partners are supporting their customers, that work's been redesigned, and we're just a better organisation because of it. But what I hope will be the same, that you didn't ask me, are people feel engaged, they're excited, they continue to opt into Lilly, they're excited about the work that they do and the ways in which they're supporting each other; and that we have this inclusive Team Lilly environment that's excited about the ways in which we're really making medicine and impacting the globe. I hope that doesn't change, right? The way in which we get things done will, but I think at its core, I think staying true to our values, respect for people, excellence and integrity, and creating an environment that people can be a part of, I hope that doesn't change. And so, as long as I'm here, I'm going to work hard to make sure that that part doesn't happen.
[0:44:40] David Green: Well, Eric, it's been an absolute delight to speak with you. Thanks so much for being a guest on the show and sharing the fantastic work you and the team are doing at Lilly. Can you let listeners know how they can follow you?
[0:44:50] Eric Dozier: Yeah, sure. You can find us on lilly.com. Feel free to reach out. We're very active on LinkedIn as well. So, you can find Lilly there and you can find my profile there as well. So, would love to engage and happy to engage with the crew that listens to the podcast. And, David, thank you so much for allowing me to be a part of it.
[0:45:07] David Green: Well, it's been a pleasure. Hopefully, Eric, I'll meet you in person one day, maybe a conference at some point in the future.
[0:45:15] Eric Dozier: I would appreciate that. That'd be great.
[0:45:18] David Green: Eric, thank you so much for coming onto the show and being so open about Lilly's AI transformation journey. I learned a lot and I'm sure our listeners will too. So, thank you again. Turning to our listeners, I'd love to hear your take and your thinking on how HR can own workforce transformation in the AI era. Head over to LinkedIn and let me know what stood out to you from this conversation, or where you're at in your own journey. And, if you enjoyed this episode, please do share it with a colleague who'd get something out of it. And if you haven't already, hit subscribe so you don't miss what's coming next. One last thing before we go. For those who would like to keep up with what we're working on at Insight222, follow us on LinkedIn, or head to insight222.com. You can also sign up for our bi-weekly newsletter at myHRfuture.com to get the latest thinking on HR, people analytics, and everything shaping our field.
Right, that's us for today. Thanks for listening, and we'll be back next week with another episode of the Digital HR Leaders podcast. Until then, take care and stay well.