ServiceNow, Inc. (NOW) Earnings Call Transcript & Summary

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Welcome to the Executive Exchange Customer Experience Program, where today, we're going to discuss HR leadership in the GenAI era, how we optimize for employee productivity. So I just wanted to start off by saying thank you for joining us today. My name is Dave Wright. I'm the Chief Innovation Officer here at ServiceNow. And for the next 45 minutes, we'll be having some candid conversations about the real challenges and strategies for transforming HR today. I'm excited to be joined by Kelley Steven-Waiss, ServiceNow's Chief Transformation Officer. And together, we'll be talking about one of the hottest topics out there for HR professionals today, how can we as leaders optimize our team's productivity in this new era that's really being changed by generative AI? But before we jump in, I wanted to do a brief lay of the land. So what are we going to go through today? Well, first, we're going to discuss the state of HR in the generative AI era, then I'm going to bring Kelley on and we're going to talk a little bit around how we can use AI within the organization to help support productivity, some of the observations we've seen around this and as part of that, how can we touch on ServiceNow's concept of rethinking employee experiences. Then we'll share some closing thoughts with you. And finally, we're going to wrap up with some Q&A. So what we'll do to start off with is go through the state of the state, what are we seeing today? We know that today, every organization is expected to have an AI strategy. And different companies are at different levels of maturity. And it's interesting to see people's AI strategy and understand how they're thinking about it. But the one thing we can say about AI in general is that it's being adopted at an incredible rate. One thing stood out is how we look at a normal hype cycle for adoption. The rise of GenAI has been dramatic. And it feels almost like we went from the hype straight to production. So the time for adoption and buildup has been extremely short. This is one of the types of technologies that we haven't really seen adopted in a way like this before. And it's interesting now as well how AI has kind of become synonymous with GenAI. People are using the phrases interchangeably. But one of the interesting things is that not only did GenAI emerge in the market and quickly become popular, but everyone was expected to have a strategy that was already created and a solution implemented very, very quickly as compared to other innovations. It became one of the top CEO-focused things. So CEOs were really paying attention to what this GenAI strategy is going to be. And that's probably because of the actual business value that leaders are seeing and the potential that they see to realize through GenAI. So the slide that we're looking at now is from Accenture. And it shows that they think companies could unlock an additional $10.3 trillion, with a T, in economic benefits if they adopt responsible people-centric approaches to generative AI. So now we find ourselves very quickly and deeply in this age of GenAI. Like everything, it's gone through different eras of evolution, and each one is built slightly on the last. So the first thing was the diagnostic era, which was largely defined by data and the mathematical ability to analyze data and start to establish causality. Then we moved into the predictive era, which allowed the application of machine learning algorithms to make increasingly accurate forecasts about everything from operations all the way through to customer behavior. And then late 2022, we saw the public emergence of the generative era. So although people have been working on this for a while, this rapidly came to the public market. And now machines weren't just predicting things with high accuracy, they were actually generating creative content and offering personalized suggestions. And this is one of the areas that I want to get into with Kelley a little bit more. So Kelley, I'm going to start off by welcoming you to the discussion. We're going to have a bit of a chat now, but I really appreciate you taking the time to come on the board with this as well.

It's great to be here, Dave, and certainly have this conversation with you. It's so important.

Absolutely. And I'd like to dive into the topics a little bit deeper. But I thought I'd like to ask you some questions and get some thoughts specifically from HR leadership perspective. I obviously haven't got that HR background, but how they're thinking about using generative AI to optimize that productivity? But before we get into that and go into details on that, I wanted to start with your story because I think it's so interesting, the approach you took and the transformation you've gone through and the place that you've actually ended up now in your life. So maybe you could just give us a bit of background around you and how we got to where we are?

Yes, absolutely. So I'm not sure I used to be able to spell AI. But I started many years ago as a CHRO. I was actually a CHRO in tech for 13 years. And because I was at the crossroads of trying to solve this problem that I saw, people not having access to learning and the flow of work not being seen, valued and heard, not being able to get the content that was most important to them or to do work in a meaningful way. I started to study that problem pretty deeply, and it turned out that AI was going to be the eventual savior that would attach itself essentially to skills information and make the invisible visible, make people able to do work differently and better. And I started a company called Hitch or Hitch Works because I had better SEO. And eventually, that internal talent mobility and skills intelligence platform was acquired by ServiceNow. And so here I am getting to work with our customers on massive digital and workforce transformations. And my relationship to AI really started there, and I am extremely bullish about what GenAI can do for the HR profession and for employee experience.

So Kelley, as our CTO, you're out there and you're talking to customers all the time about how they can transform. And I speak to people again on the technology side, most people are just taking the first steps into AI, and they've got concerns and issues about what they do. I wondered from a human resources perspective when you're speaking to customers, what are the common concerns they've got when they're actually starting out to build this GenAI strategy?

Well, first of all, Dave, most of the time, they're a little bit deer in the headlights because while there is massive excitement about this, there's -- and tons of pressure to deliver on it, I think that there's concerns, and those concerns are typical for HR. We have had to work through things like GDPR, protecting data. And since this is all generative AI is all surrounds the issue of data, we worry about PII, personally identifying information, what LLMs are being tapped, what data is being shared. That's one piece of it. The other piece is as stewards of the company to think about employee experience and things like diversity, equity and inclusion, is this going to take us further back on issues of bias or inclusion issues? Is this going to help or hurt employee experience? So I think these are the things that as the sort of steward of the organization and having the conscience for the company that they think about GenAI.

So what are the -- I mean you brought up something then that was interesting. I suppose I haven't thought about it before. But from a bias perspective, I guess everyone wants it to be as transparent as possible. Everyone wants to be able to understand how it's making the decisions.

Absolutely. I think the big question about, hey, where is this data going? Could this data actually be helping someone take an action or a decision that might have bias inherently in it? So understanding, at a somewhat technical level sometimes, what is happening with data in the back end. HR leaders didn't grow up living in sort of the digital space. I mean we've had to evolve over time. And just like you talked about earlier, there just wasn't a lot of time to figure this out. So those HR leaders that sort of sit in the middle and said, "I'll wait for someone else to go first and learn from them" really didn't have that opportunity.

So it's interesting, we were talking about Accenture before and Accenture making that $10 trillion-plus prediction. But they'd also done another survey that's interesting when it comes -- it actually comes into that transparency place to a degree. They surveyed a lot of people, and 95% of the workers that they interviewed saw value in working with GenAI, but they have this real concern that they don't trust organizations are going to necessarily use AI to ensure there's a positive outcome for everyone, which is kind of a worrying fear to have. But if you think of the leaders that you work with and ServiceNow as being leaders in this space, how do we get this best of both worlds? How do we get the gains that we want from AI, but also make sure that employees feel that they can trust what is happening? Have you had any conversations around that?

Absolutely. I think it falls into the category of what we call responsible AI. So what do we mean by that? I think we mean that it's part process and governance of the use of AI internally, and I think HR has a role of playing the conscience there, asking good questions, holding the organization accountable. And then there's the technical aspects of that. And of course, as ServiceNow, we have something called the AI control tower. We have a way to see what is happening in the enterprise. We have domain-specific LLMs that we're working with that help safeguard things like PII type of information from getting in the wrong hands. So I think it's process, it's also governance and it's technology. It's all those legs of the stool.

I mean it's interesting to think about all those different elements that you do have to think about and take into consideration. I think quite often, when people come up with their vision and strategy, they don't come up with everything. We were having a conversation in Vegas a few weeks ago. One of the things that I always find with people's AI strategies is they haven't really defined what they want to do with the time that they're going to get back. They haven't thought about organizational redesign and stuff. So lots of different things to think about, right?

Yes. I think it's really funny because if we go back in time, when we thought the cellular phones were going to give us so much time back or the computer or the PC would give us so much time back and we were saying, "What are we going to do if we're working 32-hour work weeks because we have all these devices?" And did that actually happen? No. It just meant that -- my husband used to say to me, "It's you, me and the iPhone for dinner." So we just incorporated in and found ways to work longer. And now it's all the time. In fact, your iPhone is like an appendage. So sometimes the way we think things will go are not the way that they do go. So we definitely are going to get extreme amounts of productivity back. I think we should spend some time thinking about how could we innovate, how can we build something new and do that across certainly across HR, all centers of excellence.

So how do you think -- when you think about GenAI specifically for human resources, what are we thinking about GenAI optimizing from a business output perspective? Because normally, we think about what does it do for technology workers or customer service. But what do you think to expect when it comes to getting efficiency from a human resources team?

I think there's a couple things to think about. I think one is how it's going to improve people who are working in HR and trying -- people get into the profession because they like being in service to human beings. They enjoy that job. So your ability to be higher touch but on higher-value things. So as an -- if an HR agent can resolve an issue with higher satisfaction in a shorter amount of time, their amount to spend in a conversation that is high value and high touch is greater. And likewise, I think for people who have to either work to solve a problem and we, as employees, we have things that come up, whether it's benefits related or something with a conversation with a manager, if we have a better experience because generative AI help my manager understand more about me, and therefore, we had a better conversation, that's great. That's only going to increase my satisfaction. And that will add a third element, which is very near and dear to my heart was what it's doing for talent, strategy and workforce planning. When we are able to use AI, attach it to skills intelligence and be able to take someone through a journey against their aspirations and reskill or upskill them in a new direction that's very personalized and customized, it becomes a consumer-like experience. And if we can offer that at scale in a company our size, Dave, of what are we at, 22,000 people almost, that's -- or more, that's amazing.

I think you touched on something interesting. We talked about the time that we save. And I think there's this concept of if you give everyone an hour or 30 minutes back a day, think how much more productive they'd be. But it's kind of what you said with the phone. It just means you'll end up having an extra coffee break or a longer lunch. But if you amalgamate that time, if you say, "Well, yes, we need people dedicated to these tasks," but then use some of the software you developed around the talent management to actually look at what's available with what you've freed up, you can use organizational transformation to drive that business transformation, right?

Absolutely. And one of the things that I don't think people think about is that we all need think time to innovate. So if we actually free up the minds of many of our employees across so many different disciplines, think about the better processes that will get created, the better products that will go to market. And ultimately, that leads to revenue, right? So we're going to get a bunch of growth, not to mention there is an exponential benefit of people being able to find their passions and do the work that is meaningful for them. So we get all of the -- we tap all of this energy and capacity in the organization that we would have left on the table. And part of the premise of being able to digitally tap people on the shoulder for all work that needs to be done in the enterprise is that who knows what will be created out of that. It's definitely going to create massive amounts of benefits to both people and to the organization.

Yes. You were -- you touched on something then that I just wanted to go into a little bit more. You're talking about -- we talked a lot about what it can do for employees, how it can free up time, how it can help them do the job slightly better. I wondered, have you thought about or have you had an experience of how this can work for HR leaders? Is there going to be a way we can make life easier for a CHRO using GenAI?

Absolutely. I think one of the things in the spirit of transparency and going for better business outcomes is visibility, better workforce planning. The benefit I know for our CHRO, Jacqui Canney, is that she has a CHRO dashboard, and she can see so many things that are happening in the workforce. And so with generative AI, I think the ability to spin up a visualization of data that can actually be meaningful in taking an action and being able to see that in real-time, not lagging measures, but leading measures. So how are we actually -- when we take just an example of reskilling and upskilling, Jacqui is going to understand where do I build talent from the inside, where do I buy talent from the outside and what do I borrow? And that alone, if you get an 18-month proactive decision, think of how that can change your business.

Think about -- so you said something then that most people don't think it was where do I build, where do I hire and where do I borrow? I think that, that whole concept of borrowing, for me, that just makes work so much more enjoyable. Knowing that I'm not necessarily going to be able to do the same thing, that I can have this agile capability of potentially being allocated somewhere else for a specific period of time. And as you said, Jacqui has that visibility of the whole organization. So it's not like there's a fear that there's no job to go back to. You have that whole dynamic landscape layout.

That's right. And I say the CHRO role, it's such an exciting time to be in HR and certainly to lean into GenAI. It's becoming -- that role is sort of becoming what I call the COO of the talent supply chain. So much like we think about the inventory and movement of product. Like if we can scale that to people in a meaningful way that they're digitally raising their hands for opportunities, and we're digitally tapping them on the shoulder and the flow of work for those opportunities, we can drastically impact the amount of productivity that we have across our employee base. And if Jacqui can actually go to the Board and say, "This is the reason why I'm going to go after this specific talent on the open market and I'm going to make this investment in what I buy versus what I build because I can massively reskill and upskill people. I can move the ship very quickly." That is the definition of agility.

Right. Do you think -- this is kind of a different question, I suppose. I was writing something the other week based on observations I've seen and stories that I've heard about how different people from different generations use AI. So I very much ask it something and expect an answer as a direct question, whereas we were saying a lot of kids will get the AI to adopt a persona and then have that conversation with a persona. Do you think as we move forward in human resources, there will be more steps forward in that kind of agent focus around can I create a digital persona that I can ask questions to and get answers from a management perspective?

I think absolutely. I think that traditional HR, when we think of -- we thought of it as sort of this operations of a function. We never thought -- and who knows, we may not even call it HR in the future. In fact, we've been moving towards Chief People Officer because of the focus on employee experience. With GenAI, we're going to have more HR people building product because we have text to code. So we're going to have product managers. We're going to be analyzing more things. The skills that are required in this thing called talent strategy and people management is going to drastically change. So GenAI is going to essentially make me, the noncoder, able to develop applications and solutions like immediately and then put them into practice. So I think when we talk about the younger generations, and I'm out there telling like my own kids that are graduating from college and thinking about the field they're going to be in, this is an exciting time to be in what we call HR today. And if you're -- whether you're a product manager or an engineer or hey, you never know how this discipline is going to evolve, and GenAI is going to be at the heart of it.

So really cool conversation, Kelley, about a really interesting time and where we are. I am getting the light to move on to the next section. What we're going to do is we're going to do Q&A in a few minutes. But based actually following on from what you were saying then, Kelley, do you want to kick off this section and give us a few of your thoughts around how you see this developing?

Well, much like you said, Dave, earlier, is that AI has actually been around for a long time. I think that GenAI made it a household name. And we started with diagnostic, went to predictive and now generative. This is the game-changer. So this is a great quote by Josh Bersin, who said "The future of HR is fewer support agents." Remember, those people just churning sort of paper in the back end and more consultants, remember high touch, high value, more product managers, designers and advisers. So this profession is changing. And guess what, GenAI is actually the perfect solution because it means more and more HR teams are building things, analyzing things, which is the core essential value prop on AI. So he goes on to say, "It's the perfect solution," right? So we've been saying in HR for a long time, we want a seat at the table, we want to add value, product build, product engineering did all the coding, but guess what, generative AI sort of hands us this opportunity to do things so differently to build our own solutions in our own function. And so this impact of GenAI is really going to create HR as more of a strategic and data-driven organization. So if we look at this chart, and this was a study by BCG. And you look at like today where we are in sort of the divisions of time, like how do we spend our time in HR versus the future, we are going to drive through GenAI this transformation towards more self-service, higher levels of productivity and experience enhancements. And I've been saying for a long time that HR is getting consumerized, right? What do I mean by that? We are able to scale personalization. So with this technology, we're going to understand more about you, just like marketing studied the personas of the audience. We're going to know everything about you that you want us to know so at the right time, we can deliver the most relevant experience with high levels of satisfaction. Think about that. In the old days, it was one to many. Now we're going to really be able to drive a more comprehensive data-driven talent strategy. And it goes on to how that is impacting traditional centers of excellence. So when we say centers of excellence, we mean total rewards, leadership development. These are the kinds of things that we've traditionally had as sort of subdepartments within HR. And if you look at this data out of the study, GenAI is going to create greater than 50% efficiency gains across all of these areas of HR. So if the function was about high value, high touch, this gives us that time back to say, how do we change these roles in HR to deliver those consumer-like experience? So we have time, we're going to be doing more text to code. We're going to be building more solutions, and we're going to be delivering on that promise.

I mean it's a -- I think the impact of this is underestimated by so many people, and that's a really nice point for me. So thank you for just giving that, Kelley. We'll come back for Q&A. But I just wanted to finish off a little bit by talking about what ServiceNow's approach to GenAI has been through the creation analysis. So our strategy is to build trustworthy human-centered AI. And how we do that is by looking at how we control our LLM. So we use logging. We use moderation. We take feedback. We do test sites. And we look at capabilities based on use cases. So it allows us to learn from experiments. We can deploy quickly with things. We can iterate some things. And then we can allow people to actually show the trackable business value. Plus, we're investing in AI training again about that transparency, that visibility so that people don't just understand how it works, but they understand how AI can actually help them work, give them some insights into what they can do with it. And I guess the interesting thing you touched on it before, Kelley, is that the AI isn't new, and it's definitely not new for us. It's something we've been investing in for years. And it's allowed us to be very strategic and intentional in how we've acquired companies and incorporated those technologies into the platform. So we've been able to go from predictive intelligence to conversational intelligence, looking at intelligence search, looking at task intelligence. And then last year, as you said, Kelley, when we actually did the Hitch acquisition, we started to understand how we could build skills intelligence into the platform. And as we worked on progressing that work, we looked at how we developed LLMs. We realized we needed skills around that as well. So we actually look to acquire companies like Element AI to be able to get that expertise in the platform. But when we've done all this, we've been responsible around how we've done it. We've made it human-centered. We followed human-centered AI guidelines. You talked about it before. We have the uniform Now Assist admin consult, so people can turn on and turn off GenAI skills by product. We've used customer support in AI research and designed programs to make sure that we have that diversity, that we have that inclusion. And again, I think those domain-specific LLMs directly integrated into the platform help that. You're making sure that you've got the data where you need it to be. And the last thing that we did is we made it transparent and accountable. So customers have always come to us right from the start with worries around how data is going to be shared. So now we give customers control over how they share that. And we've got documented product capabilities and limitations, things that we can't do. We talk about how we actually handle data and go through that whole data-handling process. But at the end of the day, everything we do puts the employee at the heart of our platform. So this is about automating away some of the tedious tasks, but letting people solve problems on their own, letting people help the enterprise become more agile and linking the results of GenAI insight into action. That's one of the great things about having that on the one platform. I can find out what a probable cause is and then suggest the probable action to save it. But for the people who spend every day fixing people's problems, we can give them overviews and insights to help them work more effectively. We can get to reduce the workflow by allowing people to get answers to their issues and have a full engaging experience. We can give them that full natural human language experience. We can generate content automatically. So we can do anything from work notes to knowledge articles and even help developers out with recommendations for code. So hopefully, once they get used to that, that means more time spent innovating and less time spent coding. So everyone is looking for ways to transform and optimize. And if you transform anything and you want that transformation to be successful, then you have to provide a better experience. And there's no better technology, I think, than generative AI to actually change what that experience feels like. So with all that said and with all that covered, and it's been a great session so far. We've had questions that have been coming in from the outside. So we're going to open up to the audience, and I'll just look down now and pull out a few questions and maybe we can choose who's best to answer it, Kelley. So the first one that's come up is what steps do you recommend for an organization that is just starting to define the GenAI strategy?

Yes, I really think understanding the use cases with the highest value for you as an organization is really important. In fact, if I could draw a box and say, these are high value and easy to implement, starting with those, right? So you always want to go -- because the viral nature of GenAI and the adoption phase, like people are using this in their iPhones, so they're using it kind of in their personal life. But if you can actually demonstrate value early, and we certainly have made GenAI very easy to implement, right, because people get it. But if they get the value quickly, then we can move on to other use cases that are more complex.

Okay. So kind of low-hanging fruit with high value, that's where you start. I think that's a good advice for anyone. Another one that's come up, and again, I'm going to throw this to you first is because we kind of talked about this, but we never defined it. Who should own the AI strategy within an organization? Because I feel it was just kind of given to the tech guys somewhere, and they didn't necessarily want it. But should it be if you're doing a human resources rollout, should it be within human resources?

Well, I definitely think when the CEO -- gosh, was at the end of '22, but any CEO, I'm sure, put their team in a scramble, right? We need an AI strategy because I'm sure his boss, the Board of Directors was saying -- or her boss was saying, "You need an AI strategy." So everybody ran to their places, right? What are we going to do for HR? But I would argue that there should be a collective view. HR needs to represent some of the employee experience, as I mentioned earlier, conscience of the organization, decide how to hold the organization accountable. And there should be sort of a committee of business leaders that are -- have some governance around the AI strategy because if left to everybody go to your places, we'd have a lot of fractured experiences for our end-user employees and we probably wouldn't go to the use cases that have -- generate the most value for the company as a whole. So this needs to be done in a unified way.

I think you're right. And sometimes you see this appointment of chief AI offices, but I think that whole concept of having a committee, whether you want to head it up with a Chief AI Officer is a different question. But having that committee where everyone understands what's going on and everyone starts to make logical solutions, I think that's the approach people need to start to think about. Otherwise, it becomes a bit like people's cloud strategy, where everyone will just go off and do their own thing. And then you're going to have to crawl it in.

I think I mentioned the Chief AI Officer may be the head of that governing body to pull it all together. But I think without the voices from across the business, we cannot represent the customer holistically or the shareholders holistically, yes.

Right. And the last question, and this is probably all the time we're going to have time for, so we are going to run out. But this question has come through, saying, you talked about the hype cycle for GenAI. Is GenAI a bubble or will it last? And I guess if you think of -- and I know I did this like 2 years ago, every conversation I had was about the metaverse. And everyone wanted to talk about the metaverse, and then that just kind of popped. For me, I don't think it is a bubble. I think it's a -- or if it is a bubble, it's become almost structural. There's so much investment, so much expectation put into this that I think even if people don't get to the ultimate dream as quickly as possible, I think it's always going to be here. I don't see this getting switched off now. I think this is out of the bag.

Absolutely. And I think the message just to the HR audience is to lean into the opportunity here, which is enormous. So I hope that we have sent that signal that this is a game-changer for this discipline we currently call HR. I really do.

Absolutely. I have got to the point now where we have run out of time, but I just really wanted to thank you, Kelley, for your insights, for your experience. I know we didn't get enough time on this to go through everything. We had some great conversation.

Never enough time.

Never enough time. But for everyone who's watching this, if we didn't get to your questions, then we'll be sure to follow up via e-mail. And just let everyone know, this is part of a series of conversations here from the minds of our top leaders and executives. We've got one more conversation coming up this year, a very germane conversation based on what's happened in the last few days. But please join us in November. We'll talk a little bit about how companies can strengthen cybersecurity and resilience. If you want to revisit what Kelley and I talked about or you want to share with colleagues, then this is a webinar that's downloadable so you can pull it back on demand. And with that, I'd just like to thank you for joining us and say that we'll see you next time. Thanks a lot.

Yes. Thank you.