How to Build an AI-First HR Organization
In this episode of the HR Leaders Podcast, we speak with Brandon Roberts, Group VP, People Analytics and AI at ServiceNow, about how AI is transforming talent management as we know it.
Brandon shares ServiceNow’s Four Point Plan for building AI-first organizations, highlighting how real-time skills data, agile workforce allocation, and reskilling are changing how companies attract, develop, and deploy talent. He explains how HR must build strong partnerships with IT, invest in AI fluency, and completely rethink talent management for the age of AI.
🎓 In this episode, Brandon discusses:
The future of talent management
Talent management in the age of AI
Why HR must reskill itself for the AI era
ServiceNow’s Four Point Plan for becoming an AI-first organization
How implementing AI requires the right mix of people and processes
Deel is the all-in-one payroll and HR platform for global teams.
Deel helps companies simplify every aspect of managing a workforce, from onboarding, compliance and performance management, to global payroll, HRIS and immigration support.
Deel works for full-time employees and independent contractors in more than 150 countries, compliantly.
And getting set up takes just a few minutes.
Brandon Roberts 0:00
What I think is very clear to me is talent management needs to be more agile. Like, fundamentally, that is the challenge, right? Like, no longer. Can you say, I hire a person for a role they do the work for? You know, it just doesn't work anymore. And AI is making it easier for us to really measure skills and use those skills in real time to reallocate people towards work, and I think that's the unlock, if you know, I think most organizations haven't figured that out yet. I think ServiceNow included, we're still trying to figure out exactly the way that works, but that's what AI is going to change from a talent management perspective. It's going to give us this opportunity to say we're going to move people to whatever our priority is, and we're going to move them quickly so that we can get The work done we need to as an organization. You
Chris Rainey 1:03
Hi, welcome to the show. How are you? My friend, I'm good. Thanks for having me. Yeah, I'm sorry that we didn't get to cross paths in Vegas, yeah, which was time, which for the audience, sounds like weird, but just so you know, we were there for events. You had your work related, okay? Yeah, I was unleashed, and you were at your knowledge conference, which was you literally took over the whole of Vegas, which, that's the goal. Yeah, go. The goal is everyone that we got to take Vegas as Oh, but how are you? Because I know it was quite a few days, and there's a lot to take in, I'm sure, along. Yeah, I'm good. Had
Brandon Roberts 1:39
a week to recover now, so I'm back on it. Ready to have a good conversation, amazing
Chris Rainey 1:44
before we jump in. Tell everyone a little bit about your background and your journey to the role you're in right now. Yeah.
Brandon Roberts 1:50
So I currently, I'm the Group Vice President of people analytics and AI, and I've spent the last 20 years or so in the people analytics, data science space. And, you know, I kind of think about my career in sort of three parts. I first started at Qualcomm in the early 2000s and you know, that was when people analytics was just coming on the scene. Like people analytics teams were rare back then, and got the opportunity to really Qualcomm was about 12,000 employees when I started to build their people analytics team. So was the first person on that team. Centralized a bunch of resource analyst analysts we had and built an analytics function. I was there for eight years. Learned a lot i My background is in Organizational Psychology, so I knew nothing about data engineering and automation and everything you need to know to be able to support an organization of that scale. So that was a great experience. And then, you know, in about 2010 I got the opportunity to go work at Pinterest when it was a few 100 employees, still a startup. And that was, that was like such a different experience. I was still there to build the people analytics team, but coming into a company of that size, where you didn't even have an HRIS fully implemented at the time, and really building from the ground up, from start to finish, just an incredible company, incredible culture, incredible time to be there. And then, you know, about six years ago, I got the opportunity. Actually, we were just talking about Pat waters. Pat waters recruited
Chris Rainey 3:27
me. Yeah, she was
Brandon Roberts 3:30
the CHRO at the time, and so said, Hey, do you want to come build the analytics team at ServiceNow? And so been there ever since, watched the team grow over the last six years. Watch the organization grow. Been fun to be at a company that's so central to this AI transformation that's happening, and to be able to build AI for the HR function today.
Chris Rainey 3:53
Wow. What a journey. You were there from the all the way from the inception, right? I think back then it was probably HR analytics, yeah, not people analytics.
Brandon Roberts 4:05
So I like, I remember at Qualcomm reading, like, what Google was, because Google was just starting to to build their people analytics function. I was like, we got to do this, this. This is the future. Yeah,
Chris Rainey 4:19
we had a little people analytics network that we built back then as well, where it was so new, and people like Don kinghoffer over at Microsoft, and others who came from within the business to this brand new role that was created so everyone, we were bringing everyone together, and it was like that must be Really something exciting for you to be at the beginning of something which now is one of the most important functions within an organization. Yeah, I'm sure. And I'm sure you're getting a lot of questions with because now you've got aI yeah
Brandon Roberts 4:56
as well. And there's been such a like, so many different stages, right? Like. Think in the beginning it was all just about dashboards and just trying to get, you know, automated metrics to somebody without having to manually use Excel for everything. And then we sort of figured that out, and this new challenge with predictive and AI and how you actually help the organization make decisions so very It's been fun to see the different stages, and I'm sure there's going to be more in the next few years,
Chris Rainey 5:20
we can only imagine with agents and the advances of Gen AI is just going to get even more fun along the way. How does it feel good? Way to describe it like you got you have to either smile or you might cry, so you're gonna just gotta choose one. How does it feel to be in an organization leading the people analytics and AI function in a company just also delivering this to its customers. That must be really fun. And what type of relationship do you have with the Product team? It must be cool. Yeah, it is.
Brandon Roberts 5:53
It is, and it's one of the things I'm really thankful for in my role, is you get this. You sort of have two parts to your role, and one way, you are very much a part of the product and working really closely with the product organization and our internal teams that are implementing the technology to say, what would we want to build? Right? What could we build with AI that will really help the HR organization? And that is just an incredible it's a very different challenge. One of the things I've learned along the way is building something internally is hard. Building something for 1000s of different companies and customers. It's impossible. It is so much harder than what we have to do focusing internally. And I love that. I think that's the fun part. What are the kind of core challenges that every HR organization across all these different industries are facing, and where can we really differentiate from the competitive landscape and create AI that really helps deliver value for the organization? So that's definitely a huge part of it. And then I think the other great part about working at a company like that is just the level of engagement internally. Like there's no convincing anybody that this is the future or that this isn't that we skip that step, like everybody's bought in, and it's about, how do we really get to value quickly? Yeah, I love and that's why
Chris Rainey 7:17
so excited about this conversation. Because you're you're you're building this playbook internally of how to become an AI first organization, yourselves, and then then you're then also delivering that for your customers on your on the other side. So you're living and breathing, practicing what you preach as it, as it were. But that's constantly evolving with the rapid technology advancements that we see. I'd love for you to share service now's Four Point Plan for becoming a AI first organizations. The fact that you have a Four Point Plan
Brandon Roberts 7:53
is already impressive enough. We've been working at this for three years. And you know, when chat GPT exploded, everybody was sort of like, oh, this is new. We've got to figure it out. But my experience at that time was everybody was like, what, what are we what are we doing? Like, where, like, which way are we going, and what do we need to be doing? Specifically within HR was a question that I was talking to customers a lot about and we were thinking about internally like, what is our role as an HR function in this transformation? And so what we tried to do with the Four Point Plan was really think through the different roles that HR needs to play in driving this transformation, both within their function right, to make us an AI first. Ai powered HR organization, but also all the things that we need to support, support as this AI transformation happens across the enterprise. And I think that's one thing I always remind people about, is that we sort of have two roles in everything that's happening with AI. We have we've got to make this HR function AI first, and then we also need to support the enterprise and the transfer. Transformation. So the Four Point Plan was our way to say, these are the four things that we need to focus on and really get accomplished to make the organization successful. And so the first one, I'll walk through all of them, but the first one we call implement an AI operating model. And I really encourage organizations that haven't done this yet to pause whatever you're doing and go back to this step if you haven't yet. The concept is there are AI ideas that exist everywhere in your organization, you know, and you'll you see it right? Everybody's raising their hand with an idea about how AI is going to make them more effective, and the use cases and different ideas that will help their team or their organization. How does that idea go from a concept to reality in your organization? And when I ask customers that a lot, or when I talk to customers who are on this journey, usually there's not a clear answer to that question, and I think that's. That's really important is, okay, an employee in your talent acquisition says, Hey, I've got this idea. I think we can use AI to do XYZ tasks. What happens next? And for us, that meant the idea goes into a workflow, and our technology teams quickly assess that idea for effort and value. So we try to get any idea that's submitted. We've had over 500 ideas submitted to our organization. We assess it on effort and by value as quickly as we can, usually within two days. So just high level, is it valuable? Is it worth investing the time and effort? Then what happens is there are tons of other stakeholders. If you feel like it is valuable, so if it gets past that gate, right, legal, it, data security, data privacy, all these different stakeholders have to be involved in the process. How does that work? Right? Do you have a consistent way that that should work in your organization? What's your governance process? How does that all work? So that the idea goes really quickly from idea to reality. And so we've spent a lot of time in the beginning spelling that out, and we call it like our AI factory, right? Basically idea to actual delivery. And I think what my goal has always been that any employee in HR, if they have an AI idea, they know how that process works. They know what they would need to do, where they should start, and how to ultimately, you know, get it to value. I
Chris Rainey 11:28
love that. What? What is the I know you got many more things to share, but I've got a few questions before I forget. What is the process of of submitting that? Yeah, so, like, tactically, like, how does that
Brandon Roberts 11:41
work? Yeah, there's a this workflow flow company that I know about called service now that builds workflows. So that's what it is. So we built it all on service now, so an employee submits an idea, right? Like, goes through and they can actually, what's amazing about it, idea gets submitted all the right? People are notified. There's approvals, right? There's, you know, all these things are built into the workflow so that it's a nicely spelled out process. And yeah, you know, that's generally how it works.
Chris Rainey 12:14
And do you have you mentioned the different people that review? Do you have, like, a AI Ethics Council that reviews it together, or is it like individuals? I can you want to also make sure there's not a bottleneck somewhere. Yes, in that, and that's
Brandon Roberts 12:28
why that that first gate, I think that's really what I find, is like people go directly to the governance and ethics, and then it kind of can slow things. Doesn't even get to that part. Yeah, effort, value first, right? Is it going to be valuable period, right if, and then get to the parts where you really have to work through sometimes and figure out exactly how you know. So I think that's that, that part of it is really, really important. Now we do have a governance structure. So we have an enterprise AI Governance Committee, which is cross functional, um, thinks about everything related to AI for ServiceNow, including our product. And then we have an HR AI Governance Committee, and that's specifically, you know, employment law, data privacy, all the stakeholders that I talked about previously. And so once the idea gets past that initial gate, it goes to that committee just to flag, hey, is this high risk? Do we need to go deeper, or can we just advance it and
Chris Rainey 13:29
start executing love that well. So what are some of the other points on the Yeah, yeah. So the second
Brandon Roberts 13:35
one is the one that I hear a lot of people talking about, which is build the tech and data infrastructure, like building the foundation that's going to ultimately allow you to be an AI first organization. So there's a lot in here. I think you know a couple things I'll call out just quickly. First is really having a strategy about your technology and where you want your AI experiences to be built and live and interact with your employees. I find a lot of organizations are, you know, using point solutions or creating agents in specific areas. I think that's not going to be the way of the future. We need to figure out a way to bring these experiences together, creating a single experience platform that really helps you. You know, you know, you don't have to remember where the agent lives. The stat we already cited service now, the average company has 80 different employee facing systems, so the employee has to remember all that. And if there's AI in every single one of those, they have to remember that. So how do you create whatever your strategy is, wherever you think employees should be going to interact with your AI? What is that? And really putting that down on paper is key to me. And then the second piece is really the data. Data is ultimately the driver of whether AI is going to be successful. So centralizing data, bringing data together from different systems, thinking critically about what data is really going to be needed to drive whichever use case you're going after. Future, and then quality, you know, really having an approach to data quality and investing in that space. So the example I always give is, you know, we built this AI, what we call AI search. And what it does is, it takes all our policy documents, it indexes them. An employee can go on and search, what are my benefits? And instead of having to sift through the 200 page policy document, it says, Oh, we know that person is in this country at this level, here's the answer. It's very similar to what the experience you get on chatgpt or Google externally, but we built it internally for all our policy documents. But what happened was we discovered that our policy documents were not call like high quality enough, and where people are getting the wrong answer. So we built a way to really assess that and measure the quality of those policy documents, keep them updated, measure and ensure that they're not getting out of date. And so those are the types of things that I think organizations need to start really thinking critically about what data is going into your model, and how do you, you know, really assess the quality and make sure you're staying on top of it?
Chris Rainey 16:06
Yeah, I love the part about the experience, though, that you also mentioned. Correct me if I'm wrong, Lloyd's. Lloyd's is a customer. Yes, right. So I was interviewing their head of AI and people analytics technology in Studio A few months back, and we were talking about agents, right? And everyone's fighting to be the the master agent, as it were. And he said to me, Chris, you know, I could, I could turn on five agents tomorrow, you know, from our, from all of our different tech stack, like they all have an agent, but we chose service now as the main agent. And I was like, why? Like, you know, why is that? And kind of like, what you said, he was like, it connects and plays nicely with all of the other tools and platforms and is creating a consistent experience for their employees to connect that and bring that all together. And I thought that was really, really interesting. And I'm hearing that a lot with many companies now that are turning to service now, not, and this is not sponsored by service now, by the way, everyone listening right now, but so you clearly there's something you and the team are doing really well to ensure that you have that consistent employee experience or customer experience, or that everything's feeding into one agent within the
Brandon Roberts 17:20
AI, yeah. One of the things that we do, which I think does really help, again, thinking about the employee as the user of these AI use cases, we are not function specific, so ServiceNow doesn't, yes, exactly the agent, is it or finance or, you know, doesn't matter. We create that, like seamless, that consistent experience. And the employee goes there and says, Okay, I got a question. I don't even know if it's HR or finance, so I mean, 100% Yeah, yeah. That's like, exactly. I totally where there's already companies
Chris Rainey 17:51
right now where you've got, like, I know friends of mine are very large organizations. They've got like, four different agents, all right, like, or, you know, chat interfaces that they have to talk to to go here, to get this material, to go there. And it's just a bit of a nice like
Brandon Roberts 18:04
thinking that has to happen to know which one answers your question is like, yeah, just we're trying to solve
Chris Rainey 18:10
for that. Yeah. It kind of defies the point of having the technology in the first place. And and, yeah. The other point you mentioned many to come to speak to that when, when I when they talk about ServiceNow, one of the first things that they they talk about is the fact that they love that they can find their employees and their company can find access to the resources and their materials straight away, and the ability, like you described earlier, to help update that. Because before now, it was just a disaster. You had this information sitting in silos across the organization, in random internets somewhere, you know, it was just a bit of a mess as well. So that's such a like, it sounds like, you know, it sounds trivial, but it's actually a use case that comes up all the time in my conversations as the thing they appreciate most. Yeah, and
Brandon Roberts 18:57
it's such like, an interesting experience being at the company, because it is literally, because everything we do goes into the service now it's one place for everything. You just start you ask the question, like, all, think about all the complexity that sells for So, yeah, it's
Chris Rainey 19:14
a lot less, a lot less tickets for the HR team. Yes,
Brandon Roberts 19:17
yeah, reflection, right. And like, we've seen that with a lot of the AI solutions, we're seeing a real reduction, yeah, in, you know, tickets and the amount of work our ops organization has to do,
Chris Rainey 19:28
yeah, a lot of unlocked hours. I'm interested to see how we utilize those unlocked hours. I think that's going to be an interesting part.
Brandon Roberts 19:35
Yeah, like, yeah, that's, to me, that's, that's what we one of the things that the HR organization really needs to lean into is we're starting to create this capacity. It's starting to get real. How do you reallocate that to something important and strategically important for your business? I think is that's something we should do. That's workforce planning, that's, you know, things we should be thinking about as an HR organization.
Chris Rainey 19:59
Yeah. Yeah. Where are we at? We're at point three. Oh, yeah, point three. Okay, sorry. I love, I love this, back and forth. This is great. I love it. I feel like we're doing your TED talk right now. It's like the master.
Brandon Roberts 20:10
This is great. Not as, not as smooth as
Chris Rainey 20:15
rehearsal. You know, we can, we can use AI to narrow it down.
Brandon Roberts 20:20
That sounds good. So the third pillar is enablement, which is just re skilling up, skilling everything we need to do around the technology to be successful. There's a lot we can talk about here, but you know, one of the things that we did internally, which I think is really valuable, is deciding on what is really what do you want to build? What skills do you want to build within your organization? And so we've kind of landed on this, like three pillars, which is the first one that we call no AI. And every employee in our organization has to have this foundational understanding of AI, responsible AI, what it can do, what it can't do, what tools are available. That's something that every single employee needs to understand. The second pillar is what we call use AI, which is, if you launch a technology meant for a specific role or function and you do not provide training, I will guarantee you it's not going to get adopted. And we've seen this with AI solutions. So we were talking about ops and shared service agents. We launched this functionality that okay, let's say someone submits. They want to change their benefits. They work with an agent back and forth. They're trying to get all the information. Then that agent goes out on vacation, new person takes it over. Right in the past, they had to read through every single communication that's ever happened before that case got to them. What the AI does is it summarizes all of it and gives them a nice little Hey, here's what's been done. Here's what worked, here's what didn't work, here's everything you need to know. Great functionality. We're finding it's making people more productive. But we launched it and no one used it. And the reason no one used it is because they didn't understand what was going into the model, and they didn't trust so they, they were like, Okay, can I actually rely on this summary, or do I still need to read through all, you know, all the documents, all the emails that happened before, simple idea of, you know, five to 10 minute video that just explained, hey, this is the data that goes this is how you should use it. You know, it's really obvious. But if you ask people if they've done it, I find most organizations are not really consistently developing that training around the use cases that they're launching. So that's been really, really key for us. And then the third one is what we call build AI, so all the technical skills, and we really believe, yes, engineers and it needs to build the technical skills. But I think where this is going is very much that everybody needs to build technical skills to manage agents, to use agents in their day to day work. So how do we build that, what we call citizen development, so that it's not just engineers that are building AI use cases, but that every employee across our organization can build AI into their workflow or what they're doing.
Chris Rainey 23:02
I love that, and you you can assume that people know how to use these tools. I think I've made that mistake before. You know, we built our own AI agent Atlas, which we fed with all of the 10,000 hour plus of our content, and we're training it constantly, and we handed it out to all of our community and users to access our podcasts, our recordings from the events, and just assumed that they would know how to get all of the value from it. And we we were mistaken. So I had to create a series of videos just like, very basic stuff, like, like, of how to use it, and people, oh, I didn't realize I could even like, oh, like, because I play around with the tools every single day, and I'm sure you're the same, we just assume everyone does and has that and has that level of competency as well. How do you How does content show up in the plan, in the agent, like, if you have a video, does it like link to an external video? Or have you been able to make sure that shows up in the flow, in the same user experience, because that's something we've just we've just integrated video, audio and documents into the interface of the AI, so you don't have to go somewhere else, because that seems to be a challenge for companies that they'll have, like they'll have it and then, okay, you've got to go over here to our LMS, yeah, or here to, you know, does that make sense?
Brandon Roberts 24:17
No, totally. It actually very much ties back to that, like data infrastructure topic I was, where do the videos actually live? Because if they don't live on where you're building the AI platform, or you can't pull them in, right? You're not going to be able to show them in that experience. So what you know, I think we have both actually, in most some cases we're linking out, in some cases, the video is embedded in the experience. And I think goal, right long term goal, is that you don't have to go anywhere. It's all in one experience again, but it's a little bit of both, right now,
Chris Rainey 24:52
yeah, that we've just gone we've now removed arms just within the experience now. So we today. Point where you can even ask the agent a question, it will take you to the exact second in the video the answer that answers your question, or the exact second in the document that answers that. And you can actually talk to the video in the agent and have a conversation with that, or even turn the document into a video and the video into a podcast, so you can kind of play around with how you want it without taking people externally. And I think never requested, I'm sure, and I know you guys already do this is like everyone's it needs to show up in the flow of work as well through the other communication tools, so making sure that it can be accessible via things like teams and slack. And because I think, I think I saw something the other day that the average employee has like, 15 apps. Yeah, it's kind of crazy.
Brandon Roberts 25:49
Yeah, that's actually seems low to me, but like, yeah, yes, it does feel like that. And I think that integration, and again, meeting people wherever they're at is key to adoption and to actually getting value. Yeah, what was, what's the fourth pillar? Okay, last, last thing, and this one is, you know, one of my passion points is, AI, we really believe, and we've seen, in a couple areas, a huge ROI for the investment, but there is an investment upfront. And I think investment doesn't just mean technology, it means talent. It means getting people into HR who really understand this AI transformation, having a leader within your function who's responsible for building all the things that we've been talking about today, I think, is really, really key, building that investment, building that business case, and then really thinking about, what are the outcomes of what we're investing in, and how do we actually show that this is returning value to the organization? I think, you know, one of the things I see a lot in talking to people who are implementing use cases, they'll say, oh, you know, every time you use this feature, you save five minutes. And that's great. That's wonderful. What happens with that five minutes? Yeah? Because if it just goes to the into the ether, and you know, someone's whatever they're doing with those five minutes, and it's not tied back to some sort of plan about how to reallocate that capacity. Hey, we're going to take on this additional work. We're going to move people who had previously done this work to new roles so that they can, you know, upskill and do things that are more strategic or valuable for the organization. Those are the types of conversations that I think we really need to be focused on, especially as you know, in my mind, these capacity gains last year were like on the front, on the edges, it wasn't huge. I think some of the use cases that we're starting to see this year and into next year will create more and more capacity, and we need to think within HR, how do we manage that? How do we make sure we have the right workforce to support the work that we actually want to get done?
Chris Rainey 27:58
Do you think that most companies right now have the skills and capabilities within their existing HR team to do this. So
Brandon Roberts 28:07
I think so there's, there's a scale to that. I think so we've built this, like internal, what we call the AI control tower. It monitors all of our use cases. It says exactly how much people are using. We have assumptions about how much capacity that is. We're real time monitoring this stuff and seeing the value, and then trying to take that back to our workforce planning council and say, hey, you know, we're really creating capacity in this organization. Let's think about what that means. How do we upskill or move the talent to new roles so that they can deliver more value for the organization. But I do think there's a there's like, a simpler version, like that everybody can be doing like that's great to measure everything, and, you know, use all this data, and fundamentally, it's if you're implementing a use case. Do we think this is going to really affect how many people we need to do the work today and just having a conversation. I mean, it's not as scientific, maybe, but I think even just having the conversation and thinking about that as you're implementing use cases is something that every HR organization you know could be doing. One
Chris Rainey 29:14
of the common things I hear, both in my private conversations and even during during some of our shows, is is that when HR leaders are bringing in different AI solutions, it just gets to the IT team and just gets stuck, and it doesn't go anywhere. And someone described it recently, they're just piling up on the desk of the IT team. What advice would you give to HR leaders, listening and of how to you've already shared great of us already with the model and like what you shared in beginning. So there's a lot there. But if you could kind of summarize that, like, what would be your main advice you would give to them to ensure that this becomes more of AI, suppose a partnership as opposed as opposed to sitting of it, they'll get back to us.
Brandon Roberts 29:58
Yeah. Yeah. I I think that partnership is key. And I think, you know, we within HR have to educate ourselves on the challenge, the challenges that it faces. So all those things I talked about, you know, if you talk to most HR leaders and talk about data architecture and integrations and where data is flowing, you know that is not usually a topic we spend a lot of time talking about, but we need to, because these are the things that the reason that that's happening right where you have this great idea and it doesn't end up working out when you actually go to implementation or execution, is because of challenge. It's not because they're not smart, or it's because of some of these challenges we talked through, not the right skills in the organization, not the right data in the right place. You haven't thought about that technology experience layer, and that creates a lot of challenges. So I think building the partnership, listening to the challenges, and then I also, again, think building the expertise within HR so that you can combine your knowledge of the use case with the technical knowledge needed to actually execute it. I think the problem is that too often we're sort of, we have this idea, it's a great idea. We don't understand all these technical challenges that they have to face to actually execute it. And so I think building that expertise, you know, I talked about the concept of investing in talent. I think that's another way, right, build the talent within your team, someone who can really partner and interface with that IT organization and, you know, hold them accountable, but also, like, listen when they're facing challenges and change. Yeah,
Chris Rainey 31:39
one of the You are our last AI HR summit in December. And one of the things that I saw immediately that comes that are really thriving companies are re thriving is places they have a really strong relationship with their CIO, their CTO. Throughout that event, we had many kindred did a session with their CIO CTO, and many others and like that relationship is so important, but in the past, that tradition in me wasn't really as important. But right now, those are really succeeding, having really candid conversations, have really struck strong partnerships with their CIO and CTO, and
Brandon Roberts 32:18
our work is getting so similar, like, is like HR organization is moving more towards it. And I think it's work is sort of moving more towards HR. Like tech we're fundamentally in, I think about service now. A lot of what we do within HR is implement technology to support employees journey, to support the employee experience. A lot of what we're doing is around technology. It's, yes, there are programs, yes, there are other things, but we are we need to build that expertise within HR to support the technology we need. And yeah, one of these
Chris Rainey 32:54
interested in asking you about in the age of AI what? And we had, we had a panel this Wednesday with 1000 CHROs talking about this, is that topic and six panelists talking about it in Age of AI, what does this mean for talent management, or the future of talent management? Because it's massively disrupting this space. Yeah,
Brandon Roberts 33:13
I think couple things I would say. Well, first, tell me what you think of it as, like talent management, what? Because I think there's like different
Chris Rainey 33:23
variations. There's loads we know. Where do I even start? Like we we spend, we spent time talking about building a skills based organization, and we were talking about talent marketplaces, and how AI is that was a lot of it, how AI is impacting that in so many different ways, whether it's job matching, whether it's gigs, whether it's mentorship, whether it's like connecting that to the talent intelligence like, I mean, we went down a whole rabbit hole. We did a whole series on that topic. Yeah, for sure,
Brandon Roberts 33:55
let's, let's have another 45 minutes to talk about that question. But what I will say is, what I think is, is very clear to me, is we need to talent management needs to be more agile. Like, fundamentally, that is the challenge, right? Like we no longer. Can you say, I hire a person for a role they do the work for? You know, it just doesn't work anymore, and AI is making it easier for us to really measure skills and use those skills in real time to reallocate people towards work. And I I think that's the unlock. If you know, I think most organizations haven't figured that out yet. I think ServiceNow included, we're still trying to figure out exactly the way that works, but that's what AI is going to change from a talent management perspective. It's going to give us this opportunity to say we're going to move people to whatever our priority is, and we're going to move them quickly so that we can get the work done we need to as an organization. And there's lots of challenges with that, people challenges. There's do people want to move that much? Yeah, but it's, I think, to me, that's, that's the real, yeah,
Chris Rainey 35:03
that was the whole, and I'm hunched with you, and that was why we did that session, because it was a, it was a, it was something that our community kept saying, cat Guys, can you please do a session on, session on this for the group? And one of the big parts we spent time on is the whole culture shift of that, like, you know, you're asking managers now to be exporters of talent, rather than hoarders, right? You know. And to your point, you know, people are so used to having, okay, this is where I am, and this is the journey up to and through the ranks, right? As opposed to, okay, I'm gonna go work on a gig over here for a few weeks, and then maybe I'll be over there. And you're no longer, you know, your role is no longer defined by a title, but by a set of skills that can then be applied across the business, that just changes everything your processes the way you're rewarded, just just every it's a complete, you know, it's less of a technology challenge right now. It's more of a transformation and cultural challenge, which, and that was kind of what we discussed many of the companies on the call yesterday were quite advanced on that journey using, you know, tools that are out there or talent marketplace platforms already, and are seeing incredible, you know, value, whether it's unlocked hours, whether it's retention, whether It's upskilling their workforce now, so they're hiring way more internally versus externally, which is obviously saving them a fortune. But there was one company on the call that, through their tenant marketplace, had saved 100 million last year. Wow, right, just through not recruiting externally and capitalizing on their internal skills, which was just like, wow, that's
Brandon Roberts 36:40
the, that's the skill of the future, I think, is like you were talking about, like we need leaders, and we need everybody who has this ability to accept that the change is going to be constant. It's already constant, but it's like, accelerate. And so I think that's, that's if I look forward to what we need out of our leaders in the future that, to me, that ability to embrace and accept change is really, really key. Yeah, what?
Chris Rainey 37:07
What's the main, the main way that AI is changed, the role of the people analytics leader and and the work that you and the team do? Yeah?
Brandon Roberts 37:20
So I think I'll say three things. So one is the interface is changing. No dashboards are going to go away, or they're going to be in the background or whatever. But the formal, the most consistent way that people are going to interact with data in people analytics is through agents. I think that's hard stop. We need to think about that. We need to think about what that means. We need to think about how we help that accelerate. But that that's one piece fundamentally, I think basic reporting is, you know, roles, basic data analysis roles will also not be where we invest our resources. That's been happening for a long time. Yeah, but, but I think most organizations still have a few like that. Are still doing work like that. I think that that goes away, and then I think it accelerates our ability to focus on really meaningful questions and deeper, you know, data science type questions. It's been a journey we've been on for 20 years, right? Moving from just a, can I just report from Excel spreadsheets, yeah, yeah. Well, we talked about in the beginning, right? Like that, that journey is, is, this is just, you know, you know, the hockey stick of, of that journey, and it's, it's something we've been talking about for a long time. I just think it's really here now, and we need to think about what that means. I think a really interesting question is, what does the future org structure of people, analytics teams look like? And you know, what are the actual talent and resources you need to support that function? Yeah,
Chris Rainey 39:00
a question that comes up a lot is, should, should people analytics even sit within HR?
Brandon Roberts 39:08
Yeah, yeah, it's in there's like, so service now has a, like, a federated model, so we have a central analytics team that measure that maintains our enterprise data platform right bringing data from everywhere, so it's all in one place, like I talked about. And then we have the experts today who sit within HR and have an understanding of the programs and everything that you need to know. On that side, I do think it's going to I think there's going to be a lot more centralization, to be honest, if you think about everything we just talked about with single experiences, I think it's not just analytics. I think it's a lot of a lot of roles that will be more centralized in the future, in there too.
Chris Rainey 39:47
Yeah, no, I agree, because this is not it's touching every single part of the business, yeah, and every single customer and every single process, yeah. Do you think this is one of the biggest moments of trans. Informations. You know, we talk about, like, the age of the internet, right, the Industrial Revolution. Do you think this is as is as big as that, or even bigger?
Brandon Roberts 40:10
Yeah, I tend to be on the side of it's even bigger. I think we are in the early days, where it's easy to say it's not delivering value, but it's very clear to me that there are some things we need to work through, and it's going I tend to think there's like the foundational stuff is going to take a little bit longer than people are suggesting, but I think the transformation is as big as people are saying, if not bigger, but I do think all the things we just talked about on that Four Point Plan are going to take time and for organizations to get there, and then we're going to see this huge transformation of business. I
Chris Rainey 40:55
agree, like the technology is evolving quicker than we can adapt in every way, in every way right, like what we're doing now. Only a few years ago, people were like, saying, yeah, it's gonna take 510, years. Like, no, it's right now. It's here. Yeah, there's some
Brandon Roberts 41:10
really Foundation, like, we could spend another 45 minutes talking about, you know, data security and who has access to data and how that works in the future. Because I to me, that's really the interesting question about unlocking HR productivity is we're going to need to be comfortable with data going to more places, to more people. We'll
Chris Rainey 41:31
say that for part two, listen, we could talk forever what we covered a lot there, but for people that perhaps maybe earlier on their journey, what would be your parting piece of advice? And then, and then we'll say goodbye,
Brandon Roberts 41:45
yeah, I think just one thing I really encourage organizations to do is go through those four pillars and say where you're at. Just say, hey, we haven't even started this. We're, you know, whatever we're a c minus in this, whatever it is. Just assess yourself and say, Are there things we can be doing today in each of these pillars to at least move us in the right direction? I think that's a really tactical thing you can take away. Yeah,
Chris Rainey 42:09
so for those that are watching this in Atlas, ask Atlas to create an action plan from this podcast and write up an email that you can send to your team. Love it to set up a meeting with those four pillars to have a conversation. It will take 10 seconds to do that, and you can actually action on this now. But where can people learn more about ServiceNow if they want to connect with the team and learn more?
Brandon Roberts 42:32
Yeah, so one thing is, we just launched actually a knowledge it's called ServiceNow University. It's free to everyone. It's it's literally you can learn about general if you don't have basic AI understanding. There's some general foundational learning if you want to learn about ServiceNow technology. Specifically, they also have like certifications where you can get become an expert in our technology. It's free, so go check it
Chris Rainey 42:54
out. Amazing. So wherever you're listening or watching right now, the links are going to be in the description. Make sure you go click there and check it out. It's free. Make sure you do that. If you haven't learned anything from this call, you definitely need to be stay ahead and change and upskill and rescue yourself. So make sure you do that. And also connect with Rand on LinkedIn, probably good place to follow you there. Appreciate you chatting, and look forward to doing it again soon. Sounds good. Thanks.
More from the HR Leaders Podcast
Brandon Roberts, Group VP, People Analytics and AI at ServiceNow.