This is episode two of Decoding the C-Suite, a five part miniseries from Recruiting Future about how leadership really thinks about AI, recorded with the leadership team at SmartRecruiters seven months into their acquisition by SAP.
The headlines about AI and the workforce are relentlessly grim: surveillance, layoffs, roles disappearing. Lehua Stonebraker, who leads the people function at SmartRecruiters, starts from a different place: naming the fear rather than managing around it. In this episode she explains how to build psychological safety when employees are scared to admit they use AI, why she believes the org chart is gone, how engagement went up during an acquisition, and a vision of a connected employee lifecycle that finally uses everything an organisation learns about its people.
Key Takeaways
- The org chart as we know it is gone; organisation design now has to start from outcomes and the work that needs producing, not job titles and fixed responsibilities.
- Leaders won't have all the answers about AI, but naming the fear beats managing around it every time.
- AI fluency is built on psychological safety, not technical skill; people can't learn in an environment where they're scared to admit they use AI.
- The real opportunity is using AI to make work more people-centric, freeing humans for judgment, complexity and conversations rather than just chasing efficiency.
- AI should never be the decision maker; it gets you to root causes and options faster, and humans decide what to do with them.
- Connect everything an organisation learns about a person, from application to onboarding to performance, and the employee experience becomes genuinely personal for the first time.
Transcript
Matt Alder: [0:18] Hi there, and welcome to Decoding the C-Suite, a five-part miniseries from Recruiting Future about how leadership really thinks about AI. The organisations genuinely driving AI change in talent all have one thing in common, which is alignment with the C-Suite. Winning that alignment means understanding how each person around the leadership table actually thinks, and that's exactly what this series is for. I'm talking to five senior leaders at SmartRecruiters, seven months on from their acquisition by SAP, each seeing AI through the lens of their own function.
Matt Alder: [0:55] We're starting with the lens closest to home for most of the audience, the people. The headlines about AI and the workforce make grim reading at the moment, dominated by surveillance, layoffs and disappearing roles. Lehua Stonebraker leads the people function at SmartRecruiters, and her approach starts from a very different place, naming the fear rather than managing around it. We talk about how to build psychological safety when your people are even scared to admit that they use AI, why she believes the org chart as we know it is gone, and her vision of an employee life cycle that finally connects everything an organisation learns about its people. This is Decoding the C-Suite, episode two, The People.
Matt Alder: [1:42] So let's talk about AI and people. The headlines at the moment, when we read about AI, it's companies using it for surveillance, measuring keystrokes, laying people off, roles disappearing. There's a lot of scary stuff out there. What's the emotional reality of that like within organisations, and how does that shape the way you think about the workforce?
Lehua Stonebraker: [2:07] It is true. I wake up every day listening to the news and I hear doom and gloom all over the world. And then you apply that to the place where you should feel safe, or you should feel trusted to be an expert in what you're doing. So one other added measure of a Meta headline to track keystrokes, or Oracle doing 30%, or whatever the number is in terms of layoffs. Those are scary things. I can't generally speak to how all organisations are thinking about it, but from a practicality standpoint, if you're wanting to have a surveillance and a monitoring system, are you just doing it for compliance? What's the goal? What's the purpose?
Lehua Stonebraker: [2:44] For our organisation, what I believe we're doing a little bit differently is really taking this moment to say we have to stay curious. You have to adopt an even faster learning mindset. It's almost like the playbook hasn't even been fully written and you don't even know what page you're going to turn to. If you don't stay on top of it, all of a sudden you become even further behind. So it's about being able to allow people to experiment with safeguards, helping them understand that the work is not necessarily meant to replace what they're doing. How do you use AI to not only take away that low value add, the administrative responsibilities, or create more efficiency, but actually use AI to be more people centric? Because now you're focusing on those scarce skills. Judgment, complexity, conversations with people, helping them understand the moment. Helping people come along on the journey is probably the most important aspect we can take, rather than having something happen to them.
Matt Alder: [3:49] How do you give them that psychological safety to do that? Because there's some really interesting data out there about people using AI at home in their personal life and then not using it at work, because they're afraid to or their company won't let them. How do you make people feel safe?
Lehua Stonebraker: [4:10] So at SmartRecruiters, a couple of years ago, we actually went and did a lot of discovery around our first organisational introduction into AI. The IT team and the InfoSec team surfaced something that they thought would be beneficial to all roles, so role agnostic across the organisation. That tool is Glean. It sits on top of ChatGPT, but what it does is allow you to aggregate data sources from all over the organisation that every unique person has access to. In my role in HR, obviously, there's lots of sensitive, confidential access and information. I don't want that to be pulled into a search or used in a prompt.
Lehua Stonebraker: [4:48] We did a bit of an organisation-wide experiment by creating a corporate goal around it. What would happen if we created a bit more efficiency? We used that as a starting point, and what we started to see is all of these interesting use cases and ambassadors that surfaced across the business that said, well, let's try and apply it in a different way. How do we collaborate a little bit faster? How do we get to the information? How do we solve complex problems in a different way? That itself started from the top down, and that started the infrastructure of psychological safety, allowing people to then want to carry that forward.
Lehua Stonebraker: [5:26] So now, speaking from the people and HR team that I lead, we're using that same concept to say, if you could rewrite your job, what would be the work that you find either uninteresting or cumbersome or frustrating, because there's bottlenecks or you're waiting on something else? We're starting to crowdsource and do some experiments of our own.
Lehua Stonebraker: [5:50] When I think about the blockers of AI within the HR world that I live in, a lot of what we do is react to the business. You can have foresight in terms of thinking about workforce planning or flight risks and all of the rest of it, but the reality of the day comes, the business changes, all of a sudden we have to respond in a moment and then we're running out of time. So it's about being able to carve out blocks to do some of that more creative thinking. Right now I've got a leader on my team who is actually going to reserve a full eight-hour day over the next few weeks. We've come up with a couple of hypotheses of things that she could do. For instance, we're looking at moving into SAP through our acquisition, and they have a very different way that they look at compensation, job architecture, title levels and so on. Rather than having to go and look up all of these independent pieces of information as we think about bridging from one world to the next, what if we could create agents that could go and do that for us? There's consistency, there's scale, there's reliability. And what would that then do? What capacity does that give us back to do something different and unique around the business? So we're testing it. We're going to see the effectiveness, we're going to see if we've got the right tools, and then we're going to start crowdsourcing not only around HR, but around the business, and see how we can apply some impact elsewhere.
Matt Alder: [7:14] And you said that comes down from a leadership level. What does that look like practically? Are you assessing the leaders in how they're using AI and how they're thinking about things?
Lehua Stonebraker: [7:23] Not so much in terms of looking at goals and having specific outcomes. If I go back to the traditional ways of measuring SaaS, you're looking at consumption or widget-based measures. We're not necessarily looking at that scale. But a few weeks ago, the executive leadership team got together for a two-day off-site. A lot of what we do is talk about the biggest problems, how we collaborate in solution, and what our strategy is going forward. But we actually spent 50% of our time, one full day, where we just did AI design, like a masterclass. We applied a lot of these principles to ourselves. Talking about top down, we can't expect any sort of excitement or desire to change and to lean into the moment if we're not practising that and embodying those qualities. Right now we're taking a lot of the things that we did at that session and carrying them forward in terms of initiatives that we're going to see across the entire business. So we're really excited about where we're at.
Matt Alder: [8:25] So you're going through this integration at the moment, and I'm presuming a lot of the work is around how teams are structured and designed. We're at a point where AI is actually changing the way the work gets done. What does that do to the way you think about organisational design?
Lehua Stonebraker: [8:45] It's such a good question, and it's hard, because I go from us being the decision makers to now being in a bigger organisation where we have influence and we have credibility, but at the end of the day, we're part of a larger organisation that may have a very specific way of doing things that we're trying to learn. In my personal point of view, I think the org chart is actually gone. When you think about org design, you really need to think about what are the outcomes? What's the work that you need to actually produce? Then you're not necessarily confining people to a specific job title or day-to-day responsibilities, because those could ebb and flow and change. We just haven't necessarily gotten to that inflection point. But I am excited about SAP and having access to this autonomous, large ecosystem where data can come in from everywhere and really help you inform and accelerate a lot of those decisions.
Matt Alder: [9:38] If organisations are designed like that, what's the impact on people, particularly people who have grown up in a structured environment where org charts are the norm and they know their responsibilities? Or has work just changed anyway, and is that an outdated way of describing it?
Lehua Stonebraker: [9:55] I think the work has changed. It's going to be a continuum on where people are at in that journey, particularly if you think about the industry sector that they're coming from. But in particular, I do think there's an opportunity to invite people into that conversation. These are not necessarily decisions that get made and pushed down, and all of a sudden people are just saying, my job is different. It's about inviting them in to say, if you could design something different, if you could remove something that you are basically blocked on today, what would that look like? That's where we're starting to have more of that conversation across the business.
Matt Alder: [10:31] I want to talk a little bit more about skills, because you mentioned earlier in the conversation the type of skills that are bubbling to the surface that people need in this AI world. Tell us a little bit more about that.
Lehua Stonebraker: [10:43] Soft skills are always going to be important. I mentioned a few of them in terms of being agile, having that learning mindset, being open-minded to things that you just don't even understand, and the desire and curiosity to go out and seek, to learn more and to practise. Those soft skills will always be there. But the other one is just around AI. We talk about not wanting to create bias, and it's not meant to be the decision maker. It's meant to influence, or to help you succinctly get to what a root cause is or what some potential solutions are, and then let's have a conversation in terms of how we're going to execute against it. So it's the softer skills around the complexity of work, the decisions that need to happen, the judgment piece, the human elements. Which is why I don't envision AI completely replacing our jobs, because we need all of those across the world.
Matt Alder: [11:32] To talk a little bit more about the integration, obviously that's going to come with a set of challenges when you're integrating processes and people and cultures. What has that bubbled up in terms of the challenges you've had to deal with, or you're dealing with?
Lehua Stonebraker: [11:45] We talk about AI as if it's this thing, but at the end of the day, it's not owned by one person or team. It is the culture of the organisation. So I think there is intentionality around how you talk about it. Going back to your earlier comment about waking up every day and hearing all these things about job loss or tracking, name the fear. We know that these are things that you probably have on your mind, and we may not have all the answers. So name the fear, name what the purpose is, what outcomes are you trying to drive for. There may be organisations that want to drive efficiency, and then what do you do with all that extra work with fewer people? Those are conversations that you have to have. Naming the fear, being transparent, speaking frequently. Over-communication is really important for us.
Lehua Stonebraker: [12:30] We actually just concluded, we do an engagement survey two times a year. We announced our acquisition September 11th, we'll always remember that day, and we then did our first engagement survey in October. Shockingly, in headwinds of change when something like that happens, our engagement scores went up. And then in April, we just saw another increase in our engagement. Globally, you start to see engagement go down, and for us, I think it has been because of those intentional choices to allow for psychological safety. For people to say, I don't like this, or I feel uncomfortable with this decision, or I'm scared, and how do you help me work through those things? It's not to say that you can appease or come up with an answer that's going to help everybody, but being able to name it and walk them through that moment together, I think, is really important.
Matt Alder: [13:25] And what does SmartRecruiters bring to SAP culturally? What's different? What's the add there?
Lehua Stonebraker: [13:30] It is interesting, because our stated corporate goal is that we're going to be the innovative growth engine for SuccessFactors within SAP. What that means for us, when you think about startup organisations and the very generic descriptors of bullish and disruptive and fast paced, I think all those things can still be true in a very large organisation. So it's a new way of working. It's a new way of bringing focus. One of the things that we've actually seen implemented within SuccessFactors is an OKR framework, where you have a very small number of corporate goals. Everybody knows what those are. Those then drive your prioritisation and your decision-making. If something is not linked to those, then that makes it very clear that it's either no or not yet. We've introduced that, and I think that has propelled a culture shift and a culture change.
Lehua Stonebraker: [14:24] We do see a lot of shared DNA across our values, which is a great foundation to start from. But it's about being able to bring that energy, that speed. I will say in larger organisations you tend to see a lot lower risk appetite. I'm not saying that we are just throwing all caution to the wind, but there is a level of appetite for us to say, let's just try it. We can pull back quickly, but let's just not be afraid to hold ourselves tethered to old rules or old ways of working.
Matt Alder: [14:57] Obviously, this is leading to a situation where you're able to offer full visibility on the employee lifecycle, from when people are hired to when people leave, with all the data across that and AI powering it all the way through. What does that mean for people professionals? What does that mean for talent strategy? What does it enable that isn't possible now?
Lehua Stonebraker: [15:18] This is something I'm the most excited about. I'm not necessarily the owner of this idea, and it's nothing that's come to fruition yet, but I do think that the possibility is the greatest with SmartRecruiters joining SAP. It's this idea of almost having this employee blueprint. You think about it, I submit an application, so here's some information about me and my experience and what I'm interested in. You go through this journey of being interviewed, and then you get hired. You get hired for a very specific job, and we talked about how the org chart or the job itself may change, so obviously take that with a grain of salt in terms of what it evolves to. But you get hired to do something, to perform some outcomes.
Lehua Stonebraker: [15:54] Then from there, your first 60, 90 days, you're learning. You're trying to absorb as much information, understand the company's vernacular. But at the same time, how do we build an onboarding plan with you in mind? So it's not a rinse and repeat. There may be a playbook for certain elements, but there are very specific skills or experiences that that person is bringing in. How do we use AI to surface those? Maybe it's, we think it's really important for you to start interacting or building a relationship with these people or these pockets of teams. Maybe it's these systems that we think are really important for you to get your work done.
Lehua Stonebraker: [16:33] From there, now you're ramped up. All of a sudden you're performing, you're getting those continuous conversations with your leader on how things are going. Maybe there's a continuous listening moment where we can take whatever that performance cycle may be, annual or quarterly, and AI can then leverage it. You talked about this being a very tactical goal, how did you produce against it? Here's something more strategic, or a learning and development plan that we have, and then surfacing and tracking how that person performs against it. Mobility. The possibilities, I think, are endless if we're able to use this open concept around data. How do we then leverage that to make the employee experience not only incredibly personal, but also maximise the output of their experience as well?
Matt Alder: [17:18] I just think that's so powerful, because it's always a ridiculous situation that someone goes through a recruitment process and you find out all this information about them that then just gets lost within their role description, and we don't really know what they do. It's just such a powerful thing for organisations, isn't it?
Lehua Stonebraker: [17:36] You think about the employee life cycle as these buckets. You've got recruiting and you've got onboarding and you've got benefits and pay, and it's almost like the journey for them just stops at each moment, rather than having that continuous flow. It's not even a cycle. It's all connected, all the time. That's where the power really lies.
Matt Alder: [17:57] What are the implications of all of this, though? Because this is going to affect the way people think about talent, the way people hire, the way people develop people. What does that look like in terms of rethinking the way that talent is thought about?
Lehua Stonebraker: [18:14] This is where people's fear comes in, because we don't know. But how exciting a moment to be able to be the architect of that future. I don't have the answer. I don't know what that's going to look like. But the possibility, as I described, in terms of thinking about new ways of work, or breaking down the traditional constructs of what we think we've always been expected to do, what sort of possibility is that for us? The curiosity piece is what really has me the most excited.
Matt Alder: [18:48] Curiosity is really interesting, because you can develop curiosity, can't you, as an attribute, as a skill?
Lehua Stonebraker: [18:53] Absolutely. And I think it's something that you actually have to have. We're talking about screening for talent or making sure that they're the right fit for your organisation. It's about building that in as a litmus test. Curiosity, the fluency, the desire to go and take on some new skills and to apply something in a new way.
Matt Alder: [19:15] It's just so hard as well, because there is so much uncertainty, and things change very quickly. That must have an impact on the way that people think and behave as well.
Lehua Stonebraker: [19:24] It does. We have definitely seen, I would say, both an openness and then also a resistance, but those are things that you expect to have happen. They want to see, well, what happens if? Those are some of the conversations I've actually had with the SAP colleagues that I'm working with. They're kind of, what happens if you do this? And then maybe if it's successful, then we'll follow. Why don't we just go and take that first step?
Matt Alder: [19:49] Yeah, it makes a lot of sense. As a final question to really pull this together, what does good leadership look like in an AI-driven world?
Lehua Stonebraker: [19:59] Good leadership. We talked a little bit about this earlier in terms of the fundamentals that are really important. So psychological safety, naming the fear, helping somebody understand how they can be a part of the solution in addressing the fear. Good leaders have to lead by example, so it's not the do as I say, not as I do. Leaders also have to understand exactly what they're striving for, so starting with the outcomes in mind versus this is the expectation. And also just challenging. If there is a desire to look at AI as only efficiency, or only for compliance and surveillance, challenge why, and what is the reason for that?
Matt Alder: [20:48] Lehua, thank you very much for talking to me.
Lehua Stonebraker: [20:50] Nice to see you. Thanks, Matt.
Matt Alder: [20:52] That was Lehua Stonebraker on fear, safety, and the end of the org chart. Next time, we follow the money. So if you've ever struggled to get AI investments signed off, the next episode is for you. Tom DiDesidero is SmartRecruiters' CFO, and he explains exactly what he wants to see in a business case, why the old rules of measuring ROI no longer apply, and shares some numbers about the real economics of AI that genuinely surprised me. Subscribe or follow wherever you listen to your podcasts, and I'll see you in episode three.
