One List Every Head of People Needs Before Their CEO Says to Use AI with Ben Langer, Global HR Executive

Speaker A: Foreign.

Speaker B: Welcome to the foundation series. Your deep dive into startup compensation with industry leaders from across the startup world. Join ME Matt M. McFarlane, a people operations leader turned compensation specialist, as we uncover the strategies and practices driving success in tech startups around the world. Hear insights from heads of people, founders and experts as we explore how to build robust compensation frameworks that not only

Speaker C: fuel growth and retention, but do so

Speaker B: in the dynam startup environment that we all know and love.

Speaker C: Let's get into it. Welcome. In today's episode, I'm joined by Ben Langer, a global HR executive focused on the work behind the work. We're talking AI in hr, where it genuinely helps, where it's being used as a crotch, and the human moments that should never be automated. Let's get into it. Ben, welcome to the foundation series. Uh, I'm excited to have you here, mate. It's, um, it's been a long time coming, um, but we've got a few, a few topics that I'm excited to explore with you. But welcome, uh, to the show and thank you for being here.

Speaker A: I'm very excited to be here. Thanks for having me. I've been looking forward to our conversation for a minute, so I'm happy the day is finally here.

Speaker C: Amazing.

Speaker A: Ben.

Speaker C: I'm going to jump right into it. Um, I think a topic that is just continues to dominate just about everyone's agenda is, of course, AI. Um, I don't know about you. I feel like I wake up every day and there's some new tool that has been launched and I immediately feel like I'm back to square one. One of the things that I've loved, um, as I've followed you and I've followed your journey, has been around this kind of theme of, yes, AI is great. Yes, it's going to help transform our roles in many ways. Um, but there's also a really large component of the role that is unautomatable potentially or certainly, you know, needs to maintain its, its humanity. I'm really keen to understand off the top, like, what does today look like in terms of how AI shows up for you? Um, and similarly, where are you kind of seeing people lean on it maybe a little bit too much?

Speaker A: Yes, the world of AI and HR is ever evolving and to that point feels like every day there's, there's something new and revolutionary coming out, like, oh,

Speaker C: my gosh, I have to try this,

Speaker A: I have to try that. But when I, when I try to boil that all down and having the HR function myself, the people around me the people that I interact with, not losing themselves to AI, um, is kind of a critical piece that I speak about passion, um, but there's a lot of like, real practical use cases that make the lives of HR professionals better. A fantastic time to be alive in the HR space. Um, right now, today, um, with all of these advancements. And so when I try to think about AI and how I'm applying it and how people around me are applying it, it's speed, insight that comes like first, uh, first to mine. There's, there's always been so much data in hr and I think when I originally got into HR and where I'm at today, that really hasn't changed. Like, there's always been a lot of data. Um, before it was on paper and in filing cabinets and there was like a bunch of different ways we tried to like maintain the data set. And now it's far more digital, um, and we have probably even more data than, you know, 10, 20 years ago, um, at our fingertips. And now to be able to interpret that data, ingest it, and then be able to provide that back to our businesses is way easier than it's ever been. And so that's exciting for me in the position that I am in the HR space in general, that speed to insight, um, is incredibly useful and AI does it extremely well. Um, I think there's particular use cases like speed to insight is a pretty large kind of concept, I guess. Um, but I think about like um, drafting policies or just data analysis in general. Um, I think comp benchmarking is a, there's a lot of use case for, for that data, job descriptions we hear, I mean, that's not, there's, these things aren't revolutionary and I'm not like, you know, saying anything new to anybody that's listening. But these things, if you're not using AI, you have far more ability to uh, uh, speed to insight in these things and be able to provide faster, probably more accurate decisions for our decision makers and businesses moving forward.

Speaker C: Yeah, I hear what you're saying. And it's funny if I reflect on even just a couple of years ago, one of the key skills I would have suggested are important for HR professionals as they inevitably progress in their career, was that learn how to use Excel, have some kind of analytical capabilities. And I still think that's the case. Or maybe really AI has just kind of made that more accessible in the sense that now you can, you can point AI at like a whole bunch of people data. Uh, and like you said, we have so Much of it, um, and it can make sense of it really quickly. It can kind of surf as insights. I do still think there's this kind of risk, um, and I think this probably speaks to some of the reluctance maybe of HR teams to get their hands dirty with AI. Is that, can you actually fact check it? Can you go in and make sense that it is giving you accurate insights and things like that? But I otherwise agree with you that it's like, it's kind of made that ability to go, okay, well, rather than be heads down in a spreadsheet all day just to try and answer this question, I can now go, you know, cliffety clack on the keyboard. And then possibly several minutes later, I've got, I've got, you know, a story that I can tell about what's happening in the people space. And I think I agree with you that it's going to just augment our ability to be decision makers much more, rather than the people that help, you know, surface the insights that maybe ourselves or others can make them on. So, like, more better quality decisions. Is that what you're saying?

Speaker A: Yeah, 100%. Um, on the opposite side of that, I think you and I will agree that especially in the HR space, you cannot. I think you actually framed this in your question about not using the, you know, not using AI as a crutch, or where have I seen people use it as a crutch? If you, if you completely rely on the tool and stop thinking critically about the data that you're trying to move quickly, analyze differently, um, if you take the human out of that and you just prompt, prompt, prompt, prompt, prompt, there's a different level of thought and critical thinking that goes into prompting and making sure that you're doing it in, you know, the best way possible. But if you're completely outsourcing your thought process and just trust that the AI, whatever, whatever tool, um, you or your company is using, um, I think that is, that is very risky. And I think that's where you were kind of leading. It is incredibly risky to put complete, 100% complete, like, trust in the tool. Just because it's fast and gives you an answer every single time doesn't mean it's the right answer. You still need to, like, critically think about the output that it's giving you. Um, and don't let your human judgment just be like, nixed by something. That's cool. You saw something on LinkedIn, you saw something on X, you know, what have you. Um, you still need to have that human insight into the data probably now more than ever, like, because of how quick and easy this stuff is. Like, you still need to have that. And that's what I like to talk about. That's what I like to, like, chew on a little bit. Like, you still need the human behind the prompt to be able to critically

Speaker C: think afterwards to make sure that what's

Speaker A: being put out is actual, like, good. Um, because it's all great outputs.

Speaker C: I've definitely come across, you know, I think we've all kind of come. Come up with some sort of, like, trashy answers when it comes to AI. I know. As you were speaking then, I was just thinking about, like, what are, what are some of the ways practically that I try to make sure that the way AI is being used is like, not kind of circumventing that, um, that process or that chain of thought that, that I would have liked it to follow. I know, and I'm curious to, to hear if, if some of these resonate or if you're using different approaches. I know one of the most common ones, in fact, that I use is actually asking AI to give me the plan before it does something, and so saying, hey, tell me how you're going to tackle this. You know, here's the problems that I have. Tell me how you're going to tackle it before we actually get to doing it. Um, and the other thing that I'm doing and this, to be honest, this one's probably the hardest. Um, for a couple of reasons. I try to, um, watch it, you know, when it's thinking and it's kind of like articulating what it's doing. I have a really hard time as someone who probably has adhd. I'm not, I haven't been diagnosed, but I like sitting there and, and reading how its thought process is going, rather than just going, okay, that task is handled, I'm going to go over to a different task and let that one happen in the background. I really have tried to force myself to read how it goes through that thought process to try and catch if it's doing, you know, misinterpreted something or whatever it might be. Um, and sometimes I'll even expand that section kind of after it's, it's finished. The prompt, because it can go quite quickly, can be hard to read sometimes. Um, but I'm curious, are there, you know, are those things you're seeing, uh, in the team, are there others? Like, what are the ways that you're, you're seeing, uh, yourselves, Kind of like check the AI and Make sure that it's, it's working effectively.

Speaker A: Yeah, exactly. To your original point here. If, if you are using AI and just trusting that your simple prompt of, can you review this and provide me an output? Um, and that's as, that's as in depth as you get with your prompt. You're not going to, you're not going to get the output that you're looking for in most cases. Sometimes you might, um, but I think on the front end of that and training, you know, the individuals that I work with and others, um, that are, that are connected to this space as well, like taking a step back before you get into like the simplest simplistic prompt. So what am I, what am I trying to get to? What is the end goal of what I'm trying to achieve? And maybe you don't know how to get there yet. And that's where your prompt should start. Like, this is what I'm trying to do. This is what I've done so far. These are my thoughts. But I want to, I want to interact with you and ask me some questions. And so that's, that's where I've seen m. The front end of prompting really shine is have it be an interactive process versus you, the human trying to like frame the output on the back end, like interact with it first, frame the prompt then. And then in that process you'll get a far better output because it's not just a, like a standalone single point. This, the back and forth, um, conversation on the front end of it. There's so many times, I'm sure you've seen this too, where it's like, if you, if you take that approach versus just like, give me the, give me the end. And if you have this like back and forth on the front end, you get far better outputs on the, on the back end of those interactions than against like standalone single point prompts.

Speaker C: Yeah, yeah, I hear you. It's a good call because it's. You're right that there's. And I'm, I can definitely. It resonates is the sense that like, there's sometimes where I'm prompting where I'm really clear about what I want and I can just have like one, you know, behemoth prompt that I'm like, I can go through and I can read it and I'm like, yep, this is, you know, this is giving all of the guidelines that I wanted to follow and this is the output and it's framed really well. But you're right that there's times where I'm like, I kind of think I know what I'm trying to do. I put it to someone the other day about when it comes to content writing and I was like, sometimes I write the article I think I'm, I want to write or that I think, you know, I'm trying to talk about and I get to the end of it and I'm like, I, uh, don't. I don't really know what I'm saying here. And that's actually where I found it can be a really great like sparring partner is just helping it clarify your thoughts and. But I see to your point, it's like, you know, being able to try and start describing what you want and then getting it to ask you questions and then helping refine that to a point where actually you can articulate it really clearly. That's a. Yeah, it's a great way of. A great way of using it.

Speaker A: Yes.

Speaker C: Um, I'm curious what, uh, like what are some ways outside of prompting that again, either internally or kind of case studies that you've seen, um, where people, teams are really capitalizing on this not from, not from necessarily a prompting perspective, but from either an automation or an agent or something like that. Is it something that's be used um, really heavily internally or is it still something that, I mean, everyone's on the journey, but do you feel like it's, you know, you're at a, you know, sort of more mature stage?

Speaker A: There's two sides of this. So I use AI heavily on both sides of this, but very differently based off of where I'm interacting. So internally for the organization that I currently work for, we use a very particular set of AI tools that are in a trusted environment that our business has deployed to us as employees. Um, and so I think in my day job, um, it is much more controlled. There is a lot of trust, um, from our organization in the tools that we have. Um, but it is far different for me, um, when I think about this personally and on that side, the personal side, I've found the use cases that I'm using like most often right now, like daily. I'm, um, not sure how familiar you are with Claude, but Claude, over the last 30, 60 days has, has changed a lot of lives in the HR space. I think I see it everywhere. Um, and for anybody listening, if you haven't done some discovery on Claude and Anthropic, I highly recommend just, just understanding what they're doing, especially in the HR space. But there's like in general, um, and from A, from a personal perspective and like being on social media and LinkedIn and writing and like being uh, a thought partner with some, um, some things outside of work that those use cases are incredible. Like what, what Claude is able to do today, that it, that at least I didn't know about like 30 days prior, um, has made my life so much more easy. Um, I'm able to, I'm able to like 10x my output just based off of knowing how the tool works and like using it to its potential. Um, um. And so the, this journey that I'm on, like from a personal perspective using Cloud has been just super, super eye opening. Um, and I'm not sure if you've used cloud. I'm sure, I'm sure you have, man.

Speaker C: I'm deep down the quad, uh, rabbit hole, that's for sure.

Speaker A: So you know what I'm talking about then.

Speaker C: Yeah, yeah, yeah. I was going to say to you, it's, um. And this is one of the things I'm kind of envious of my position in the sense that, you know, I'm a solopreneur, I can kind of, I can buy a tool on a whim, I can use whatever I like. I think my experience in a professional sense very much maps what is more like the personal experience I would say most others have. And certainly you described, um, how do you think? Well, actually, I guess like one of the, one of the challenges that I see and I'm keen to like put me to the bones of this is like, how do you juggle this, like incessant pace of AI, like you said, the last 30, 60, 90 days, uh, for a tool like Claude, but certainly many tools, it just is increasing exponentially and it's like, how are you seeing companies or people, teams or organizations in general, kind of grapple with the pace of change whilst also balancing the need to make sure these tools aren't going to hand over the keys to the kingdom in a security sense. How are you seeing those two things? Be. Yeah, be, be, be kind of married

Speaker A: for me, I think anything that requires, um, Actually no, that's not where I was going. Regardless, if you're going to be using this for personal circumstances or if you're using it at a business, I think making a list, a simple list of where the human interaction with your employee base, or again, whatever you're doing from a personal perspective is required. And if you don't have that list, I highly encourage you to jot that down, have kind of a roundtable with your network, your team your business and say, where are we not willing to bend? Um, where we think that you have human in this particular workflow process circumstance. If you don't know what those are, it's incredibly important to know, um, and go through that exercise. And I think if you have that, it's honestly that's, that's the first step of setting a boundary as it relates to AI. Ah, because I think there's a lot of, you know, individuals in the C suite and they hear AI and they want to move fast, they want to use AI and they kind of want to just like move with it because it's everywhere and everybody's talking about it. But if you don't know where the use cases are most practical inside of your organization or what you're trying to achieve, it's very, very easy to just like remove all human aspects through those processes. So coming up with a list on where you're not willing to bend is one of the things that I've encouraged others and for. I have kind of made a stance internally for me and my team. Where can we automate? Because it's, it's here, it's, it's right now and it will not go away. Um, so how can we automate things that are transactional, Low, low human value? Um, and then where, where we can't, where are we unwilling to bend? Having conversations and making sure that those around us understand what those are. Um, so using AI to move faster, but not necessarily just to move faster, we're not willing to remove our fingerprints from the situations that require a human interaction or a human moment. Um, and so that's one of those things I'm always kind of battling with, like, where can I elevate my team, the people around me, into moments that matter. Here somebody wants a human, and if they don't want a human, transactional questions benefit related things. How can I make sure that we are using AI? And that's where I've kind of went back and forth in this battle of pushing to use, but not pushing it on everything because it's not valuable in every single circumstance. Um, and if you know what your boundaries are, it's far easier to stick to your guns and make sure that you and your business are kind of operating under the same mentality.

Speaker C: Yeah, I love these. So I'm keen to stick with the list for a second. But then I want to talk to you about AI adoption. So, you know, for other practitioners, uh, for people, professionals that are listening to this, I hear more and more that, you know, Roles like these are the ones that are kind of whether formally or informally being charged with AI adoption, with AI transformation, things like that. So I'm keen, talk me through like from the start to finish, like what does it look like in terms of how you start to have the conversation with the business around this kind of, this list of, you know, things we're not prepared to use it for versus r in terms of navigating how to actually integrate it into the business.

Speaker A: I think it's going to, it's going to depend on where you are at from a business perspective in your journey with adoption. But I think the safest bet for those listening is internally with your HR team, come together and talk about the things that you know as an HR professional are far more advantageous to be a part of as a human versus automating, um, through AI or a particular tool. And so internally with your HR team first having that conversation and basically taking a swing at kind of rough draft number one on these are the things that you know as HR professionals are going to, are going to land better with a human interacting in these circumstances. And then I think from that stage where you feel really good about the list that you have, um, where you have set kind of your boundary as a team is then where you go and kind of cherry pick if you will self select some of the early adopters on the AI train inside of your organization and kind of present the idea of wanting to automate but wanting to ensure that as a business and as we continue to go down the path of utilization in, you know, AI tools that these are situations that we don't want to remove ourselves from. So I think from a starting point internally with your HR team and then and deploying that thought process and that list with your business stakeholders that are on the, on the train of AI adoption is going to be kind of a two prong approach. And I, and I think uh, good way to at least get on the path of creating that list. And then again as, as that list gets developed and based off of what organization you find yourself in, you'll then be able to kind of navigate, you know, how you apply automation, how you apply the use of AI and where you level up, uh, the individuals on the team to make sure that they're not being removed from conversations that need to be happening. And there's like, if we want to get like super specific, we can talk about those things. I don't know if that's where you want to go Matt, but there are very like real things that happen in the lives of employees at organizations all day. Um, that just shouldn't be. And nobody wants to talk to a computer about, you know, very real things that have been in the lives our employees. So um, there's that whole side of it too where it's like there's, there's like practical, real situations but like holistically, if you're just looking at trying to make that list, um, that's, that's the approach I would take for those on this journey.

Speaker C: That definitely hits in the sense that like, you know, thinking back to the kind of first piece that we talked about around where AI is being used internally, it's like you know, having it surface these insights is really great. But you know, one of the things certainly that I'm increasingly hearing from organizations is that it's like that the AI shouldn't be making a decision based on the data, that it's just surface.

Speaker B: Right.

Speaker C: Like ultimately we need to be the decision makers. We're the ones that are accountable for our respective areas of the organization. So that for me is like one clear area where you know, but I guess you have to define a threshold, right? Where maybe within an onboarding flow actually it could. So yeah, I mean I'd love to spend just a couple of minutes going, you know, just that level deeper for uh, people to understand. Like, you know, what, what does a, what does a dialogue with a, uh, department head or something look like in that sense when you're helping them to map out what AI would or wouldn't be used for in the context of their work? Startup People Summit is back for 2026 and we're bringing together the sharpest minds from people professionals across the ap. This year's event will be showcasing all the ways that fast growing companies are doing things like AI powered people ops, driving high performance cultures and building modern people practices. This year's event is focused on giving you the content and the connection to become the most effective people professional around.

Speaker A: Hope uh, to see you there.

Speaker C: Link in the show notes.

Speaker A: There's a couple situations that come to my head instantly where I don't think there is ever a future state in a human LED world where somebody who is going through a performance like maybe let's start like simple and then if we look, let's get a little bit more like sensitive topic. So performance, um, almost every organization has some level of framework around what performance management is. There's a lot of automation that can happen on the front end of like data analysis around performance management. And I think the concept of like transactional hr, we can get a lot of the data transactionally through AI and do different automation that gives us the data set to then go and have conversation. And so on the front end of performance management, I think that's a brilliant use case to use technology to feed you the data. When you are telling somebody they're not doing well at work as a result of data that's being fed to you. I don't think there's a world that that individual wants to hear from an AI tool that they're not meeting their expectations. They want to hear from their direct manager. They want to hear from the HR team. They want to hear from a human that's interpreted the data and give them insight and like practical insights on what to do next to succeed in the role. I would argue there's not an. I hope I'm making like a definitive statement here for I don't think there's any organization out there that hires people to fire people. Like that's not a thing. And so if you're using like that mentality, performance management, there's, there's thought process to help this person achieve what you hired them originally for. They may have deviated from the path. They don't have the tools necessary to meet those expectations. But not having a conversation with that person in that moment when something's going wrong again, I don't think ever gets automated from it from a tool like that just doesn't seem real to me. So that's like one, one piece for me. The second, I think are the more personal circumstances that happen at work that are just a reality for HR teams all over the world. M. Uh, individuals go through very real things outside of work, um, that require conversation because it may be taking away their ability to be, uh, at work. Um, so there are very real circumstances going on outside of work. And I'll use the example of somebody going through a miscarriage. I don't think there is a world where a mother comes to HR or they interact with a chatbot. Uh, and that's good enough. Like in that, in that particular situation, I don't think that world exists anywhere down the future road of AI. I think in that moment that particular individual wants to have a conversation about what their options are from a time away from work perspective, what benefits they have available to them to work through the circumstances that they have. And so those very real personal circumstances, that's just one use case, but there's 10 other ones that we could talk about right now. Um, those don't Ever get automated. Those aren't computers interacting with humans to help you those tragic moments in their lives. That's human with human. Um, and those are the use cases where I think you can argue all day long on transactional HR, um, being augmented by AI. And I, I 100% agree with it. I, I don't think that's a threat at all. Think about this holistically. I really think that's actually a gift for HR teams because it then allows us to, to put, um, ourselves in the moments that are actually very important for the humans that we serve and that we are working with in our organizations. And so I don't, I don't see this holistically as a threat. It's very, very much a gift, um, for us in the HR space to be able to be in those moments with the people when they need us, when they want us, when they depend on us to be there and not just, you know, opening some chatbot. And what are my, what are my benefit options here? What can I do? Like, those are human moments that require thought, empathy, conversation. Like a moment that is deserving of a conversation and not with this automated process workflow.

Speaker C: Yeah, I hear what you're saying and I get the sense that, you know, those are the parts of the role that will probably be amplified through AI adoption is that actually it takes away a lot of the, like, how do we get to the answer for this thing? And actually again puts us at the, at the sort of front line of being able to have these conversations and engage with people and make it more human. I actually like explicitly remember back, um, it might have even been just before AI. I remember being at this conference with like a futurist, which I think is just like probably the most fun job in the world. Um, but they were talking about this like, this concept of like automation and robotics and things like that and um, about it from a medical sense. And they were like, it's not going to do away with the role of, for example, a doctor or a nurse or something like that. Like AI, I'm sure will get to a point where its diagnostic ability is exceptional. And it's probably, you know, because it can obviously retain more information than any one person could as a doctor or a nurse or whatever. But what it actually does is it changes the role of that person from maybe being ah, a diagnostic or whatever process. Um, and actually fun fact, they did some research on this and people are more comfortable sharing, uh, openly all of their symptoms with a robot, uh, or with something that can't judge them basically, uh, was the sentiment. So this is an interesting overlay. Um, on the piece that you mentioned. It's like, how do you balance that? Actually, I would be more forthcoming on symptoms or issues that I'm facing or something with a robot than I would be with a human. But then when it comes to the care component and the actual, like, treatment and things like that, that's the part that actually needs to be human because we don't want to be cared. We don't want to be, you know, jammed in the arm by a robot or like patted on the head like good human or anything like that. Right. So that's, that's the part that, you know, and I'm being a. Being a bit facetious, but it's like that is a part that I think we, we can play within our organizations. Um, but I'm curious, like on that, on that vein, like, what are the, no pun intended, what are the ways you see the role augmenting further with AI, with some of these kind of more human components versus the automation and things like that?

Speaker A: So are you asking where I think more automation is going to benefit AI or hr? Yeah, I guess.

Speaker C: How do you see the role changing when we can, from an operations perspective, we can now do so much more. And I mean, my background is much more people operations than I think it is. That kind of hrbp, like that kind of human side of things. Um, not to say that it wasn't always a part of my role, but I think that is like, that can do so much more. It can be so much capable. And I think I see it enabling the HR role to be more engaging with the workforce and with leaders and things like that. How else do you see it being changed?

Speaker A: I think it gives us an ability to. I think for the longest time it's HR teams talked about people, um, and people data. And for good reason. Your function is to know the people and the data and provide those insights. But I think if that's where you've landed in your HR journey and haven't opened your eyes to what is now possible, not not only having that information, but now how do you take that information and how do you change business outcomes and not just report on people data, and that's what I'm super excited about. I think that's the next evolution of the HR function. I don't think it's asking for a seat at the table anymore. I think it's building the dang seat. I think. I think if you know how to change Business outcomes with the information and tools that we now have available to us. There shouldn't be an HR team out there that doesn't have some level of access to what Matt and I are talking about here. Uh, if you're only siloed in the world of HR and don't know how your business actually operates or moves forward, I think you're doing the function of hr, um, injustice and I think connecting the dots between all of the people data that we've had for years and years and years and thousands and thousands of data points. Our HR teams should know how our businesses work and how do we, how do we connect the dots of HR data with business outcomes and marry those two things together to be able to, to act as a business operator versus um, just an HR practitioner. And that's, that's like the next phase, um, that I'm super excited about and like, and helping drive at my organization connecting the dots of all of these pieces into business outcomes. Stop to stop thinking just about people data, people strategy. How are we thinking about our business strategy around these other data points? Um, and with the advancement that we've now found ourselves in, in the last 5ish years, those are very real possibilities for anybody willing to learn new skills, um, not be afraid of AI and know that it's here, it's happening away and kind of like leaning into it. Um, and that's, and that's where I see kind of next steps for HR teams. Like, we're not, I'm not just going to be talking about HR anymore. We're going to be talking about it in the context of solving business problems and business solutions because it's now possible in a much different way than it was before.

Speaker C: I couldn't agree more. Hey, like, I am so bullish on people teams these days. Like we have such an amazing, uh, opportunity in front of us now and I think the role has, the, the profession has got, undergone such a, like a profound change in the last five years. Like it genuinely has gone from being this kind of like, oh, uh, you know, HRs here, compliance, hiring, firing, that sort of thing into like genuine fundamental impact on the business. And I think, you know, we're increasingly being handed the keys to tools like AI and being asked to lead its adoption, which I'll talk about in a second. But it's like the impact we can have. Like again, I was, I was reflecting on this with a colleague the other day about how just three years ago, and so the last role that I was in house for, we Built an app using like a low code or no code sort of tool. This was before AI. Um, and we were, I was so, like, smitten with it. I was just like, oh, my God, we've built an AI, like an app. It's so incredible. Like, I've never really done this before. And the response from the business was so, like, positive. And they're like, this is incredible. Like, thank you so much. And, um, and now you can, you can. I mean, and obviously, you know, you want to be doing things that the business cares about, but you can do this stuff on a dime now. Like, it takes minutes or hours. Um, it costs nothing. Like, the, the opportunity is, is so profound. So, yeah, I'm, I'm with you. I think, like, this is an exciting time. This is cool stuff happening in our space. By all means. I think people should be more excited.

Speaker A: I think, like, like, one step further in this thought is to know our people data, uh, and, um, be able to do this next step that we're talking about. So, like, retention, isn't this just like, feel good metric that HR people should know? It is. It is a cost metric that your CFO should know about in your C suite about. There is a cost associated with retention. It's very easy now to connect those dots, um, with these types of tools. Um, you think from like a, like a recruiting perspective, time to fill isn't just like a recruiting metric. Um, it's also revenue impact. Um, and if, if you don't connect those dots, that. And that's what I'm talking about. And like, these. We have our people data. How do we connect those to our business results? And those are like two good examples in my mind where it's like, we have this people data. How am I, how am I giving it in a new way? And I guess, like, this isn't like, revolutionary like these metrics and, and associating them with cost or revenue. Isn't this, like, grandiose. Oh, my gosh, Ben just like, landed the plane fine. Gosh, he did it. Like, that's not what I'm saying. We, we can get these things far faster, um, with very little, like you said, like, in minutes, not months, orders like these, these, um, these metrics and these connectors inside of our business are like, really, really quick now. And if you're not leaning into it, then you're just losing your ability to be that business partner with your business. Um, so, yeah, I'm, I'm right there with you. Very bullish. Um, on people teams, ops teams like, leaning it very heavily.

Speaker C: Yeah, I love it.

Speaker A: It's, um.

Speaker C: Yeah, it's an exciting time. It's an exciting time, by all means. And, um. All right, so the last part of the conversation that I really want to give, like, ample time to is adoption. Because I think, again, in this exciting new future, one of the things that I continuously see HR teams grapple with is, like, this expectation that they themselves are obviously adopting AI, but they're actually enabling the adoption across the organization as well. So I'm keen to understand from your perspective, like, how is this showing up at work? Let's kind of start there and then, um, and then see where we go.

Speaker A: Adoption in general on the AI journey.

Speaker C: So I'm hearing a lot of companies, and I'm curious to hear if this is the same with you, where, you know, CEO, uh, setting the mandate, or board setting the mandate. Hey, you know, A.I. is here. Uh, we need to see it, uh, integrated more heavily into the organization. How. How are you kind of grappling with that?

Speaker A: Uh, it goes back to part of our earlier conversation. If you don't know that, like, the pros and cons of utilization on this, it's very easy to get kind of steamrolled in the conversation where your, you know, your CEO or part of your C suite comes to you and says, we need to be on AI. We need to start using AI, Please. Where. I've even seen, like, the horror stories of. I can't remember where I saw this, but, um, you know, somebody in the C suite, every single time, I think it was like there was a marketing professional and they were doing copy, and every single time they would propose it for approval, uh, their. Their leader would come back and say, well, have you run it through AI yet? And there's like this, like.

Speaker C: Like this, like, I think I was about to say in Bayes.

Speaker B: Yeah.

Speaker A: And it. It's. And if that's the. If that's like the framework that you are sitting in, um, it feels like there hasn't been a boundary set yet. We don't know where the value is or really how everybody in the business is using AI. And so the journey for everybody is going to be slightly different across the board. Um, but it is truly in my heart of hearts, I think if you haven't yet identified where you want your human interaction to be, that is step one, and then that stems multiple conversations down the line. Um, regardless of who that person is coming to you on utilization of AI, you have the framework in front of you to say, yes, I. 100% agree with that statement. Let's do it. How are we going to do it? Let me help you. I want to do that. Or if it's like augmenting something that's really, really critical for you or your team from a human component perspective, you have kind of the data set behind you because you've already taken the time to define that, to be able to say, well, let's pause, I hear you, but let's talk about it in this context. Um, but yeah, that's a very real challenge with a lot of, a lot of teams. I think I find myself in a position where the company that I work for is not shying away from AI. We have tools inside that our organization allows us to use. Um, uh, in the controlled environment, obviously there's so much critical information that businesses have. So just making sure that you're following the guidelines of your particular organization. But even from the personal circumstance that we talked about too, um, learning, taking m. You know, taking the journey myself to learn AI, even outside of work, I think that's, that's another suggestion that I have for everybody listening. Like you can argue all day long about the tool that you wish you had inside of work. Um, the tool that doesn't work the greatest because it's, you know, the one that work rolled out and it's not the one that you necessarily want. Well, that means that you can't use it at work. But there's a hundred other use cases that you can like go on this self journey, um, with and really, really improve so many, so many parts of um, what we all do in the HR space. So you don't necessarily have to just like segment yourself to what the business is doing. There is plenty of use cases outside of, you know, the, the 9 to 5, if you will, um, on this journey. So there's, there's multiple pieces here, but yeah, it's, it's a challenge. Um, but defining, defining what it looks like we're not willing to bend in having those conversations is critical for me.

Speaker C: Okay, so if I'm hearing you, it's like, it's a good place to start is really with this, this kind of like this kind of no fly list that we talked about earlier on. Right. So it's like being clear about what is not going to replace. So you know, human judgment, human experience or people experience in some of those really, um, you know, important moments. Um, and then it's about understanding. Okay, well then, you know, with that aside, what are the, one of the ways in which we do Want to adopt and kind of some of the targeted use cases there. Are you using that? So you mentioned that piece of like, encouraging people to, you know, to, to embrace some of these tools outside of the 9 to 5. Are you using that or a different mechanism for kind of identifying some of these, like, AI champions internally? Like, what's the approach when it comes to, you know, speaking to those who are kind of first movers in this space and learning how you can apply it internally?

Speaker A: It's a great question. I, I love talking about AI and just like, how I'm using it, how others are using it. So there's not a day that really goes by where this like, concept isn't being talked about in some respects. So I think because of how much of a champion I am, it's just, it's just natural that something's going to come out in conversation that then sparks those that are also on this path of like, early adoption and like, wanting to utilize these tools and then that just like, that allows those conversations to happen. Yeah, just organically. Um, um. And yeah, it just, it's, it's easy to identify, in my opinion. It's easy to identify if you're talking about it. Um, and you're willing to kind of show your use cases and, and put yourself in situations where like, hey, have you tried it this way? Or have you tried Copilot or, you know, whatever the tool is that your organization has? Um, I've challenged several people in the last week or so who have come to me with ideas and not just like pushing them off. Hey, have you put that into AI? But like, how about, how about we like, sit down together and actually work on this together and use the tool together? Like, this is how I've used it in the past. Have you used this yet? Do you understand what's capable, uh, do you know that you have access to this at work right now? And so like, not just like shoving AI down, anybody that wants to listen to Chicago AI helping them, helping them learn and understand. It's pretty daunting. Like, if I'm like self reflecting right now, if somebody's never used AI, like, if somebody came to you or me right now, Matt, and like, I've never used this. Like, I can imagine, like, oh my gosh, there is so much that one can use this for. So like, how do you take a really small piece of that so that they can chew on this very small piece and apply that? And so I've seen that to be super successful too. Like taking this person under Your wing a little bit like having like a one off, uh, 15, 30 minute conversation. Like, this is how I've used it. Like, have you seen this? Have you done this? Did you know you had that? Um, and those have gone, gone, um, gone really well. And I've seen, you know, individuals in those circumstances, you know, where I've had that conversation several months ago, or then I come up and have a conversation with them again. Um, it's like, oh my gosh, look what I built. Or like this, look what I did with this tool. It's like, this is great. Like, I didn't even know you could do this. And now like you have this, like for. What's that phenomenon with people.

Speaker C: So, yeah, I love that. So if I'm. So what I'm hearing really is like, one is kind of create a forum for people to like share some of these, you know, these best practices or the ways that you use it internally. And then hopefully that kind of sows the seeds across the organization. But the other is actually, it sounds almost like a kind of coaching approach. Right? It's like someone's coming to you with, um, something they're trying to tackle or something maybe they've delivered and you're, you're using that as an opportunity to go, hey, let me show you how, you know, we could do this faster or more effectively or something by using AI as a way to kind of give them a little bit of a grasp of how swing. I like that because it's like one of the things, one of the models I guess I'm hearing about, um, from some companies that are trying to adopt is that it's like this concept of rather than just mandating everyone, use AI and then just be like, all right, we're done. AI rollout complete. It's kind of this concept, and I've heard it phrased as raising the ceiling rather than raising the floor. So it's like, how do we create more space and incentivize and talk about and promote and champion the people that are doing incredible things in the space and make it really clear? And this all comes back to that whole, like top down, you know, leadership, right? Is that it's like, how can we make it really clear that the people that are doing these things are, uh, you know, creating success for the business, for themselves, for others, etc. And use that as a way to, um. Yeah. To be the example for everyone around them to adopt similar kinds of practices. I'm also hearing of like, companies that are kind of using an approach of like more like I guess, tiger teams, like dedicated like individuals or small teams that are looking at only AI and use cases and how to roll it out across, uh, the organization rather than trying to level everybody up, um, at the same time. So I think again, that kind of speaks to um, what it sounds like, your, Your approaches internally.

Speaker A: I think I was at, ah, um, I was at a conference a few months ago. I can't remember the. I can't remember the. The individual that was speaking, but she, she was, I think, a chro. For gosh, I'm not gonna be able to remember the organization. If I do, I'll let you know. Um, but she, she took it a step further based off of what I'm, I'm describing. She made like dedicated groups inside the business where they set up like formal like think tanks. So first, rather than just like this like organic flow of like conversation, like, hey, have you. Let me show you. She took it a step further and said, um, and I think this will apply for a lot of organizations and individuals listening. Like if you are mandating AI to be used, but you don't have a format for individuals to push back an idea, give thought, show you what they've built. I think there's better ways to go about it. And so she. I can't remember what they called it. There was this really cool concept of like coming together quarterly and like best idea, one kind of idea, like this is what our business, um, almost like

Speaker C: a hackathon sounds like similar, sort of, but over a quarter. Yeah.

Speaker A: Yeah. And so I think that's a really good approach. If you're looking for AI adoption and you have an organization or parts of your organization that are hesitant, like make the safety net so that they have the ability to take risks and fail forward, um, versus just saying it's now deployed, go do it, like create the environment that you want for. For your team to um, to be successful. And I think that's a really good way to do it. So if you have the ability to set up hackathons or um, AI roundtables on a quarterly basis and present ideas, um, that your people in the businesses that you are all a part of, to say, like, this is what my problem was. This is how I solved it. This is what I've built, I think that that momentum can drive a lot of adoption inside of businesses. And the way that she framed her was brilliant. And um, I think something that we can all kind of take away and apply back into our own businesses doesn't have to be this huge formal thing that she did. But, um, if you're wanting change, you have to put people in an environment that allows them to trust that they can again, try it, maybe not be great at it, fail at it, ask questions and be in that environment. I think if organizations and HR folks that are on this journey and maybe responsible for making some of this reality inside the business, then, then you're putting your employees in a position to have success versus just hoping that they adopt it and understand what they're doing with it.

Speaker C: So, yeah, I couldn't agree more. I think it's ironically, some, some profound wisdom to sort of end on is that it's like really not that dissimilar to these kind of cultures of innovation that we've talked about for a long time, right? It's like, how do we create an environment where people can try and fail? And that's okay because that's how we, you know, that's how we get to bigger and better and bolder and things like that. Mate, this has been super, super insightful. I know I've learned a lot. I'm, uh, I'm sure there are many people who are going to listen to this that are going to have a bunch of different takeaways. So I really appreciate you, uh, you jumping on the pod and having a few words with me.

Speaker A: Of course. Loved it. Happy to be here. Thank you, Matt, for having me. Thank you.

Speaker B: Thanks for joining us on another edition of the foundation series. Make sure to head over to our website to subscribe to the foundation series for monthly editions featuring future interviews on startup compensation. In each edition, we'll explore the different strategies, trends and challenges faced by startups around the world. If you have a burning topic you'd like me to cover or a standout guest that you want to hear from, drop me an email so I can dive deeper, uh, into the compensation topics that matter most to you. Join me next time as we continue to uncover the strategies and practices driving success in global tech startups around the world. Thanks for listening.