How AI Agents Can Multiply HR's Impact with Nelson Spencer

Speaker A: We know the output will kind of go up naturally just because of AI, but I think it's also the quality. I think you'll feel like you're just capable of doing a lot more than you ever have been in a very tangible way. And I think you'll also understand and realize that the actual work is shifting. So what I mean by that is a lot more like orchestrating how work gets done versus like you having to manually do the work.

Speaker B: You're listening to HR Superstars, a podcast brought to you by 15Five. On this show we talk to strategic people leaders who are making a meaningful impact in their organizations and shaping the future of work. So get ready to be inspired and discover the secrets behind building high performing teams and fostering a culture of growth and thriving. The future of HR starts here. HR has always had to adapt. Twenty years ago, the job looked completely different. We had different tools, different expectations, and different seats in or out of the table. HR systems changed how data was managed. Self service portals changed how employees interacted with hr. And every time we went through one of these shifts, the function of HR was never replaced, but how the job got done did change. AI is the latest version of that moment and it's just much bigger than most of the ones that we've ever experienced in our lifetime. HR leaders who are going to come out ahead aren't the ones who wait around to see what happens. They're going to be the ones who understand what AI can truly do for our function, where their expertise still matters, and how to bring their organizations along without losing the human side of what HR is supposed to do. The heart of our work. Today I'm talking to Nelson Spencer, founder of Augie Ventures, an AI consulting firm that helps organizations put AI to work in practical, human centered ways. Nelson built his career in people analytics before making the shift into AI consulting and spent years inside of HR data functions before helping organizations figure out how to put AI to work. Nelson, welcome to HR Superstars. Tell me, um, the movie trailer version of your career, how did you go from People analytics to where you are now?

Speaker A: Thanks so much for having me, Karina. Super excited to be here. So I would say thank you. The movie trailer kind of version. I started in sports, so if you're familiar with Moneyball, um, I worked in baseball. So the idea was to use data technology, really try to find advantages for those teams that don't have the resources to just kind of like outspend and to acquire talent. So you have to really kind of find those edge cases. So that was kind of my, I would say the first big act wanted to be a, uh, general manager of a team. Turns out one of getting one of 30 jobs in the world is quite challenging. But uh, it did kind of kickstart my career in the data space. I basically worked with the players to understand their experiences. Um, and then I moved internally to a role to help the people coaching the players directly. So it kind of opened my eyes to the broader people analytics in HR kind of space. M in that world. So that was around 2020. So we know kind of what happened uh, around then. So I got into people analytics and started to see that shift was going out into the industry. So jumped on that wave and was able to lead a few different people analytics teams and kind of dive into how do we use again using data and technology to kind of understand and improve the experiences of people. And then November 2022, it was a lot of, a lot of ruckus on Twitter at the time and ChatGPT had just been publicly announced. So I remember like creating an account like almost immediately and becoming pretty obsessed with it. And that obsession has continued. So the through line is just kind of using data technology and analytics to understand the people and had been uh, a fun, fun, interesting ride.

Speaker B: I love it. Nelson. I mean obviously when you first heard ChatGPT, your first reaction maybe wasn't fear or anxiety, but the anxiety is very real, right? For many and especially in the HR world, when you look across the HR leaders that you're working with right now, you know, there seem to be these two groups, right? Like those who are in why does this even matter case and those are who are using AI but not totally sure how to get to that next level. Right. Like there's very few who are really in that kind of elevated bucket. Given just where we're at. What do you think is going on with that hesitation? What do you think is happening there?

Speaker A: I think a lot of it kind of comes down to the unknown. Um, so I think folks are, I think we're still obviously very early in our journey and just understanding like how it works. I think for a lot of people, I think there's a lot of anxiety around roles and what that means for kind of like the future of work and specific jobs. I think as humans we don't love change. I think that is ah, a pretty kind of universal thing. So I think it's kind of like humans are doing what, what humans do, uh, and we're just trying to evolve and understand what that looks like. But I Think it's a very kind of exciting time once you understand how AI actually works and kind of what really kind of allows you to kind of multiply yourself and kind of like really get to that, um, I would say augmented version of yourself.

Speaker B: I feel like one of the biggest anxieties that you just touched on in HR is that AI is going to be replacing people. Whether it's HR leaders, HR teams, people in organizations. What do you actually believe when it comes to that specific fear?

Speaker A: I strongly believe in the idea of like AI being a multiplier in augmenting of human talent. The name of my, the venture, Augie Ventures is augmented intelligence. So I don't think that is like the ultimate kind of goal. And I think kind of what really it can do when you really understand AI, you understand that the magic in the sweet spot is when you're bringing your domain expertise to work with AI and that's kind of where you get that multiplier effect. So I think it's very strong in the camp of it's going to really kind of improve and augment, uh, everyone's roles and things like that.

Speaker B: So when you think about augmented intelligence for HR leaders, what do you see five years from now between the leader that has really leaned into this and has gone into that kind of augmentation prep process versus the one who's set back?

Speaker A: A few things I think we're starting to see, like, the work is very much shifting in kind of like what it actually looks like day to day. So I would say the folks that are like in five years that are kind of all in, it's not just the quantity, because we know the output will kind of go up naturally just because of AI, but I think it's also the quality. I think you'll feel like you're just capable of doing a lot more than you ever have been in a very kind of tangible way. And I think you also understand and realize that the actual work is shifting, um, and changing. So what I mean by that is a lot more like orchestrating how work gets done versus like you having to manually do the work. So I think the folks that don't lean in, I think the roles will kind of feel like they always have been to some degree in the sense of like very manual, not great on just like documentation, just kind of like very operations focused in a sense that like, I have to go in and I do X, Y and Z and I kind of do this, these steps, like over and over again. I think in the future you'll be orchestrating that work across different agents and you'll basically have a much wider kind of scope of work that gets done. I think that'll kind of be a huge shift for folks that lean in.

Speaker B: I love it. Let's talk a little bit more about orchestrating, because I think one of the biggest blockers that I see with HR leaders, and I was even here myself in my own journey, is that at a certain point, like, most people start to use AI for writing or completing very simple tasks, which is great, but then it's really hard to jump somewhere more meaningful beyond there. It's like, okay, I can get ChatGPT to help me write some LinkedIn content, but now what? Or rewrite this policy, but now what do I do? How would you describe what leveling up really looks like in a practical way?

Speaker A: I think you, I think you've hit on it that there are definitely different levels to the interactions with AI. So I think that level that you explained, I think is kind of like level one. It's not like level zero at this point, right? It's just like the basic kind of interaction. You'll start to just understand how it works, right? So you'll understand, um, things like memory, you'll understand things like context windows, you'll understand things like tokens. So you'll just start to naturally realize that we can't have one thread in ChatGPT for two years, right? Like, it's not going to work well, um, in that regard. So you'll just have to understand, really kind of. It all kind of comes down to context when we're talking about AI. So in the sense of just like, am m I giving AI enough context to make a decision and take some type of action? Right now a lot of the way you're interacting with AI is like that kind of chat back and forth. The next level is really starting to give it actual tasks to do on its own. And then you are obviously going to be kind of like the human in the loop and kind of being able to see what it's doing and approve things like that. And then it's just more levels of autonomy as we kind of get further up into the future. So I think that's kind of what it will continue to look like. Essentially. It'll be less on, like I pull up ChatGPT and I'm like, interacting versus, like, I know there are different workflows and agents, like already working autonomously behind the scenes. And I know how to understand kind of like what's happening. I know how to like look at the results and things like that. Um, so I think that'll be the shift. It's kind of feel like uh, extreme version of multitasking I think when you're being able to just like kick off a lot of different workflows and really just kind of orchestrate what that end result looks like.

Speaker B: It's really interesting as you're describing this Nelson, that hasn't ever really clicked with me before until right now is the way you describe this progression of autonomy from I'm chatting with ChatGPT or whichever LLM I'm giving it a task, I'm actually letting it do autonomous things is actually just like almost a career ladder for the AI you're working with is like when you bring someone really junior and you're expected to be hand holding, you're giving them a lot of direction. It's kind of constant interaction to get what you need from them. And then the more you work with them, the more skill that they develop, the more that you're learning yourself. Right. You give them now something to do on their own. Here's a little bit of the guidance. Go do something small and come back to me versus being at that pinnacle point in their career where it's like great, like I can now give you have less oversight of what you're doing, but you're expected to be running these things during the day. For me and we're having check ins of a different nature, which is I think maybe a helpful way for some HR leaders to think about this because it can be really hard for leaders. I know I've interacted and talked with to even just imagine, well, what's a task I'm going to give Claude or ChatGPT, like what would I even ask them to do? What do you do when the leaders you work with ask you that? Like what are some kind of simple ways you break them into that task mode?

Speaker A: Yeah, well I think first like I think that's a great way to frame the relationship. Um, so I think like when you're thinking about AI, a lot of folks say think about it as like a very strong, capable, like literal intern to your point. So like I think that's a uh, good framing on what that looks like. So when I say think about task and breaking things down, I try to have folks like literally just like go through the day and just like write down the things that you're actually doing. In terms of how many emails do I have to send, who am I sending emails to, what types of things Am I having to approve, um, am I having to go into uh, you know, different dashboards or different uh, strategy docs basically? I think leaders are so used to just like context switching and having to like jump between a lot of different things. It does kind of make it difficult like I think like ironically to understand like what am I, like what do I actually, what did I do today? So I think literally like writing things down, writing different tasks that you do down and then looking at those and kind of like starting to group those so you'll start to see there are, you know, how much time do I spend on emails, how many times do I have to jump into Slack or teams? What are like the decisions that I have to make, really try to capture all of those and then um, I think it's kind of like grouping those into different buckets, um, to understand where you spend your time. What's like the highest kind of area of opportunity, I would say for AI, um, and just kind of like automation in general and then going from there. So I think it's always trying to just start with how are you spending your time? Is a great place to start in general with AI.

Speaker B: Yeah, I love it. I think one of the most helpful, I'll say like tasks that I've been able to use our AI tools with right now is really just like so slack, right? Because There's a lot one within Slack where we at 15,5 are a big Slack heavy workshop that's like 90% of our work is getting done there. But there's a lot in slack that I need to know. But like it's just hard to read and digest on a regular basis. I want to know what our go to market teams are doing, what's happening in R and D. But I also don't have time to read like an entire day's worth of back and forth and like mentally to your point on context switching, it's really difficult to suddenly be there and read one message, ten threads, another five messages. So having, you know, a tool, be able to go in, say, tell me what happened in the channel day? What are the most important things I need to know? Are there any, do you see any risks of conflict, tension, slowing down of work that I can be useful on, knowing what my role is and just getting that digest is so much more valuable than the time I would have spent doing it manually. And it's those like little, those little level ups where it's like I'm spending less time reading, more time doing the work that really matters for my role, yes, absolutely.

Speaker A: AIs like superpower right now is like summarization of a lot of information. So I think that is like one of the best areas to focus on. The more that we can make the shift from just kind of like the cognitive load of the doing of the work, the simple things that we have to do so much of, the more that we can kind of offload that to AI, really allows us to have that space and that capability to do the more impactful strategic work.

Speaker B: Exactly. And then, you know, on the agent side too, one of the cool agents that we built recently here for ourselves on the people team, is an agent to help us with leave administration. It's a thing that takes up a lot of time and energy, is very, very specialized. Again, not the place where my human mind, my team's human mind is most valued. And so to have an agent that we were able to build, which is, here's all the context you need to know about 155 about the applicable policies. We obviously understand there's still, you know, legal oversight that needs to happen. But to say we're going to give you these inputs and you have to go run and send us back the details, the comms, the plan, the payroll calculator, all of those things that we would have had to do manually and takes time, but it is so much less time for an agent to do that and run it for us and us to just be able to review, check off and move along. Right. It's. I'm even kind of seeing that for, for my team of like, how can we really progress and level up in really practical ways?

Speaker A: Yeah, absolutely. I mean, I think that this kind of goes back to the levels of autonomy. Right. So like, uh, our relationship will shift and that is what it looks like when it's going well. Essentially you want to know like, the work's getting done. Right. But like, you are not the one having to kind of like literally move the pegs from step to step. Um, and kind of just see, see how that. So I think that's a great approach and how I would definitely think about in terms of just like automation and things like that. I think for people, teams in particular, I think it's really fascinating with AI just in general because there's like, there are so many like processes and systems that kind of are in the space, but also the nature of the work, obviously it's also very kind of like people first. So I think for AI in the HR space will be fascinating. But I think there's so many opportunities, uh, Especially the operational core, operational work that needs to get done. Like you mentioned.

Speaker B: How do you see then, you know, AI tools impacting career progression within hr? Like what do you think is going to be different again in that five year, six year outlook in general, I

Speaker A: think software is definitely changing, um, a lot too. So um, another like interesting thing is like how, how we interact with software and kind of like what it looks like. So if you've been spending a lot of time within the AI tools, you'll start to actually see the literal like UX and UI looks very different than I think like historically what we've been used to. So I think there's a lot less of dashboards and things like that. A lot of it right now if you can picture this, it's like you have like your chats on the left hand side and then you kind of have one sliver where it's like I'm chatting with the AI and then I see like the output essentially, right? So like whether I am building a deck or whether I am going through my emails or building some internal tool, like I think the way software is being written and created is changing and I think that's going to be very interesting for us in the HR space. I think another big interesting thing I think really kind of like looking forward for the HR tech space is a lot of software right now is obviously built for humans, right? It's like built for human interaction and things like that. The future will be software that's built for agents. That'll be an interesting shift in the HR tech space in general. I imagine there will be a future where us as humans are not necessarily having to like go into workday to update our profiles constantly and things like that. Right. I think we'll have either like, we'll bring our own like agents to work or we'll have some type of tool where a lot of that is automated and like the agents um, will be kind of filling out different things so you can kind of think about the same thing for like employee surveys or whatever. Different touch points across your life cycle. I think will be fascinating with the interaction with AI in technology and how that will I think will continue to shift, uh, quite a bit.

Speaker B: It's really interesting for HR to think about because then your workforce is going to be totally different. Right? There are leaders certainly who are already ahead of this now and it's coming up more in conversation of um, how do we think about agents in our workforce, how do we manage them, but from the HR perspective it really is thinking about how do we make impact through all this, how do we maintain consistency? There's so many different levels. When you think about what's going to happen when 25% of my workforce is agents. 40%, 50%. Right. And that doesn't necessarily mean people are going away, but there is that combination. And what's the future going to look like? I think for a lot of people coming back to what we were talking about earlier, Nelson, there's so much fear when they imagine that of like, oh my gosh, is my job going to be managing robots? But I think the likelihood is like, well, no. Well part of your job will be like, part of your job will be thinking about that, but then part of your job is still going to be humans and humans interactions and the way human and technology works together. Right. What an incredible fascinating moment for us to be able to be a part of and lead. Right. Like this is really a such a fundamental shift in our society.

Speaker A: Yeah, absolutely. And I want to double click into that Karina, because I think it's like even more important when you understand like how, how AI works. Because essentially the skills that make you a great leader, manager, communicator, et cetera are the same skills that are going to make you really good at AI. So like you have to understand like how can I break down complex problems, workflows into a simple way, like that's orchestration. You have to understand how to communicate that to AI. You have to understand directions. Right. So like when we are communicating with humans, we want to be very clear, we don't want to be ambiguous. We want to give them enough context to make decisions. It's the same relationship with AI. They're able to do the work execution wise, like significantly faster than in humans ever could. But it all depends on the inputs that you give them as a human. If we're really good at communicating, it's really using the same skills and things like that. It's just like it's a different interface, different kind of person on the other side receiving it, but it's the same thing. So I think it'll be a really fascinating time and I think it'll be really, we'll see the folks that are really good at those human soft skills already will be in a really good spot with AI totally well.

Speaker B: And as you see that Nelson, it makes me think of what you shared earlier around. Right. The fears of AI. Right. And people not maybe necessarily knowing how AI works. Right. And what it means to give a context or a strong prompt. And it is Interesting, because you make a great point that it is tied so clearly to the management skills and just the people skills, right, that we develop within HR and that we're leading from. Sometimes when I'm talking to other HR leaders, it's this narrative of like, well, if I just tell ChatGPT to go do this thing, they're going to come back and they're not going to understand it and they won't know the context. And I'm like, well, of course, if you just throw one line at it that says, hey, solve this problem for me. But that's why giving it the context and knowing how to take the thought that you have and the things that are important to share and what you're looking for and why giving it to any tool that you have is so important to do it. Well, to your point, do it clearly. Do it in a way that kind of gives it the right parameters. It's exactly what you would tell one of your team members is actually not that different. But the less you give it, the less time you spend really understanding how to work with it, the lower quality the output will be. It's garbage in, garbage out. As it is with most things in life, it's not really much different.

Speaker A: No, it's the exact same thing.

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Speaker B: Thinking about the employee side of this, right? One of those fears and anxieties that comes up a lot is that feeling like AI, especially AI tools that the HR team might be using have that surveillance like intrusive quality, I guess. How do you think we help employees and organizations build trust with AI tools and get comfortable with that workflow?

Speaker A: I think it kind of just goes back to uh, fundamentals of when we're using data technology with employees in general. I think of things just like transparency. Just think about like if you are from the employee side, right? So like if someone is using my data or tracking it, I would like to know a what data are they collecting, how are they using it, how is it used to make decisions, et cetera. So I think being transparent in your operations and your processes and sharing what that means and what that looks like. I think we have seen a lot of it in um, obviously like in the recruiting space, um, so far.

Speaker B: Right.

Speaker A: So we're seeing more and more of like automated interviews and things like that. Um, but you'll see it'll say, no, we use AI or we may use AI as part of our process and things like that. So I think just being able to be clear and be transparent, um, I think will go a long way. And I think a big piece of that from the trust perspective is psychological safety. So I think when you just kind of think about change and transformation in general, we already kind of like know best practices there, right? So we know when folks feel psychological safe, when they feel included, they feel like a bigger sense of being able to like, experiment and you know, try new things, being able to um, test things without any like, repercussions of something going wrong. I think that the more that you can build that environment, the better you will be poised to, um, make real change. And I think that's kind of two way street, right? So I think the employees will feel much more adept at understanding kind of like what's happening within processes and understanding how AI, um, is impacting them on a regular basis. So I think a lot of it just kind of comes back to culture. Um, so I think a fun theme of this conversation, right? It's just like a lot of what we do as people leaders is the same stuff that's going to be really, really important. Um, it's just going to look different.

Speaker B: Yeah. I don't think there's any skill you've mentioned so far that is not already completely within the HR wheelhouse, right. Things that we are doing today probably all the time that we don't even realize and that just haven't yet really made that connection of like it's the same principles, it's the same foundation that we're going to keep coming back to because it is change, right? And change is inevitable. And change has, we know like there, there's many great systems and frameworks out there to help lead people through it which come back to communication, transparency, psychological safety. To your point, it's all those things that we really uniquely bring from, um, the HR function and as leaders. So I love that. I think that's in many ways a very comforting thought and also a bit of a relief, right, that we're not entering this world of AI tooling that I now suddenly have to become a software engineer. That's actually the beauty of all of this is you don't have to come with these years of skills and experience in certain areas. It's taking really those parts of you, your professional skills, your personal skills, what brought you into this function and elevating it, just as you were saying in the beginning.

Speaker A: Yeah, absolutely. I think the multiplication effect, the more that you can understand what has made me great and what is my specialty area and how can I communicate that and how can I make the shift from. I might not be the one that has to literally do that work anymore, but I have 15 years, 20 years of experience doing that. So I have a ton of context on how it should be done. And it's just, literally just a transfer of your knowledge to AI in a way that makes it repeatable and things like that. So yeah, it's the same skill set.

Speaker B: I love it. And do you see HR starting to bring in more roles? Like there are functions like go to market, like engineers, right? People who are coming in with these kind of like AI tooling responsibilities. What do you think HR can learn from, um, those kind of roles or transformations that would help our function?

Speaker A: The biggest shift, I think in specific departments right now is in the engineering space. And just like for context on why that is, because LLMs are trained on text so that they are essentially really good at creating text and writing text and code and software is just literal text. So that is why I would say we've seen the biggest jump in engineering to start with. I would say what we have learned and what we can learn is really a lot about what roles look like, ah, what these, like, um, the shift in like the orchestration as I mentioned, like what that has looked like and then also like the software side. So I think if you really want to stay at the forefront of understanding what this might look like for the HR and people space, I would say focus a lot on understanding what's happening in the engineering space right now because I think a lot of that will continue to move out through, across the, uh, different organizations. We've already seen a lot of the big labs, OpenAI and Anthropics, a lot of their tools have been coming a lot more to the average knowledge worker. And I think that's on purpose. So I think when we think about specific roles and things like that, I think for the GTM engineer, I think it's a fascinating thing to study for those in the talent and recruiting space, because if you understand what GTM is, it's essentially creating the systems and processes for acquiring new customers for your product in your company. Right? And if you think about that same kind of shift in skill set, it's essentially like recruiting, but instead of for like your employees, it's for the products. This GTM Engineer is like one of the hottest roles right now in tech. And I think that's such an interesting kind of perspective because it's the same thing as, like, what I think the future of, like, recruiting will look like. I think a lot of those roles will be a lot more AI, kind of obviously, like, powered and enabled and augmented, but it's still like, really kind of breaking down. Like, it's like kind of sourcing at a high level. It's really understanding kind of like, what are our different processes? You know, what type of employee do we want to kind of, like, target in terms of outreach? It's the same thing that a source or recruiter has to do. It's just a lot more AI powered. Um, so I would say, like, that's one specific area where I think there's like a very kind of clear blueprint on, like, what it could look like. Um, when you kind of think about that from a talent and acquisition kind of perspective.

Speaker B: And I feel like this connects Nelson, to what you've talked about before, which is this idea of multiplying yourself through AI. Tell me a little bit more about what you mean by that and where you see it. In practice.

Speaker A: As humans, we can only achieve so much at one time, right? So when I say multiply myself, I would say it's like the quality, but, like, multiplied, because you can do so much more back to, like, the orchestration. So let's say you have a task list of five things, right, that they typically, you can complete that across, like, the whole week. Just because, you know, we have to put out fires, things are happening. You can imagine a world where on Monday you are just going into your tool, you're doing something like voice to text, and you're just speaking to the AI on, like, here's what I know is on my to do list. Here's the goals. Here are all the clear, like, inputs, here's the files you need to look at. Here are the people that need to sign off on that enter, and then, like, you just go to the next task. So I imagine a world where, uh, we're able to get through, like, the traditional to do list so much quicker that we're able to just have this space and have this time to really kind of dive into a lot of, like, the people and strategic work that need to get done. And so I think, like, the folks that really are able to, like, create those systems and processes to allow you to take advantage of that opportunity with AI will allow you to really kind of like, level up on the strategic and human aspect of the work. So I think that's kind of what I mean when I say multiply yourself is like, like it's not just the quality, but it's also the quantity. So it's just kind of being able to create a higher output of high quality work.

Speaker B: Yeah, that's such a great, very practical example of what that looks like. And what I hear when you describe that too is that HR also has to be ready to let go of the tasks and work that are not a value add to them. Right. Like, there can be, as with many people, like the protective nature of like, but this is mine only I know how to do it. Like it needs me and it's just a letting go of like nothing actually needs us. Right. And that's okay. Like that work doesn't need you. What the business really needs, why they've invested in you, where they're going to need your impact is on these other set of problems. That needs your unique experience across all the companies you've worked at, other leaders that you've talked to. Like you can bring that you aren't the person who has to get tasks from A to B to C throughout the week. Let the agent do that.

Speaker A: People really think their like workflows are so special and like nuanced and things like that that like AI, uh, couldn't possibly like understand how that would work. And it's like, no, it's most certainly something that could be automated or augmented in some way. I think that the biggest challenge is that you probably don't have the documentation to like, tell me like, how does this process work? That's probably why it feels so crazy and hard. The folks that are able to have the good documentation and things like that are ones that are going to be really kind of thriving in this new space.

Speaker B: That's actually such a great call, uh, out. I think back to HR leaders and team members I've worked with who tend to be the most protective of their work, who have that same idea of like, you know, this is too nuanced. It's only me. But it's only because you actually just haven't written down the 10 steps. Like, I promise once you tell someone else how to do it, actually like most people could do it. You're not doing something that only has like the knowledge of like 1% of the world. It's like we're, we're going through policy processes. Like we are navigating tough situations, but there's many of us that can do that and I think even if one of those low hanging fruit tasks for HR leaders is find a few processes that you feel that way about and document them. Like just do that first. Don't even worry about the AI tooling part but just do you have documentation of how work happens on your team? Could maybe be a first step into the world. Are there, are there kind of other things that you think would be that easy?

Speaker A: Low hanging fruit, I think that's always number one is just kind of like documentation. I think most folks don't have processes document documented. We have a good understanding of like what work needs to get done. We don't have a great framework most companies for like how we do the work. That'll be kind of a big shift. Um, so it kind of just comes back to the communication and the kind of transfer of skills and how we will be working with AI. So the ones that have their documents, processes and know like kind of where knowledge lives and where data lives, um, that'll be big I think again just kind of writing down like where do you spend a lot of time right now also like where do you like want to spend more time? Um, because I think there's an opportunity to kind of like make that shift and be um, a little bit more balanced and in whatever way that looks like for you. The better that you can get at like letting go of like I have to like own this whole thing from A to Z, the more that you can kind of expand and just kind of be this like I think this technical like generalist I think is most of what most roles will kind of look like. It's just kind of a mix of I've done this work for a long time but like I know how to uh, communicate that to agents and automations and things like that. So there will be certainly more technical areas of the work I think, but it won't be any more than I think any other big time in history. I think like I was thinking the other day, um, when I was growing up at some point they like told us to stop putting like, like Microsoft Word on your resume. Right? Like there's an assumption that we, we know how to use these tools, right? So I think it's the same thing with AI. At some point like we're not going to say like I'm AI native. It's like of course you are. I would, I would hope you are at this point. Um, so it'll just be like a shift but it'll, it'll happen gradually over time.

Speaker B: Oh my gosh you just gave me a real flashback to thinking about my early resumes which were like, you know, G Suite, Excel, all the different tools I could use, which would, would be so silly to put on a resume now. Right. It would feel so outdated to do which. Right, yeah, like we think about that and yeah, I mean I think about my daughter. I mean the way that technology and tools are so native to her and her friends and what they're doing, what they do in school every day, like it'll just be this assumption that they are entering the workforce with a totally different foundation of knowledge.

Speaker A: It's a different skill set and it's going to look very, very different. So yeah, it's going to be exciting completely.

Speaker B: So as HR leaders start to let go more of the I need to own the A to Z. Where do you feel HR really brings in that human centered, unique perspective and how do they maintain that through this transformation?

Speaker A: When we think about like human involvement and human centered, it's the same work has to get done. So we still have to have the right policies, we still have to have um, the right processes and things like that, that. But that middle layer is what's going to get kind of automated. So we still have to have a lot of human involvement on. Again, when we're creating this process, who is it for, who's benefiting, who's not. When we're creating this survey, we have to understand kind of what are we trying to get out of it, things like that. But again the execution of sending out the survey, analyzing the results, things like that, that's the back end that we have to kind of like, like loop between so like you don't have to worry so much about the execution but the inputs and like the human aspect of it all is still very critical because again like that's, that's only how like the AI will do really well is when you have the good inputs and you have the good feedback, it's really the same thing that you do now. Uh, I would say is where you should continue to lean in from a human perspective.

Speaker B: I love that Nelson. And that comes back to what we were talking about earlier too. Right. Which is just, it's all the skills you already have have, it's all the things that you have been doing that you do all the time. When your company goes through change or a new initiative or you're launching a program, it's just leaning into that toolkit and figuring out where these AI tools are going to be a part of that toolkit. Like what are the things that they can really do for you. It's not a replacement of you, but just an enhancement really of what you're doing. I think, um, that's just such an incredible way to think about it. Nelson, we could probably go on this topic for ages because everything you're saying is sparking so many ideas for me. But as we wrap up, tell our listeners, where can they find you? Where can they connect with AJI if they want to learn more about what you're doing or chat with you?

Speaker A: I'm on LinkedIn. I'm on all the different platforms. Company is Augie Ventures. Um, so it's a U G I co you can learn more. Um, kind of starting to create more content, different resources for folks in the space. Um, so, yeah, we'd love to stay in touch with folks.

Speaker B: Well, thank you so much for coming on here today, Nelson. This has been incredible and can't wait to have you back on because I'm sure we'll be talking about this for many years, years to come.

Speaker A: Absolutely. Thanks so much for the opportunity, Karina. I appreciate it.

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