The HR Skills that Survive AI: What’s at Risk? What Survives?

Helena | GoFIGR • 01:16

And while we're waiting, I sent a little reminder yesterday, but above my head here or in the QR code on the purple side of the slides. If you have a second just to scan that QR code, you can have a look at how I might impact your own role. And I saw yesterday people give that a try. And Kim, the QR code in your side.

Kimberly Burns • 01:40

What does that do? Yeah, this is a QR code that if you haven't yet joined the human community, that is a direct link into our free community space. Thank you. You can go on, sign up, and check us out.

Helena | GoFIGR • 01:59

We are… We are at 70, Kim. Yeah, interesting. Do you want to keep going? Do you want to wait a second or do you want to kick off?

Kimberly Burns • 02:12

Let's kick off because I know that we've got an hour and we've got a fair bit to do. So I think we'll kick off and just say again, just for those that might have missed it, that we are recording this today and we will send out a recording of this post the session. And just on behalf of Helena and I, my name is Kim. I am a co-founder of Humaneer, which is a global HR community, and also the co-founder of Mak, which is an AI assistant that we have built purposely for HR practitioners. Helena, I'll let you introduce yourself.

Helena | GoFIGR • 02:53

Thank you. And, yeah, thanks so much for coming. We were a bit blown away by how many people accepted our invitation, actually. I'm one of the co-founders of a CareerTech platform called GoFigure, and we do a bunch of different things that you can figure out from our website, but today I'm representing the part of our business that helps companies understand and assess the impact of AI on job skills and tasks.

Kimberly Burns • 03:15

And so, yeah, as Helena said, we're pretty stoked about the amount of interest that this webinar has got and how much it has resonated. And you know, right now, I don't know about you, but what we're seeing is a lot of webinars about the AI tools we should be using in HR, prompt engineering, productivity hacks. But there's not that many conversations that are really asking, you know, what does AI mean for HR itself and our roles and our teams and our functions and what kind of value and work that we're going to be doing over the next few years. And like, genuinely, I think that's because, like, as HR professionals, we haven't had a chance to look up from our day job and invest a lot of time in thinking about it. Like we've got so much BAU, we're still supporting everyone else, asking to make sense of AI in our organizations as well. And so today we just wanted to take that time to really focus on what AI means for HR. It's not another webinar about tools, but we're going to have a conversation about what AI is already doing to HR work.

Kimberly Burns • 04:26

You know, we'll talk about what skills are becoming more valuable, what skills might change and how HR can maybe get a seat at the table instead of having this kind of done to us. Just a little bit of storytelling that Helena and I met because we were super interested in this question. I got to know Helena and understand that the incredible work that her and the team are doing at GoFigure about the impact of AI on the task and roles across organizations and I've not seen that done before. When we connected, I jumped on fangirling what they've built. Hopefully, we connected from the other side because we built Mak and we built that because we could see that HR teams were drowning in repetitive high-pressure admin and thought, there's got to be a better way. So today, we're really about joining the two of our sort of roles together. It's the data and then the real HR reality.

Kimberly Burns • 05:31

So before we kick off on the event, we'd love to just do something interactive and get a bit of a sense check, and we've worked out how to use polls in Zoom.

Helena | GoFIGR • 05:41

We think we have.

Kimberly Burns • 05:43

We think we have. We've tested it twice, but we'd like to just ask a couple of questions. One is just to understand, is your organization currently experimenting with AI? And are you clear on the impact that AI is going to have on your own job? So I'll give you just like a couple of minutes, seconds to do that. Okay, I can see now it's coming in. We sure can.

Kimberly Burns • 06:16

So what we can see that, you know, the majority of organizations are experimenting with AI and that's sort of becoming clear in the data that we're seeing. And also, you know, we're seeing the gap. We do have the majority of people on this session right now, sort of a bit murky. We've got a little bit of idea of how it's going to impact, but we're not like, we've not got the AI roadmap sorted out for us. So we will have an opportunity at the end for questions. We got a load of questions in registration forms and we've tried to answer them through the session today. We're also going to do some follow-up work and blog posts and videos because there was some really, really fantastic questions in there that we think will be really relevant for all of us.

Kimberly Burns • 07:04

So sit back, relax. We've got Andrea and Corinne from HumanEAR, our community manager and my co-founder, moderating and we've got Jenny who is supporting GoFigure. So if you've got questions, feel free to pop them in the chat as well. We'll try and get to them at the end. And Helena and I are also fine to hang out if people want to hang on the call and just have a little bit more of an informal chat as well.

Helena | GoFIGR • 07:33

So we'll kick off. All right. And I think we worked out earlier that you need to shut the poll window yourself. I think I've closed my end. If you can't see the screen now and there's a poll box, you just have to close it yourself. It's not me doing something weird at least, I don't think it is. All right, so who here saw that announcement from Atlassian last week, where Mike Cannonbrooks decided that it was time to cut 10% of its company headcount.

Helena | GoFIGR • 08:02

And in that announcement, he said that AI is changing the mix of skills that we need and the number of roles required in certain areas. And you probably also saw a couple of weeks before that, that Jack Dorsey, who used to run Twitter and now runs a company called Blot, which is SquarePay and Afterpay and a few other businesses. Jack Dorsey cut 40% of that company's headcount. And what he said was really quite interesting as well. And I'll quote this, within the next year, I believe that the majority of companies will reach the same conclusion that we have about AI and make similar structural changes. And you probably also saw that for Atlassian at least, there was a little bump in the share price, it's kind of gone away now, but certainly the markets reacted positively on the day. And the chances are your board or your senior leadership team read that announcement too.

Helena | GoFIGR • 09:00

So somewhere between seeing that headline and your next senior leadership team meeting or your next board meeting, there's going to be someone in your organisation who is asking or is going to ask a version of, could we do that? Or should we do that? And I know because I'm obsessed with this space, anyone who kind of knows me knows I'm obsessed, that there are heaps of reports out there telling us that either AI is gonna create loads of jobs or equally many reports saying it's gonna cut jobs, but that's not terribly helpful. And certainly not in terms of how we think about the future. So whilst I acknowledge that humans are generally and inherently terrible at predicting the future, my team and I did have a go. And so we built a methodology on a framework that was originally developed by the International Labour Organization. I've also noticed that some friends of GoFigure who are on this call also supported with this. I can't say who they are, but they're on the call and they know who they are.

Helena | GoFIGR • 10:01

And we worked together to enhance it quite significantly so that we could quantify exactly how AI was going to impact jobs at the task level. So we actually believe that organizations are more likely to fall into one of three future scenarios. So on the left here is scenario one. We actually modeled all three, but scenario one is really conservative. So let's just say you're deciding to do nothing deliberate. You don't have an AI strategy, you're not actively deploying AI, but there is a catch. Unless you can put a force field around your tech systems, your third-party vendors, AI is already everywhere.

Helena | GoFIGR • 10:44

It's in the tools that you already use, it's in the platforms that you've got through third parties like Kim and I, you're being affected whether you choose to or not. Scenario two sounds like where most of us on this call sit. So this is more experimental. So you maybe have an AI roadmap in your team or your company and you're executing against that roadmap. So you might have some pilots in place, you might be experimenting with some productivity tools, and maybe you're rolling those out in pilot form across the company. Scenario three is what we affectionately call release the Kraken or a more unhinged model, where let's just imagine what is possible if AI is fully embraced and fully released. So we're talking here full agentic deployment, end-to-end automation.

Helena | GoFIGR • 11:33

So wherever it's technically feasible or structurally possible, we redesign how work gets done. With me so far? Awesome. I think it's safe to say that right now, AI is automating tasks and not whole jobs. I will reserve the right to take that statement back if suddenly AGI or ASI is released, but right now, it's nibbling into the tasks that we do. What our model does or our different scenarios do is we break down every single role into its component tasks, and then we assess how likely each task is to be affected by AI across those three scenarios that we talked about. And we model all three so that you can understand the implications of the choices that you're making. And what we do here is that every task lands into one of five future states, although we're a sixth is emerging.

Helena | GoFIGR • 12:35

So there'll be tasks that stay with you. AI can't do this stuff yet, or at least not as effectively as us mere mortals. So things that involve human judgment, relationships, that kind of nuance that only a human can understand. There's a scenario where you lead an AI assist. So you're in charge. AI makes you faster and better, like your co-pilot type of scenario. There are tasks where AI will lead and you will guide, so AI does the legwork and the human does the review before it goes anywhere.

Helena | GoFIGR • 13:07

There will be tasks that can be fully automated end-to-end, so this is where there's no human in the loop. And there will be tasks in the future that fully disappear. So these aren't automated, they are almost made redundant by how the work changes around it. And this sort of taxonomy matters because it gets us out of this abstract, what will AI change about HR? We're talking very, very specifically about the tasks that your team perform or you do in your day-to-day job that might look fundamentally different. So what we're going to do next is look at what that actually looks like in practice. Oops, sorry, I've gone too far.

Kimberly Burns • 13:47

And this is why I loved working with Helena to put this together, is because we actually get to break down tasks and talk about tasks and skills. So this is actually a real job ad, a real HR manager job ad that was posted in the last few weeks from PwC for a HR manager role. So you can see, like, it's a solid, meaty role. It fits into what we think about a HR manager. You can see, like, the last dot point talks about embedding AI into, you know, day-to-day. But we wanted to show you what this looks like from just what Helena said before, what AI takes, what you take, what stays human. And so that is on the next slide.

Kimberly Burns • 14:35

Let's see what we found. So here, this is literally where I think it brings the story to life for me. You can see that we've broken this down and there's 18 tasks, and we've mapped them across the three different scenarios that Helena spoke about this. So the conservative, so your organization, or you do nothing. But you can already see in that, that AI is starting to lead some of those admin operational tasks. The second scenario that we've mapped is that experiment, which is where the majority of us are all sitting right now. Again, you can see that automation takes the admin, you've got AI leading in some of the analytical knowledge workers.

Kimberly Burns • 15:23

I'm just laughing at the comments, sorry, that's multitasking. You can also see where you lead and where it stays human. Again, if we move down to the transformational, the Kraken has been released, you can see that the AI is doing a lot of the heavy lifting across most of the operational and some of the analytical work. So what we can see across here is that there is a consistent pattern. The interpersonal, the relational, the strategic, the judgment-heavy tasks, stay human, stay with us. It's the analytical, it's the administrative, it's the execution-heavy tasks that we'll see get progressively handed across to AI. Feel free to take screenshots and photos of this.

Helena | GoFIGR • 16:18

But there's perhaps an easier way to look at it if we sort of merge some of these different categories together and put it in a nicer, a bit more easy to consume view. Even in the most conservative scenario where you do nothing deliberate with AI, around 83% of this HR manager's tasks are AI impacted within the next three years. So the blue is the stuff that AI won't touch. The yellow is what AI transforms, so the human's still there doing the work, but it does change the nature of the work reasonably significantly. And the red is what AI automates or eradicates entirely. And so just remember that that scenario one is like, we didn't really try, we didn't do anything deliberately. But by the time you get to that more transformational scenario, you're looking at a role in a few years that could be very different than it looks today.

Kimberly Burns • 17:16

And so, if we go to our next slide, you know, this is where we can talk, we can break it down into sort of the skill shifts for the HR manager. And so, as we can see, if AI is changing what we do from a task base, it also changes what we need to know. And on the left, you know, these are the skills that still are going to remain important. And you can see those across the different scenarios in the HR manager role. Coaching, the relational, ER, change, engagement, influence, they're not going anywhere. And if anything, we're going to start to see them become more valuable as this routine work gets automated. What I find really exciting, interesting, opportunistic, something, is when we start to talk about these new skills, because as Helena said, it would, you know, it's been so theoretical and we haven't been able to kind of like evidence-based and like break it down into tasks, but, you know, we're starting to see some of these new skills that are going to start to emerge as AI transforms our work.

Kimberly Burns • 18:25

And if we look at AI output evaluation, and there we're kind of talking about just making sure that AI isn't hallucinating, there's a human in the loop at the end of all your AI tasks. The workflow orchestration, you know, if we're starting to talk about agents becoming, you know, being more prevalent in our workforces, you know, we've got to manage those agents. How are they working end to end? Are the automations working? You know, those strategic people analytics of like. What work do we need to do in the future? What type of people?

Kimberly Burns • 18:56

What sort of agents? You know, these are the conversations that are happening now in some organizations and over the next sort of couple of years will be more prevalent. And then we can see on the right hand side that these are the skills that are gonna become less important as AI takes over the heavy lifting. And that's the reporting, the documentation, the systems admin roles. It doesn't necessarily devalue those roles within HR, but it's just kind of saying that you don't need to spend a lot of your time upskilling training in that space. And what I see across this whole sort of slide and as we've broken it down is, you know, it's, It's not about what AI is here to do, but it's like, what should we in HR be doubling down on if we want to stay relevant, influential and future fit?

Kimberly Burns • 19:51

And I think one of the questions that come out of this is what are our plans as an individual and as a HR department and as a broader function to kind of start developing in that middle space, the new skills? I can't remember if I'm on the next slide or not.

Helena | GoFIGR • 20:08

It's me. It's all right. I've got this one. So that was one role. And what so we also wanted to see what this looked like if we zoomed out a bit. So we actually assessed 100 different HR roles post.

Kimberly Burns • 20:40

There you go. You're back.

Helena | GoFIGR • 20:41

Oh, OK.

Kimberly Burns • 20:42

Thank God. It's your slide.

Helena | GoFIGR • 20:44

All right, well, let me take that. I'll start that one again. So that was one role we just looked at. We also wanted to know if the same patterns held true across a bigger sample size. So we processed 100 different HR roles that were posted in the last 12 months across people and culture, talent acquisition, OD, L&D, people analytics, tech and reward. And this is the result. So that meant that we assessed just over 1,800 individual tasks across those three scenarios that we've talked about before.

Helena | GoFIGR • 21:19

And patterns kind of hold and intensify in some case. So the proportion of tasks that stay human remains relatively stable. But what does change is the pace at which more analytical and execution type tasks move from human led to AI augmented. So that's your human plus AI scenario. So what I take away from this is the pace of AI adoption in your organization and the tech stack that you choose to deploy has a massive impact on what your team's work is actually going to look like in the next three years.

Kimberly Burns • 21:56

And hands up or thumbs up if you see a face in this. Yep. Thumbs up, hands up. But what we're seeing here is spoiler alert, there's also a vase in there. There's a face and there's vases. But what we wanted to share with this slide is that, some of us are going to look at this and see a vase, and some of us are going to see two faces. That's exactly what's going to happen or is already happening when we're talking to organizations and AI strategy. This same data that we're showing you can lead to two completely different futures.

Kimberly Burns • 22:37

I've got one leader or one organization could look at this and say, great. There's cost-saving, there's a cost opportunity here. We can automate work, reduce headcount, become leaner. We're seeing this already happen, as we already mentioned with the Lassian block, all of these large reductions in workforce due to AI. But also on the other side, a leader or an organization or HR team can look at this and say, wow, what becomes possible if my team is no longer drowning in this low-value administrative work? What higher value work could we finally make space for? What could we contribute as HR if we had more headspace?

Kimberly Burns • 23:21

For me, that's a really important distinction because what we're saying is AI does not automatically create a better future for HR. It's going to depend on how we as an individual, as a team, as a function and organizations interpret the opportunity in front of us. Are we going to use AI to strip our function back? Or are we going to use it to elevate and evolve our function? It's not a small difference, but one thing we hope to impart is that, We want HR to have agency and be able to influence how we respond in this.

Helena | GoFIGR • 24:01

So we got a lot of questions when we put the invitation out for this webinar about things like our entry level and grad jobs the most impacted. There are some definitely some trends and some correlations, but actually your exposure to AI disruption or the size of the opportunity, depending on how you like to look at this, is it two faces or a vase, depends mainly on the type of work that you do. And there definitely is some correlation between sort of more entry level type of tasks and AI disruption. But we also categorise tasks across those 100 roles and 1800 tasks. And the pattern here is quite clear. So, those administrative and more routine tasks, the documentation, the reporting data entry scheduling, those types of tasks in a more transformational scenario and certainly as this technology gets better, that work is effectively going to be automated. AI can do it faster and cheaper and without as many errors as us mere mortals.

Helena | GoFIGR • 25:07

So, if a significant proportion of your time or your team's time sits here, this is where I think you should pay attention. In the middle there, that more analytical and cognitive type of work, those types of tasks, things like strategic workforce planning, compliance monitoring, policy interpretation, what you're going to see there, or at least the trends that we see, is AI takes a lot more of the execution work, but humans keep the judgment. The tasks won't disappear, but AI changes your part in those tasks. Your team will shift from doing more of the work to reviewing it and actually being accountable for what AI produces. I think this is where legislation is going to have to start changing. We're already seeing that it's going to change as it needs to keep up. On the right there, the more interpersonal leadership, strategic and creative tasks, so stakeholder relationships, governance, ethical judgement, strategic advice.

Helena | GoFIGR • 26:05

AI at the moment barely touches these. So as the routine work does get automated, this is where your most experienced people, ideally you, would be spending more of your time, not less. So just have a think really about the distribution in your role and perhaps your team's roles across these three categories of work or tasks because it's going to tell you where your exposure or your investment should go. And just a reminder that this was a kind of generic version of the model, so we did this assessment on a more generic version, but in the experimental model that we did, we assume that you were all using Mak. So that being the case, that you're using technology like Mak, and just as a reminder that your company's tech stack, your own specific jobs and tasks do impact this, but we had to look across those hundred roles to see if there were patterns here about the skills that survive, the skills that shift, and the skills that AI is going to chomp into. So what we're looking at here is the skills the model predicts that HR teams need to be thinking about on average. So on the left are the skills that are worth protecting, things that involve influence, relationships, knowledge of your business, your ability to solve problems.

Helena | GoFIGR • 27:27

These are your really defensible human capabilities. In the middle, those types of skills that you need to start thinking about building. AI collaboration, so it's things like knowing how to work alongside those tools effectively and not just using them to write more clever emails. And AI output evaluation like we talked about before, so making sure that you're competent and capable of reviewing what AI produces and making judgment calls on whether it's right or appropriate or missing something that only you as the human would catch. Change leadership sits in its own kind of category here because someone has to bring this to the rest of the organisation. You'll hear me say this later, we're kind of building the plane and flying it at the same time in HR, given our responsibility to think about strategy across the whole organisation. Now, that's not a new skill for everyone, but the stakes just got a bit higher for people in HR, people in culture.

Helena | GoFIGR • 28:21

And maybe a provocation for you, if you look in that kind of middle bottom transformation, so this really only applies if you're going a bit release the cracking with AI. But those skills in that middle column, so governance, ethical decision making, these aren't the kind of skills that you kind of pick up in an afternoon workshop. They really mean being accountable for AI producers under your watch and understanding that black box well enough to know when something's gone wrong. And I wonder really, Kim, if you think that whether that personal capability exists in many HR functions at the moment. Thank you.

Kimberly Burns • 28:54

I genuinely don't think it does. I think it's growing as a capability broadly across the organisations as we get there, but it's definitely a skill or a gap that HR can really play a big part in if we look at upskilling in that space.

Helena | GoFIGR • 29:15

Was there anything else on here that surprised you when you first looked at this when I showed you, Kim?

Kimberly Burns • 29:21

Yeah, it did. And I think there are a few things. One thing that surprised me was, you know, in HR, we've always been sort of joked or kidded, you know, that we're the soft skills, we're the relational people, we're the ones that just talk. And there's not a lot of value historically that has kind of been placed on that part of the function. But we were always kind of measured on outputs and success, the reporting, the data, the letters, the policies written. But what we're seeing now is this, you know, the industry moves forward. We're seeing AI handle a lot of those output data roles and the relational skills have become critical. So that was really interesting, but I think it's also really interesting that it's what we've been good at.

Kimberly Burns • 30:19

Again, as I said, we've been assessed and measured on our success in data and operations and BAU work. And those things are still going to be really important, but they're not going to be the things that differentiate us moving forward. So it's like the shift is moving from the value that we create is not our outputs, like what we produce, but it's moving more towards how we think and design. And that's scary, exciting, gives us an opportunity, but it gives us, I guess, something. The develop new can also be kind of a bit uncomfortable because I think we talked about it. These aren't skills that I can just do a two-hour workshop on and walk away and be accredited and comfortable and capable.

Helena | GoFIGR • 31:09

And it changes so quickly. And it changes, yeah.

Kimberly Burns • 31:13

And it's like what we need to know is can we work alongside AI? Can we challenge AI? How do we take accountability for what it produces? It's just a very different capability. And there's a reality, I think, that we've not had the time or the space or maybe even the roadmap to start building these more broadly. We're still in the work. which is also fine, and maybe it's also about knowing this is where we are as a whole.

Kimberly Burns • 31:45

There's a big opportunity in that, and we don't have to start doing all of this at once, but let's start thinking about how we build those capabilities because they're going to be more important. That was a big spill. I've thought a lot. I've had a while to look at these slides.

Helena | GoFIGR • 31:58

That was your TED Talk. Thank you for coming to my TED Talk. So let's take a look at the next slide. They were.

Kimberly Burns • 32:08

I was going to say, you get me again, but Helena, maybe it would be really great if you can break down where the data came from.

Helena | GoFIGR • 32:14

Yeah. So the previous slide showed the skills that apply more broadly across the whole HR function, but this one goes a level deeper. So these are the skills that show up as distinctive per function. This might be another thing. We'll leave it up on the screen for a second for you to take a screenshot and just as a caveat, your tech stack, your role, your specific function, your company goals and ambitions do vary this, but across those 100 roles that we assess, these are the themes that came up. What did you notice in this, Kim? Because you're more. I left the practice about five years ago and went the tech side.

Kimberly Burns • 32:51

Yeah. You know what, generally what I think is like how when we dig deeper and we break it down into these more function tasks lists, like here's kind of our roadmap. Here is, you know, the things that we need to keep building. And then we've literally got here are some of the tasks that you can start developing your capability. And I think I can see across like OD and culture and learning and development, we're talking a lot about design of work. And you know, in the OD and culture, it's like building the capability to design for human agent teams. Like how do human and agents work together?

Kimberly Burns • 33:31

How do we manage that? What does that look like? What is the right scenario? Oh, gosh, who knows, you know, and we're talking about in L&D, like it's. We don't traditionally see those like one day management courses anymore, you know, it's more centred around human-centred design and storytelling and micro-skilling and, oh, like there's a real opportunity. And I think for me, being in HR and going, I don't know where to start, this kind of gives us a place to start building. So that's what I see when I look at this.

Helena | GoFIGR • 34:07

I think human-centred design, I really think everyone should be trained on human-centred design. That really changed my career when I did that about eight years ago. Amazing.

Kimberly Burns • 34:17

Yes, it's great. And I think actually, not to do a plug, but I will, but we do have a session running next week collaboratively with a company called PX Dojo, who are running a sort of six-month series around product design and thinking and how to apply that in HR. So again, it's like for me, it's all very good to now know these skills, but where do I build those skills? So anyway, if you have a look, I'm sure we can drop the link in the chat somewhere. Let's go back to the slide, and so now, you know, the data that we have seen through here, which is amazing, it kind of starts to tell us what AI is going to take away or automate. But the question now that we need to start thinking about is, you know, what's getting in the way and how do we make sure that we have the headspace and capacity to start building the future skills? Well then, you know, I feel very blessed to be part of the human community and get to spend so much time with HR practitioners and what I am seeing from a, you know,

Kimberly Burns • 35:26

you know, from our hundreds of conversations and chats, is that for HR, it's not a lack of interest in doing this. It's not necessarily a lack of resistance, like we know we need to do this, but it's around capacity. It's around that we're stuck in the BAU, we're still drowning in the documentation, the investigations, policy, performance, admin, you know, all that work that's foundational and needs to get done, but doesn't, you know, isn't taking us forward on this. So I think we can talk all day, as I said, about the skills that we need, the new skills, the future, but if we don't actually create the headspace for us to build those skills and build that capacity, then really we're kind of just like going to go around in a circle, and so I think some advice that we're learning and seeing as organizations adopt AI is that, you know, you don't have to start redesigning your function all at once, and I think particularly for us in HR, we need a safe space to start experimenting with AI and breaking down tasks and not trying to roll out this massive transformational program, but by really being intentional and finding those pieces of work and workflows where AI can help safely and practically, you know, we know, we've already seen in the data that we've showed you today, those administrative tasks that are going to be automated. So how do we lean into working on those as a start? It's not a magic fix.

Kimberly Burns • 37:06

There is no like magic wand, do this course, it's going to be amazing. But I think some of the advice is, you know, start experimenting, free up some headspace and just start building from there and find some AI that can help you with that. We built one.

Helena | GoFIGR • 37:24

And this is kind of why we ended up doing this, Kim, isn't it? Because we were sort of so amused by the fact that part of what GoFigure does is to assess the impact of AI and you're building an AI that impacts jobs.

Kimberly Burns • 37:37

This is literally why we built Mak was to automate literally all of those tasks that were in that slide that was like AI automates or AI leads humans review. Because my co-founder Corinne and I, we've spent 20 plus years in HR and the things that kept us from doing the strategic work, the capability building was the BAU, was the admin. So we'll talk a bit about that as a solution to like moving from where we are now to the next stage. But humans, I've seen some people say what's getting in the way of humans and I'm like, yeah, 100%. People, which is so messy, right? People be people-ing. And I think another thing we kind of talked about it again on this slide,

Kimberly Burns • 38:29

Nobody's got this figured out. I look at LinkedIn and everyone talking about all these amazing things that they're doing and the LinkedIn version of what is happening in AI versus reality, there's a big, massive gap. So you are right where you need to be, but now let's start building that capacity and let's do it as a collaborative function because we have seen already that doing nothing is going to come at a cost for the company. But if I'm really thinking about it and focusing on HR, it's going to come at a cost of our own employability and our own skills as AI continues to evolve. Helen and I were chatting and we've already heard of people leaving organizations that aren't allowing AI experimentation because they already know that if they're not up to speed with that, then they're not going to be as employable in the future. So doing nothing is a choice. But let's not stay there.

Kimberly Burns • 39:38

I think experimenting as we found in the polls, in the conversations, in the chat, this is where we sit already. We are seeing, we hear lots of teams experimenting with chatbots, AI-assisted recruitment tools, co-pilot. None of these are necessarily headline-generating, massive transformational projects, but it's compounding. And in HR specifically, this is where tools like MAP come in. We sit in the middle of your workflows. It's a really safe place to experiment, targeted, practical, grounded in the actual work that you do. And the other question I think we should be asking ourselves in this, what is everyone else doing, is what is everyone else in our organization doing with AI?

Kimberly Burns • 40:31

And experimenting with AI. pilots are happening in the business, how is that impacting our people and skills? And this is where we talk about HR building the plane and flying it. Like, we've got to look after our own teams and our own functions, but then we've got to keep an eye out on what is the rest of the organization doing? Which is why, you know, we will kind of talk about how to free up our headspace and capability and capacity so that we can then look towards the organization. And I know, Helena, you've got some examples from the clients that you work with in the transforming space.

Helena | GoFIGR • 41:06

Yeah, we, and I also do a weekly-ish future of work post if you follow me on LinkedIn. I say weekly-ish because I don't always find interesting jobs to post about, but I do keep an eye on what future companies are doing in terms of hiring, because I think the job markets are a really good proxy of what's happening out there in the market, where, if you're sort of willing to invest in some of these roles in terms of transformation, AI enablement and so on, so you can follow me on LinkedIn to receive that weekly-ish post where I spot interesting hiring trends. Combank, which is not one of our clients, you'll have seen that they launched about, I don't know, two or three weeks ago, about a $19 million fund. It's called their Future Workforce Program, where they're investing in AI skills. Moderna, not a client of ours either, one day, is actually, they've actually merged their HR and tech leadership into a Chief People and Digital Tech Officer role.

Kimberly Burns • 42:03

I love that, yeah.

Helena | GoFIGR • 42:04

Which is, yeah, super futuristic. I guess they're realising that not all of their workers are human, and I met a mining company a couple of months ago that have 5,000 agents in their HR team, and they're now working out how the hell do they put agents on almost like an org chart, because they need to know what AI agents they've got performing work. And then in some of our own client work that we're doing, I'm generally under NDA with most of this work, as you can imagine. Companies experimenting with AI aren't always entirely comfortable making that work public. But a company that we're working with in the UK is actually taking it one step further. So we did this impact assessment across their people team, that they're now looking at how they redesign their HR operating model in light of what the future HR team will probably look like. And we're working on them to design future job descriptions based on what future tasks will happen as they roll out their AI agenda, which is really cool.

Helena | GoFIGR • 43:04

Another team that we've worked with have used that skills data to work out where they need to prioritize their learning investments. You don't just roll out AI training in a day, it takes time. So they're looking at where they invest in their AI upskilling, and they're shifting their budgets to more AI futuristic types of skills, and they're worrying a bit less about the skills that AI is effectively going to make redundant, and they're also bringing it into their workforce planning capabilities. If you're doing something cool with AI, drop it into the comments. We will transcribe all of this and we'll make sure that we blog about this as well. So if you're doing something really cool, and you're comfortable sharing, drop it into the comments. Now, I haven't been able to see any of the questions because I'm presenting and I got the fear if I do something odd that I'm going to lose the questions.

Kimberly Burns • 43:58

I've got a nice little wrap up. Great. Obviously, we've got some. We went a bit QR code crazy this morning. We did. Thank you, Canva, but we did want to spend some time in questions. I think just before we wrap up, there's a good little way to summarize what we talked about today and that probably the biggest mistake we can do as a function right now is pretend nothing is happening because doing nothing is still a choice that we can make.

Kimberly Burns • 44:31

We are seeing AI changing the work and if we don't get in the room, build and start experimenting then decisions are just going to be made without us there. We're not going to be able to shape them. But I think the other takeaway we'd love for you to have is don't panic as well. And the answer is agency, you know, start small, look for work that can be automated safely, use the capacity to build on that. And you don't have to do it alone, like there is, we've got the human community, you've got a network of peers, and there's, there's companies like GoFigure and Humaneer and Mak that are here and working in this space to support you. And because from there, if we start leaning into this, I do really truly believe that we've got a really, really fantastic opportunity to, like, not just respond to this shift and evolution in HR, but to kind of, like, lead it. And so we'd love to say in a wrap up before we get to some questions, you know, if today has sparked anything in you and you are interested, you know, Helena's got the QR code up here, you can literally do that and put your own role in there.

Kimberly Burns • 45:45

And what we showed you up there with the HR manager and the, you know, the task breakdowns, you can do it for your own role and you can do it for your team's role and it's completely free to do. So, and if you want to watch Mak in action, if you want to sort of start experimenting with AI in your workflows, in your teams, we'd love to keep the conversation going. So we've just got a little demo that you can watch there and we will be running a live demo of Mak next week. So in our follow up email, you will have a link to that. And something really interesting that has come out of this is. For Helena and myself, we just don't want to say, here's the skills, good luck, go on, find where you can build these, have a good life. What we're actually doing now is starting to explore a broader workshop series around building these HR skills that we talked about in this presentation today.

Kimberly Burns • 46:48

We're just really curious to know if that's something you're interested in, and if you are, we'd love you to join the wait list just using that QR code. Just so we know how many people are really interested and how we can build this to support you and us as we go. So you're not alone, there's tools, there's peoples, there's partners, there's communities here to support you and help you. So that's kind of the big takeaway. Helena, did you have another takeaway before we jump into some of the thematic questions that we got?

Helena | GoFIGR • 47:22

Oh, I've got many, but let's get to questions. We got submitted, I think, like 50 questions in advance. I'm sure in the chat, I can see like, I've caught up a bit now, I can see there's heaps of questions. We will issue, make sure that we issue a recording, as Kim already said, and if we don't get through all the questions now, we will make sure that we distribute kind of as much as we can our response, as well as all of the comments here as well. So, we will try and tackle as many questions as we possibly can. Has someone been curating questions on the call? Andrea, have you been looking, or Corinne?

Andrea Kirby • 47:57

Well, I've been watching the chat very carefully, and I haven't seen any questions as such. I wrote down a couple of comments, but I think that you then, in the next slides, went on to answer them.

Kimberly Burns • 48:13

Well, that's okay, because I'll jump in really quickly, because there were a couple of like We, of course, you know, broke the questions, those 50 plus questions that we received kind of fell into like three thematic areas that we could potentially talk about now and, you know, we would love if you want to join in the conversation, like, just put your hand up and join in. And I know we've only got 10 minutes, but we said we're happy to stay on. But, you know, that one of the main themes that came out of sort of the variety of questions was, you know, what happens to HR careers and our pathways for like early graduate HR people in an AI enabled world. We've had we've had questions from like universities and tertiary educations, and then we've had, you know, questions from actual people in the early stage in their careers. And then how do we build the teams and hopefully, as we've demonstrated today that, you know, the HR roles aren't disappearing, but the way we're going to be building for them in the future is changing. The way people are going to be entering HR and grow is going to look different to like when we started like five, even five, 10, 15, 20 years ago, because, you know, we all know historically we entered into some of those admin heavy roles and we kind of grew from admin, coordinator, wherever we go.

Kimberly Burns • 49:37

But now with AI automating a whole bunch of those, like what is the. pathway going to look like. And again, that's something I think we're still working out, but it means that we need to intentionally put some effort into to deciding what that looks like. So the pathway is still there, but perhaps now, instead of, you know, we're teaching our early career people to, you know, analyse the outputs of HR, like we said, understand how to work with and manage and review the agents. How do we build those stakeholder judgment skills quicker with more shadowing, more exposure to those type of roles, project management? You know, I think it's not that those pathways just disappear, but it's like, what do these pathways look like now? Helena, did you have any thoughts?

Helena | GoFIGR • 50:33

Yeah, there's this amazing woman I follow on Instagram, and for the life of me, I can't remember the name. I'll send it out and maybe I'll put it on the link. This is coming up in all different types of professions, right? It's not just HR that's worried about this. It's like, how are entry-level accountants going to be developed? How are entry-level software developers? Like, I have definitely observed, I pulled this data a wee while ago, and I can see a decline in entry-level and graduate opportunities.

Helena | GoFIGR • 51:03

And it coincides with the launch of ChatGPT, right? Might be a coincidence, but I can see the decline in entry-level roles. And this woman said a phrase that I hadn't heard before, but it will make sense. It's, don't eat your seed corn or corn seed. I can't remember which way around it is. So if you eat the corn for next year's crop, you'll be full today, but you'll starve next year. And I think that's a really good way of thinking about that for entry-level roles, is that if we kind of automate the life out of everything that we would give our entry-level people the chance to grow, we'll starve next year.

Helena | GoFIGR • 51:38

So I'm starting to see anecdotes of companies, like IBM, they tripled their entry-level. grad intakes after making a big announcement about all of the back office roles that they'd automated because of AI, because they can see that AI right now, you know, isn't capable of taking on whole jobs. And so I'm starting to see companies preserve tasks from automation to make sure that there is fodder for people to learn from, let's say. So I think we are going to have to be strategic and deliberate and step in to make sure that some of those entry-level career pathways are protected because it… might be cool now to cut your grad intake or your entry level, but you can see it in professional services, grad intakes kind of down by 25%, but it's a bit short-sighted because you'll have no future leadership pipeline, you'll have no intellectual property. And the other thing I think about this as well, and it was sort of covered in some of the other questions, which is about culture. If we're all building off, I don't know, 10, 15 foundational models, like we're using Claude or Anthropic Suite or we're using the OpenAI Suite, we're gonna be bloody beige. We're just gonna be one of 12 flavors of company because we're all gonna be using one of like 10 or 12 models. And it's only our people that will make us interesting and different when everything's automated and we're all beige and the same.

Helena | GoFIGR • 53:07

So there's my, I'll get off my soapbox now.

Kimberly Burns • 53:10

There's your TED talk. I completely agree with that though. Like we're already seeing, I don't know if you're already seeing a lot of the AI slop that comes out now in terms of content and communications. It's very similar. So what is gonna differentiate businesses in the future? It's their people. How do we need to invest in them?

Kimberly Burns • 53:29

That's a big part of what we can do in HR as we move forward. So that was one theme. The other one that came was like, how do we use AI safely and responsibly in HR? And this is, I think a really, really important conversation that we should be having. And it's where we kind of move forward or we stay stuck in that, I don't know how to use AI safely. And the one thing that I think you would be the same, Helena, in what we're seeing and what the data is showing that, you know, AI should not replace HR judgment. it should support, it should support it.

Kimberly Burns • 54:12

You know, how do we use AI to support the decisions that we need to make? You know, how do we keep the decisions human? How do we make sure accountability stays human? And where we look at AI adding value is around the structure, the drafting, the summarizing. That's what I think is really important is first working out like, what are those key things that AI is not gonna touch? And then what can it touch? And how do I make sure those things that they are touching are used, you know, are safe, are guard railed, are specific.

Kimberly Burns • 54:46

And again, you know, not a plug for Mak, but that is exactly kind of why we built Mak because the large general models are risky to use in HR. They are, they don't understand the context, the legislation, and that causes, you know, risk for us and the organizations we work for.

Helena | GoFIGR • 55:08

Yeah, they're convincing, they're very convincing in their answers, aren't they?

Kimberly Burns • 55:11

Oh, they're so confident. I don't know if anyone saw, I did something with Claude the other day. Swear to God, I asked Claude to look at the Fair Work Act, answer this really kind of specific question around casual conversions and redundancies. And I said, look at the Fair Work Act to answer this question. And it came back and it was super confident and we went back and forth and built this whole plan and all of this stuff. And before I kind of like took the work off Claude, I wrote, are you sure this is correct? Because we like to test Claude, we like to test them all against Mak.

Kimberly Burns • 55:48

And Claude Detset went, I'm sorry, the answer I've given you is wrong. I didn't look at the Fair Work Act. This is actually the answer and it was completely the opposite. I got off and I think I called Kareen and I screenshotted it and I posted on LinkedIn because I'm like, this is why we built Mak and this is why it exists. Because even me who uses multiple models got sucked in with the confidence and I'm like, it sounds right, that makes sense. So yeah, that was just a use case of that.

Kimberly Burns • 56:22

I know we've got a lot of people that have to jump off now. Go if you need to go. Go if you need to go. Again, we can probably stay on for another 15 minutes, I think, answering questions. But I really enjoyed it. I was super nervous at the start, but that was actually really fun. Andrea, I think you raised your hand to have a question or high five us.

Andrea Kirby • 56:51

I would like to just draw your attention to the question from Jay Leibowitz around, based on the changes that you have mapped, do you see HR roles being less specialised and the business will try and collapse the HR function into one role, which is currently happening a bit. And as a TA person, I truly believe TA and talent management should be merged immediately. So are you seeing this and do you think we will become less specialised?

Helena | GoFIGR • 57:29

God, I don't know. I think it's possible.

Kimberly Burns • 57:35

I think based on what the data is showing and where we're sitting, is that we genuinely don't know yet. I think we're going to see roles get squeezed. Like we are already seeing reduction in HR headcount. So I think that the one thing I think that I can probably confidently say from what we're seeing in organisations and within our community is that organisations are reducing the number of HR due to the AI, you know, the ability to use AI. But whether that swings us to becoming more generalised or actually more specialised, I think it's yet to see. And I think, again, that comes down to what part of the conversation we in HR want to have about that and leading that.

Andrea Kirby • 58:24

Do you think it would also split into the compliance work, the conflict resolution stuff, and then the happy, shiny people stuff into two different skill sets?

Kimberly Burns • 58:38

I mean, they probably sit in two different skill sets right now, but they're just merged into the same job or task list for people. What I love about this time of work is going back to those tasks and instead of thinking about, you know, the future in terms of roles and is a HRBP role going to exist in five years time, it's breaking it down into those tasks that the current HRBPs do and then go, what are they keeping? What is, you know, it's what is still going to be human? What is automated? What is lead? And then what does that look like? Like what comes out of that?

Kimberly Burns •

So perhaps the conversation is. less about what the roles of HR is going to be in the future, but more about tasks.

Helena | GoFIGR •

Can I just put an awesome comment in about HR has the largest problem to solve over the last 12, the next 12 months around culture, role design, AI, human workforce design, because it's not just you, you're not having to do it for your own team, you're having to do it for the whole business. And I agree that the next like 12, I think two years, we're not going to, this is not like a two second job, right? I think there's an, it's such a cool time to be in HR right now. I think it's, it's like an awesome season, because we're all kind of looking at each other and going, what are you doing? Everyone's like, what are you doing? Like this, this whole redundancy thing, it's a bit of vibes, right? Someone sees the share price goes up, and they're like, well, maybe we should do that. So why can't someone in HR, you know, set the tone and like, set the vibe, if that makes sense, and be the first to do something cool that we all copy, because that's what we want at the moment is we want a blueprint or a roadmap or a best practice, we love a best practice in HR, don't we? We want best practice, that someone else has sort of done it, they've taken all the risk, and then we can safely follow in like, you know, 12 to 18 months time. But I think it's a super cool time to be in this space. Here's the problem is you're herding cats because you can't just do it.

Kimberly Burns •

Exactly. But I think that's a really nice place to kind of wrap it up. I mean, I think we could all just spend forever talking about this. But thank you, everyone, for coming. Thank you to my co-presenter, Helena, and what you've built with the AI Impact Assessment. I'm just, yeah, a huge fan of. So always happy to support you, and that was just such a fantastic conversation.

Helena | GoFIGR •

Thanks so much. Thanks for doing this with me. And thanks for staying on with the whole Crew.

Helena | GoFIGR •

All right, Kim, for the purposes of the recording, I'm going to say thanks so much to everyone for joining us. Looking forward to the next session. Connect with us on LinkedIn, scan all our QR codes. Thanks so much for joining us.

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