Reejig's Siobhan Savage on Using AI for Workforce Intelligence

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[00:00:30] Welcome to PeopleTech, the podcast of WorkforceAI.News. I'm Mark Pfeffer.

[00:00:46] My guest today is Siobhan Savage, the CEO of Regec. They're a talent intelligence platform that works with companies who want to transform themselves in order to address the fundamental changes that are taking place in business and in work. We're going to talk about how the company looks at the workforce and analyzes it, as well as get her thoughts on how work is evolving in this age of AI. All on this edition of PeopleTech. Hi, Siobhan.

[00:01:17] You recently put together a workplace reinvention blueprint. And I wondered if you could tell me about that. What is it and what's the point? We are, as a world, as a society, hurtling towards AI at a pace that we've never seen before. So we're about to enter or already are in this once in a generation change to work.

[00:01:43] And although that sounds really great and exciting, most folks actually don't know what that means, how they're going to get there, what the impacts of that will be, and how they think about their workforce in that context. So a lot of, you know, Regec is, we have one of the large, we have the largest set of data in the world. Think of us like the universal language of work. And we have access to insights and intelligence that no one else has in work.

[00:02:10] And we feel a responsibility to make sure that we're preparing and helping the community rise to understand what will the workforce look like in the future when it comes to AI? What will that mean in terms of the impacts to our workforce, whether that's at an opportunity level, looking at waste, looking at that potential. But then if we make those changes, what does that mean for our people? And how do we think about making sure that as a society and as leaders that we don't leave folks behind?

[00:02:38] So this blueprint is all about, you know, we've got 23 different industry ontologies that are based on understanding every role, every task, every skill. And what we're basically saying is that based on AI and the maturity of AI today and where we're going, this is likely what your industry is going to look like so that you can then take action and make sure that you're reskilling your people, you're pivoting them, and you're taking advantage of this once in a generation change to work.

[00:03:06] So you're kind of predicting what the world is going to look like in X number of years and then recommending to people how they can prepare for that and what they have to do with their workforce about that. So we're looking at it in the context of the maturity of the technology today, which will see us go out to about a two year ahead of us cycle. Because when you think right now, we're not at full autonomous agent, but we're going to go there. But right now, we're looking at the task and the subtask of where the AI agents are able to deploy into subtasks.

[00:03:35] And what we're essentially saying is this today timestamp, we've got a period of about two plus years, not much more, where we'll see whether you're an advanced pioneering company or you're one of the laggers, we will expect to see customers now start to use AI for these use cases. And here is the opportunity, but also here is your moment to be responsible and pivot folks into other work or look at reskilling efforts.

[00:04:00] So it's very much so this based on the maturity of technology today and where we believe the world will go. And also, it's kind of like a compass for not only AI leaders, but like the chief people officer for the CEO to actually think about, you know, you've got this opportunity to bring in AI. Where is the best place to do it? Like what has the most opportunity? You know, how do we free our people up to do the most meaningful work?

[00:04:25] How do we take those tasks that no one loves to do that cost us a lot of money, causes a load of pain? How do we look at focusing our energy into the areas that we know have the best bang for buck? And if we do that, what does that look like in terms of the careers for our people? Like what does that look like? Are we going to impact them? Is there some impact? Is there a full impact? Is there a pivot? The data is really like a guideline to help folks start that conversation in terms of boldly reinventing their company, but being super responsible at the same time.

[00:04:56] Are you finding that executives want this kind of guidance or are you having to do a lot of selling about the value of it? We have never grown as fast in our life. So as a company, we like, I mean, most companies and most CEOs, if you, one of the pieces of, one of the agents that we've built in our team is we have an agent that basically takes all of the earnings reports. And it looks at like, what is all the CEOs saying to their shareholders?

[00:05:26] And what's the research agent actually saying? And what we have seen across the board, Mark, is operational efficiency, cost effectiveness, velocity, productivity, AI, all keywords. Not in a little bit. I mean, over and over and over and over and over and over and over and over every single industry. So the top companies of the world are all on this path. So if their CEOs are committing this to their shareholders, then you know it's going to roll down into their teams at some point.

[00:05:53] So we are not having to do a lot of education. What we are having to do is help guide. So everyone knows they want to do it. But the status quo kicks in and they don't know where to go and where's the best place. Because, you know, having an understanding of the work in your business is the most critical part. So that you can then think about what task will I automate? Where is the most effective? You know, automating a task that you do for five minutes once a week. Waste of time, waste of money.

[00:06:22] Automating something that is 60% of your day-to-day job in terms of replying to tickets in a support desk. Very well worth it. Not only does the customer get better response rates, the quality goes up. But also you see that, you know, I can either top that person up to do more of that same work. Or you can think about re-engineering that job to start taking on other work that would typically never have went there before. So customers are there. Now, if I'm being really transparent, the CEO is there.

[00:06:51] Where we're seeing a blocker is within the chief people officer team and in the HR team. I think some folks think that this is two, three years away. But actually it's happening. And what we need to make sure is that as a collective community, we're helping those folks understand. Because they're not naturally technical. But either am I. I'm a workforce strategist. My career previous to this was in HR.

[00:07:11] So how do we translate something that is super technical into a way that it makes sense for folks in the people team so that when AI is being brought into their organizations, that they're thinking about it in the context of AI being a worker. You know, you'll have this new workforce DNA that will be your employees. You'll have your flex workers. And then you're going to have your digital workers. And what does that new structure look like? And then what does it look like in terms of, you know, designing and work design?

[00:07:38] Because that's like org design and work design becomes a very different world when you're starting to take the little Jenga pieces and break them down in terms of tasks and rebuilding rules. And then what does it mean for reskilling? Most folks in the learning teams have always kind of guessed around what they think the future jobs will look like in critical pathways with not a real amount of data. No, they're needing data to actually go, what rules won't exist in our company anymore? Where do we need to pivot?

[00:08:05] What will be the future critical rules based on where we're deploying AI today and where we're going to be? So this is where I do spend a lot of time educating. You know, it's more in the HR world, whereas at the business level, the CFO, the COO, the COO, they're doing this. They're already deploying. You know, most customers that we're seeing have already started their journey towards agent builder with co-pilot, you know, with other different providers.

[00:08:29] And it's just a matter of them knowing where to focus their attention, where, you know, you've got so many tasks in a massive business that can be automated. How do you think about where is the best place for business value to go first? So that's really where we start them on their journey is let's help you redesign your workforce, help you think about it in a different way. And then we'll make you AI recommendations of like what AI you can actually use to do those tasks.

[00:08:54] And then we're looking at, OK, if you may make these changes when it comes to the AI recommendation, what is the actual change in that role? And it doesn't just happen once. Like if you imagine you're going to constantly keep taking tasks out of these jobs, there's a reengineering of work, which is going to be the biggest thing we've ever seen in the HR space. Because to keep up with that, that's we've never done that before. So I think a lot of folks are starting to try and get their heads around. Hold on. We're not just redesigning this thing once.

[00:09:23] It's like they're always going to keep taking more tasks out of these roles. How do we keep our job architecture up to date? How do we think about knowing how to recruit? The whole thing is going to completely break down in the way that we used to do it and in this new world. ServiceNow unterstützt Ihre Business Transformation mit der KI-Plattform. Alle reden über KI, aber die KI ist nur so leistungsfähig wie die Plattform, auf der sie aufbaut. Lassen Sie die KI arbeiten, für alle.

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[00:10:15] On Spilling the Tea on HR Tech, we uncover the latest trends, truths and challenges from Sapien Insight Group's groundbreaking research and our analyst insights, sugering up everything you need to know about HR Tech with no sugarcoating. And on HR, we have a problem. We tackle the toughest workplace challenges head-on, offering you expert advice and actionable solutions to help HR leaders thrive in today's fast-changing world.

[00:10:45] Whether you want the scoop on tech or tools to solve people problems, we've got you covered. Take a listen and subscribe. If you want to become part of our community, we'd love to see you. It's interesting that you said that the C-level folks are ahead of the HR and people, you know, talent folks in terms of when they think this is all going to happen. Why the disconnect?

[00:11:14] I mean, in a lot of ways, I would expect it to be reversed, where the HR leaders would think it was imminent and the CEO might not. I think it's a combination of things. I think, one, the CEO has pressure that probably they've never had before in terms of, you know, operational efficiency, productivity, and that they're searching out how to solve and keep their business stable through this kind of economic up and down, right, that we've been going through over the last few years.

[00:11:41] So I think, you know, they are responsible for productivity shareholder return. That essentially is the CEO's job is to make sure that they do a good job for that. So I think CEOs are actively trying to solve for that. And AI and the time that it's coming through, it couldn't have come through at a much better time when you think about where we were when it launched. You know, we were post-COVID.

[00:12:03] We were all feeling, you know, you would have seen the biggest news cycles that were coming out about the lowest productivity in history and a lot of those kind of scary headlines to shareholders. So I think a lot of CEOs have a lot of pressure on them to do more with less, to remove workforce bloat, to win, to be more competitive. They're also super paranoid about a lot of companies like us, smaller, more fat, like faster companies, AI part first.

[00:12:32] Like we are a terrifying thing to a big company if we're competing because you can just move faster, right? So I think that's one part. I, on the HR side, like I want to be positive and say that, oh, you know, like it's great. It's not like it's, it's not the maturity level. And I don't know if it's because there's not enough education to that, that, that, that kind of cohort of, and that community of folks.

[00:12:59] I don't know if it's HR people are so busy that they don't get time to reskill themselves because they're caring for everybody else. Or I don't know if it's a, oh, this is another hype cycle. Let's just wait that one on. I don't know. But what I am seeing is the HR teams getting moved out of the way and the businesses are going off and doing it without them. And the concern I have with that, Mark, is if you're going out and reinventing your company and looking at AI and not thinking about the people impact, you're going to be on the wrong side of history on this one.

[00:13:29] You need to be bold and responsible and make sure that you're absolutely, you know, reinventing your company and bringing in AI. But if you're going to let a whole, you know, impact a lot of people, and we're talking big companies, big responsibilities, you know, maybe the only job in town in rural communities of America, you know, you have a social responsibility and an individual responsibility to people to make sure that you don't leave them behind.

[00:13:53] So what I'm trying to do is push the HR community to kind of get with this pretty fast so that they are able to come to the table on this and offer like a real bold and responsible way of thinking so that they're partnering up with the business on it. All of our customers, we have either it's come from the business and we've looked in the HR or we've seen these awesome HR folks who can see it coming. And then they're saying, what do we do with this? And then they're bringing the data to the AI teams to say, hey, we've got all the work.

[00:14:23] We own all the jobs in the company. We've got this new way of thinking about our job architecture. We can tell you where the AI has, like, let's work together on this. So that's where we're seeing the best partnership happen. But we're not there. We have a lot of work to do as an industry. You as a thought leader, all of us have this responsibility now to help this community rise and learn, like, this is happening today. It's not coming in the next two years. Now, you mentioned digital workers.

[00:14:51] And I wondered if you could talk more about them. You know, what are they and what's the point of them? Yeah. So a digital worker in the context of what I'm going to describe is pretty simple. I'm not going to get into technical jargon. But what I'm going to describe is you'll have a digital worker that can do specific subtasks in a process or in a role.

[00:15:15] So, like, that researcher I just explained takes a little bit of something that I would have paid someone to do that would have taken them a long time to go and download all the reports, pull them all together, export the information, then analyze it, and then give me digestible action-taking insights. That would take a full-time person for me, typically to do that kind of thing, and then to keep it up to date every time the reports launch. So that is, like, really a task-based agent that's operating based on, like, clear actions.

[00:15:45] And then you have where we're going to go soon, which is this autonomous agent. And this is where the agent will pick up an email that you have sent to a travel agent. It will take your ask and your request. It'll go off and research. It'll go find, I know everything about you, Mark. I know all of your previous history of all the holidays that you've booked with your family before. I know that you like these types of things. I'm going to make some kind of recommendations. It comes back.

[00:16:13] It says to you, hey, Mark, based on who you are, here's some recommendations. You then say, I pick option two. It goes off and books the flight. It comes back and gets you your ticket. So it's the end-to-end process it takes, that autonomous. And then you've got the third level of worker, which is your digital factories. So think about big organizations that operate with huge machinery lines.

[00:16:38] They operate, you know, we're going to see robotics a lot more now there, where we're not just talking about genitive AI. And everyone's very focused on gen AI right now. And what we're starting to see, especially in the U.S., is this thought and thinking that it's not just gen AI. It's starting to look at robotics, like actual factory workers becoming robotic task-based in their process and ways of working. So they are typically the ones that I am seeing.

[00:17:04] There's lots of other ways of describing RPAs and everything else, but they are the three kind of levels of what we see that are technically replacing the work that humans have been doing in today's world. And I think whether or not people agree, disagree on that as a we shouldn't be doing it, we should be doing it, that's irrelevant. It's happening.

[00:17:26] And it's happening because not only is it happening in a transformation team going out and building these, but actually the way that these co-pilot studios, it democratizes access for you, the employee, to build your own agent. You know, the sales forces of the world, you know, the Microsoft of the world, they're all building agents that any employee can actually build their own agent to, to help them with their day job. So it's not just one team in IT now is deploying these. This is happening across the business where people can also build theirs too.

[00:17:58] Now, you concentrate on, I think, 23 industries, or at least that's what you folks talk about. And they range from aged care, you know, elderly care, to technology, to government. And I'm wondering what do all of these have in common that, you know, your solution can apply?

[00:18:22] So there is, you know, like a similar procurement, finance, HR, administration, those lawyers, accountants, finance. Every company has a corporate services, right? Like all of these companies will have some, and they're all typically desk workers. And they are typically the rules that have the most opportunity for automation in terms of generative AI because it's all knowledge work.

[00:18:49] So we see across the board that when folks started to think about AI, they would look at whether they were in those industries, same industry or different. They started internally because it's usually led from the AI teams thinking about, oh, let's look at our software engineers. Let's look at our product managers and see, like, is there stuff to play?

[00:19:09] But then it quickly turned to there's way more opportunity for us to reinvent in ways that haven't traditionally been reinvented that much, which includes your corporate services. And corporate services are typically an overhead. They don't make money, right? So the leaner that you can make your corporate service, the more that is less of a cost. So we do see that across all of these different industries, that that is kind of a consistent.

[00:19:37] The other consistent thing that we're seeing is that there is this opportunity for no matter what industry for the story to be quite changed, that it's not about the fear of losing your job. It's actually the moment where we're teaching a lot of customers that this is a moment for you to amplify your employees, like to let them know that AI can actually free them up to do more meaningful work that can, you know, actually reduce job risk.

[00:20:04] So there's this theme that we're seeing pop up across customers where, like, if people don't adopt the AI, then none of this will work very well, really, because you need people to actually do the things we want them to do for now, right? While it's in this in this embassy. But there's this theme that's popping up in every industry where it's like, how do I bring this to our people?

[00:20:27] And so it's not a technical shift in terms of the tasks that are being reduced, but it's the same cultural opportunity really down to how they communicate and change manage AI within their organization and how they do their corporate comms. Like, they're all starting to think about, like, how do we think about that in the context of bringing our employee on the journey?

[00:20:48] So we typically see those industries are we built 23 industries because a nurse is very different from a accountant versus an accountant in certain areas. Like in a consulting firm would require a little bit different tasks and expertise versus an accounting person in a corporate function. So, you know, you've got different levels of roles within each industry. So, you know, we do need this different industry and this one language of work so that we can give good intelligence.

[00:21:14] But there is a probably 30 percent kind of across the board that's quite similar that can be used. I mean, HR is a perfect example, right? Like we're not all that different whether I work in FMCG or whether I'm in technology. HR BP is quite similar in all of them. It's an interesting area to focus in. You know, it's an interesting solution. How did you start to pursue this? I mean, why did you drop into this area or get into this area?

[00:21:43] So my expertise in my first career was very much so in workforce optimization. So I was responsible for allocating resources around a large global engineering firm. And so I care about work, getting to the right worker at the right time. And we started our journey very much so focused on the skills component, because at that time, you know, people in my mind, people had skills and jobs had skills. But what we find was jobs do not have skills.

[00:22:11] They have tasks that require skills. So in order for us to make work recommendations to your workforce, for us to think about career pathways, for us to have this data, we needed to understand a deeper level of the work that's actually being done. So pre, you know, large language models, the chat GPT era moment that that kicked off. We were really focused on I need to understand the work of an organization so I can match it, whether it's in succession planning, projects, gigs, career pathing.

[00:22:39] In order for you to do a really good recommendation for the company, you need to understand what the actual work is that they're going to be doing and who the worker is. So we started there. And then as, you know, this whole kind of AI moment happened, I'm very, like, savvy and technical in the sense of I'm up for trying stuff. And I can, you know, I can try whatever I want in my own company without getting told off compared to a corporate. So we very much so, like, wanted to test to see if this thing was real.

[00:23:06] Like, has this got the potential to truly do the thing that it says? And it does, because we're now saving over $1.7 million a month in my team alone, by the use of AI and changing things. And that isn't even sophisticated yet in terms of where we will get to. We will build a billion dollar company with 100 people because we will be AI first. And I think this is where a lot of folks seen what I was doing.

[00:23:33] And then the corporate kind of caught up, the corporate started to catch up. And then we started getting a lot of calls and me getting brought to a lot of sessions to talk to folks to really go through. Here is how to think about it. And you need the data. Like, I wouldn't have been able to do this without, like, even in a small company like mine, I wouldn't have understood what was all the work that was happening in my team. Never mind you working in a big corporate. So that was really where it started.

[00:23:57] And, you know, this is probably the we're just at the kind of the tip of the of the of the rocket taken off now, because we've hit like right into a really critical moment where organizations do want to boldly reinvent and they're expected to. But also most companies are good. They want to do good by their people. So they're very motivated to make sure that when they're boldly reinventing, that they're not leaving people behind. And that's really important to us in terms of our mission. Well, you know, it's it's it's fascinating.

[00:24:27] It really is. And I appreciate your coming by today. And I hope you'll come back so we can talk about it some more. Thanks, Mark. Bye. My guest today has been Shobhan Savage, the CEO of Reject. And this has been People Tech, the podcast of WorkforceAI.news.

[00:24:56] We're a part of the Work Defined Podcast Network. Find them at www.wrkdefined.com. And to keep up with AI technology and HR, subscribe to Workforce AI today. We're the most trusted source of news in the HR tech industry. Find us at www.workforceai.news. I'm Mark Pfeffer.