Leading in the agentic era-rethinking talent, skills, and workforce strategy

The webcast, originally aired during HR.com’s Future of Career Development & Mobility virtual conference, discussed the evolution and impact of agentic AI on talent, skills, and workforce strategy. Conor Volpe and Jaclyn Zhuang highlighted Eightfold’s decade-long experience in AI solutions, emphasizing agentic AI’s ability to operate semi-autonomously and enhance productivity. They detailed how agentic AI is transforming HR workflows, including talent acquisition, management, and workforce planning. Examples included AI interviewers improving candidate experience and career coach agents providing personalized career guidance. The discussion also addressed the balance between AI efficiency and preserving human skills, stressing the importance of human oversight and decision-making in AI-driven processes.

Introduction and overview of the webinar

• Matt welcomes everyone to the webcast titled “Leading in the Agentic Era: Rethinking Talent, Skills, and Workforce Strategy,” sponsored by Eightfold.
• Matt instructs attendees to use the Q&A tab for questions and to complete the webcast survey for HRCI and SHRM credits.
• Conor Volpe introduces himself as part of the product marketing team at Eightfold, covering talent acquisition and management products.
• Jaclyn Zhuang, VP of Product at Eightfold, introduces herself and highlights the company’s unique perspective as an AI solution provider, agentic vendor, and employer undergoing transformation.

Evolution of AI and agentic AI

• Conor Volpe explains Eightfold’s decade-long experience with AI solutions, including upskilling, career pathing, and candidate matching.
• Jaclyn Zhuang elaborates on the evolution of AI from automation to deep learning and generative AI, emphasizing the role of agents in the agentic era.
• The discussion highlights the difference between traditional AI and agentic AI, with the latter operating semi-autonomously and making decisions without human intervention.
• Jaclyn Zhuang and Conor Volpe discuss the dual emotions of excitement and anxiety surrounding agentic AI and its impact on work and talent.

Impact of agentic AI on work and talent

• Jaclyn Zhuang discusses the positive impact of agentic AI on productivity, efficiency, and employee support, emphasizing the importance of balancing AI’s capabilities with human judgment.
• Conor Volpe and Jaclyn Zhuang address concerns about job security and the need for employees to adapt and learn new skills to thrive in the agentic era.
• The conversation touches on the importance of transparency, trust, and change management in the adoption of agentic AI.
• Jaclyn Zhuang shares insights from customer experiences and the role of leaders in guiding employees through the transition.

Challenges and opportunities in adopting agentic AI

• Jaclyn Zhuang highlights the challenges leaders face in adopting agentic AI, including maintaining employee engagement and trust.
• The discussion emphasizes the need for clear communication, training, and support to help employees adapt to new technologies.
• Conor Volpe and Jaclyn Zhuang discuss the importance of addressing employee fears and concerns about job security and the impact of AI on their roles.
• The conversation explores the potential for agentic AI to enhance employee skills and career development, creating a more agile and adaptable workforce.

Practical applications of agentic AI in HR

• Jaclyn Zhuang provides examples of how agentic AI is transforming HR workflows, including talent acquisition, talent management, and workforce planning.
• The discussion highlights the role of agents in automating repetitive tasks, freeing up time for employees to focus on strategic and innovative work.
• Conor Volpe and Jaclyn Zhuang discuss the impact of agentic AI on employee engagement and the importance of maintaining a human touch in HR processes.
• The conversation explores the potential for agentic AI to improve candidate experience and increase efficiency in recruitment processes.

The future of work with agentic AI

• Jaclyn Zhuang envisions a future where agents handle repetitive tasks, allowing employees to focus on creative and strategic work.
• The discussion emphasizes the importance of human judgment and decision-making in the adoption of agentic AI.
• Conor Volpe and Jaclyn Zhuang explore the potential for agentic AI to enhance collaboration, innovation, and employee growth.
• The conversation concludes with a focus on the need for transparency, choice, and continuous learning to ensure a successful transition to the agentic era.

HR.com Moderator 0:00

Matt, welcome everyone. Thank you for joining us for this webcast, “Leading in the Agentic Era: Rethinking Talent Skills and Workforce Strategy.” It is now my pleasure to turn it over to Eightfold for their presentation.

Conor Volpe 0:38

Awesome. Thank you very much, and hello everybody. Welcome to today’s webinar. We’re very much looking forward to getting to this topic with all of you. It’s something that is very near and dear to our hearts at Eightfold, and I’ll explain a little bit about why that is coming up. But before we get into the actual webinar itself, I just want to say thank you for spending some time with us today. We know carving an hour out of anybody’s schedule is big, so we appreciate you spending that time with us, and hopefully, this is a topic that you enjoy as much as we enjoy talking about it.

Now, first, in terms of who we are: I’m Conor Volpe. I’m on the Product Marketing team here at Eightfold AI, covering our whole suite of products from the agents that we build through to our products like Talent Acquisition and Talent Management. And I’m joined by one of our product leaders, Jaclyn. Jaclyn, would you like to introduce yourself to everybody?

Jaclyn Zhuang 1:35

Yes. Hey, everyone. Jaclyn Zhuang, VP of Product, leading our efforts and solutions around Talent Management and Resource Management. Very happy to be here with everybody today talking about my favorite topic, which I’m sure is top of mind for everyone too.

Conor Volpe 1:53

And I mentioned that this is something that we’re looking forward to talking about, something we enjoy talking about, and a lot of is because we have a relatively distinct perspective from Eightfold. I’ll explain what I mean by that. And there are three different parts of this perspective.

The first of which is: we’re an AI solution provider and have been for almost a decade. So we have spent almost 10 years helping our customers adopt, appreciate, and see value from AI solutions for talent. And that’s everything from helping employees find upskilling and career pathing to helping candidates find the right jobs, and helping recruiters understand candidates. We’ve helped bring our customers along in this journey for 10 years. So this topic of AI transformation is not new to us, and it’s something that we’re pretty passionate about.

But then also, the second part of this is we’re an agentic vendor too. Just at the same time as we’re bringing AI solutions to market, we’re bringing agents to market for our customers to help them transform in this new Agentic Era.

And the last part of it is: we’re an employer. We’re a company that is undergoing this transformation, just like many of our customers. The agents that we build, we’re using them ourselves. We’re trying to figure out the new kind of AI tools, processes, and systems that we can bring in to make ourselves more productive as well. So this is something that we see as inevitable for Eightfold. I’m sure for many of you, you’re trying to figure out how to fully embrace this AI and Agentic Era. So it’s something that we’re going through. And like I said, this is why we’re excited to talk about the six [perspectives] we have. We see it from all different perspectives.

But before we get into today’s session—or the meat of it, rather, where Jaclyn and I will be going back and forth on a variety of topics that we see as really important to get into when we think about this type of transformation of work and talent and how agents fit in—we want to spend at least a moment defining what we mean by Agentic AI, and maybe even AI as a whole. Because that two-letter acronym, AI, has been used in all manner of different ways. And we just want to try to be a little bit clear about what we mean by the different flavors of AI, and particularly around Agentic AI.

So this is an evolution of AI from the earliest phases all the way through to what we are seeing today. And we’ve done this for HR, but you can do this for a variety of industries, or even just AI in general. But really, AI started—or rather started all the way back—with automation. And the simplest form of automation you can think about is attaching a plow to the back of livestock to help us till fields, right? Automation is about reducing humans’ manual effort or intervention in a process. Now, of course, the very first software did this right, and we can think about this as simple workflows and software to help people just kind of move through a process. That can be a form of automation.

And from there came more traditional AI. And we can think about this as “if a certain thing happens, then take that action.” These can be really helpful to speed up simple processes. And you can see the example of automated keyword screening on a resume: if somebody has a specific word or a specific skill or a specific experience, then an action is taken by a system or is recommended to be taken by a person.

But that really took off with the introduction of Machine Learning, where these AI systems could learn from past data or patterns to help make their insights stronger, more accurate, actionable, and more insightful. And that was a huge step forward.

And then another step forward in the learning game came with Deep Learning, where it was less about structured data and more about unstructured data. So you can imagine trying to understand something as nuanced as employee feedback and providing real, actionable insights out of that. It takes a pretty advanced system to be able to understand the sentiment of employees in that feedback and turn that into something that HR can use. Around the same time, Skills Intelligence came to bear, and kind of like what we ended up using deep learning for, Skills Intelligence was about understanding our employees and candidates so we can better see where they might fit in an organization, what they’re capable of today, and what they’re capable of tomorrow. And skills was part of that journey for companies.

But I mentioned we’ve seen AI used in all manner of different ways, or that phrase, that two-letter acronym, used in all manner of different ways. And largely that’s come in news, in our social media feeds, and that really took off with Generative AI. And what I mean by that is the LLMs like ChatGPT, Gemini, Claude, Grok—these came to bear in the last few years and really changed the game because they allowed all of us as people, not just as employees or administrators of software or people who work in software, but someone who can just log in to ChatGPT and see the power of AI right here on my desktop or in my phone. To do everything from helping with personal finance, to doing research, to helping plan my next vacation. I think everybody started to really understand the potential power of AI through these generative AI tools because they were accessible by all of us.

And as that kind of accelerated everything to do with AI, so too has Agentic. And that’s what we really want to talk about here today. Because why Agentic AI is different than everything else we see on the screen is that every other form of AI required a human to prompt. Like with an LLM, it requires you to ask it something, to program, to give it a decision to be made. With Agentic AI, part of the point is that these agents can operate at least semi-autonomously. They can make some decisions without a human having to okay each and every step. So we think about the promise of automation all the way back on the left-hand side of the slide, which is just to reduce human intervention and manual effort; agents are the biggest accelerants of that promise that we’ve seen to this point, and that can be really exciting. But there are also some questions about how that impacts the work and the workforce and talent, and how we see all of this coming together.

So just again, want to level set on some of these terms, what we mean by Agentic AI. But Jaclyn, I want to ask you, first of all, is there anything else you want to add to some of these definitions to help people kind of understand what we mean by Agentic AI and AI? But then I also have a question for you of just like, how is this different than the tools you might already be familiar with today in terms of AI tools?

Jaclyn Zhuang 8:06

Yeah, first off, I think there was a really great explanation of this evolution of AI. I think the only thing I might want to add is just the difference. So you know, with all the things earlier—with automation, traditional AI, machine learning—the tools that you use, you go to when you’re thinking about solving that particular task. With what we’re seeing in terms of Agentic AI and AI agents now, it’s almost like an always-on companion, predicting your needs, nudging you, pushing you, alerting you to things. So there’s a difference. Rather than you going to technology, what we’re seeing is more technology helping you and being an assistant and working alongside you.

Conor Volpe 8:48

I think that’s really important because one of the phrases that people use in relation to Agentic is almost like a “digital employee,” right? I think that what you’re getting at there is a reason why people use that phrase. It’s working right alongside you. Or can also, again, help extend your value, extend your productivity, because it is able to do some of these things on your behalf. Absolutely. But anything else you want to add about how it’s different than some of these other forms of AI that have come before?

Jaclyn Zhuang 9:18

Yeah, I think this slide tells it all. Like automation is: “if this happens, if there is a trigger that something should happen, take this action.” Very, very rules-based. Agentic is different in understanding the situation, understanding the system, and autonomously making those decisions and taking those actions to achieve goals. So we’ve come quite a long way.

Conor Volpe 9:40

We have, yeah. And the thing I want to start by acknowledging for everybody on the line right now is—I kind of alluded to this a little bit—but within the age of Agentic AI, there are probably two emotions that we’re all feeling. And I’m not immune from this either, even as someone who’s really in the weeds with agents all the time. It’s very normal to feel both excitement about the possibilities of Agentic AI, but then also maybe to have a little bit of anxiety about what this means for us as employees and as humans.

And some of this, I mentioned, is driven by some of these breakthroughs, right? So we can see on the left-hand side, some of the breakthroughs that maybe make us go, “Wow, this is incredible.” It’s things like unleashing AI on cancer treatment to help improve outcomes for folks who are battling this illness. Like, that’s an incredible type of breakthrough that is brought by AI and helping us to see, like I said, incredible results. Like, that’s amazing for us as human beings. Or even using AI to help figure out new types of materials that might unlock technologies like quantum computing and times that we didn’t think were possible before having something like AI. Like these are, again, massive breakthroughs that make me go, “This is really powerful.”

At the same time, we also see things in the news cycle like Mark Benioff, the CEO of Salesforce, saying that 50% of the work at—I think Salesforce has roughly 80,000 employees—50% of the work is being done by AI. Or Shopify’s CEO saying that if somebody wants to justify new headcount, you have to prove that this can’t already be done by AI. So the point is, both are happening at the same time, and they’re very reasonable things to feel, like I said, at the same time.

So Jaclyn, again, as someone who is quite literally building agents right now, and who’s obviously very in tune with how this is going, like when you look at the surge of AI and investment in these tools, both by vendors like Eightfold as well as companies like Salesforce and Shopify, what do you see that’s both exciting and then, on the other hand, like anything to call out that might be a little concerning that people want to keep their eye on?

Jaclyn Zhuang 11:50

Yeah, and I think I’m going to answer it not just from the perspective of someone who is building this for others to use, but also someone who is managing this within my team, within Eightfold as well. And I would say, overall, very exciting because we’re really getting those meaningful gains in productivity and opportunity. Like AI is taking care of the busy work, helping us learn faster, really giving our managers better tools to support the teams. That’s fantastic.

I think with the call-out too, right now, there is a tendency to judge AI by how fast it makes things happen, how much money it saves. A lot of the efficiency play there. But I think that’s only part of the story. The real magic happens when leaders look beyond these easy statistics and really think about: how is AI helping people work better together, learn quicker, build confidence, try new ideas? And from what we’ve seen working with our customers, the best ones aren’t just looking at this efficiency piece. They’re also taking into account the creative breakthroughs, the stronger relationships amongst functions, because people are doing what people do best, right? Which is connecting, growing new ideas, while AI is doing what AI does best right now: really understanding pattern recognition, improving efficiency, and speed that way. And really exciting to see companies move in this direction, really balancing those quick wins with deeper, long-term growth.

I think one of the things that I hear quite a bit, though, on the concerning side—just to give the opposite side of things—is, as AI gets very deeply woven into work, a lot of questions have come up, such as: “How much autonomy do I have?” “Where’s the trust in this system?” “Is the system spying on me?” And also a lot of clarity on how decisions get made. Is it the AI making the decision? Is it humans making the decision? How’s that all going to work?

I think overall, that kind of cross-functional collaboration and transparency is super crucial, so employees continue to feel supported and empowered. You know, employee engagement remains high, and they don’t feel like, “Oh, I’m just going to be automated away and left behind.” So opportunity here: huge. But the change management: extremely crucial as well.

Conor Volpe 14:13

And I think you’re getting a bit of this too. But obviously, you’ve been talking, like you mentioned, coming at this from not just a product leader, but also a people leader. And so you’ve been hearing this from customers, our own employees, people that you lead. And again, I think you’re getting a bit of this, but what are some other nuggets you’re hearing from leaders, from employees, about their hopes for agents, their fears or anxiety when it comes to agents? Again, I think you were touching on this a bit, but I’d love to just go a little bit deeper.

Jaclyn Zhuang 14:50

Absolutely. I think for leaders, we’re going through an interesting time right now where everyone’s being asked to do more with the same or lower headcount. Right? So leaders are under pretty immense pressure. They’ve increased goals, and they have to figure out how to make it happen. The “how to make it happen,” especially if you’re asked to maintain or drop headcount, is AI. It’s automation, is technology. So that part is super interesting, how that can be a force multiplier and really help team members be more productive because it just frees up their time to do more valuable work. Super excited about that.

But at the same time, a lot of leaders I speak with are unsure how quickly their teams can adapt. How do we get them “AI fluid”—the using of AI to solve everyday problems? And they’re also afraid about losing trust if people don’t feel included or supported there. Because again, as a leader, you’re under immense pressure. You want employee engagement, your teams to be super engaged so that you can hit your goals. So what’s the right balance of pushing through new technologies to get things going more quickly, but then also understanding that you have to work with your teams to get them feeling supported along the way? So I think that’s on the leaders’, the managers’, side of things.

On the employee side, I think the biggest fear is spoken about quite a bit. People are worried that AI is just going to take their jobs away, or maybe change it so much that they don’t know where they will fit. And I think there’s a real anxiety about this. I’ve spoken to many people who are worried that they can’t thrive; they’re just trying to survive right now with all the different changes that are being pushed down. But at the same time, every single employee I’ve met with as part of our customers really wants to get ahead. It’s not like they’re just sitting there going, “Oh, you know, let’s just have some technology come in.” They truly want to get ahead. They really want the support to do this—so clear training, communication, and just the practical chances and opportunities to add those skills and put into practice while being supported by the company. Super crucial. So I think the companies that do this well really move the employee mindset from “How do I keep my job? What is going on here?” to “How do I take the next step? How do I remain not just relevant, but thrive in this new environment?”

Conor Volpe 17:20

There are a couple of things there that I want to almost double down on a bit. You were mentioning leaders and how many leaders are trying to help their employees adopt, get more out of these tools? And I hope for everybody who is listening, it’s a tale as old as time, right? Like I know that we’re talking about something that can be very different or even more extraordinarily powerful than some of the tools that have come before. But Jaclyn, what you’re mentioning with some of these problems that leaders are facing is still: how do I get my employees to buy into some of the new tools, new processes that we’re implementing? Again, like that part of it isn’t necessarily new, right? It’s just maybe a bit different with, again, the proliferation of a different type of technology. But the core of it has existed and will exist as long as there are companies and managers and employees and all the rest of it.

Jaclyn Zhuang 18:13

I completely agree, and we’ve seen this right over time. Like there was a lot of noise when automation really started landing at factories. Supply chain was being automated. When computers came and landed on everyone’s desks. And so with all these changes, yes, sometimes jobs did disappear, sometimes jobs got redefined, but new roles always showed up, and often ones that needed skills too that people never imagined before.

Conor Volpe 18:43

And you mentioned also, I think at least what I refer to as the elephant in the room, right? Which is: what is this going to do to my job, to other jobs like mine? And you were just kind of touching on that, but I think it’s a really important topic to kind of address head-on because, as you mentioned, there is a lot of anxiety about AI taking jobs. I think the question is—and again, you were getting into this a bit, but I just love you to expand on—how should people think about that? Like, how should people internalize that kind of topic and maybe get past [it] to embrace? Just, what do you think?

Jaclyn Zhuang 19:21

Yeah, I think so. I think it’s the acknowledgement that everyone’s job is going to change. Now, how much is going to change is going to vary from role to role, but no matter what, there are always going to be new skills associated with this change. So the real question is: how quickly can everyone learn these skills, again, not just to remain relevant and survive, but to thrive in this new evolution here? And the people in organizations that figure out the best ways to adapt are the ones that do the best. So, willing to learn new skills, be curious, try the technology, right? And figure out how to use it to shore up your strengths. Being comfortable with that technology is going to be super crucial. And by doing all these things, I think employees—and of course, companies supporting the employees—then set up everyone to come up well through this change.

Conor Volpe 20:23

One of our customers was actually in our office yesterday, and they were kind of answering this very question, right? They were asked by us, “How are you helping your employees embrace this?” And transformation, I know, is used a lot, but for this company, it is a particular transformation, and I thought it was very instructive. But the way they said [it] was, they get a lot of questions from employees of “Will AI, will agents impact my job?” And the answer they have is: “Yes, it’s inevitable. So we’re going to help you.” Right? Like you mentioned, we’re going to help teach you the skills. We’re going to help put a plan or a process in place. They’re not being ambiguous about it. They’re saying it is inevitable that this is going to happen. So we’re taking this head-on. We’re putting people behind this to help redeploy, reskill, relearn for employees as their roles change. They don’t want this to happen to them. They want to make it happen. I thought that was very instructive of a way that, again, a large company that is dealing with this right now and their philosophy about how they’re bringing employees along in the journey.

Jaclyn Zhuang 21:23

I completely agree. Tackle it head-on. Don’t waffle about it, and really let employees know: we’re in it with you, and we’re going to make sure you’re supported. We care about you. We also want you to thrive in this new world.

Conor Volpe 21:42

And let’s talk. We’ve been talking about AI, but specifically with agents. How are you seeing agents actually change the way that work gets done in companies? Right? Because you mentioned too that I think many folks see agents—which is right—as a big productivity boom. But it’s not just productivity. It’s actually changing the way that people work or tasks get completed. So how are you seeing some of that actually change with agents in the mix?

Jaclyn Zhuang 22:08

Yeah, I think, you know, like we talked about just now, sometimes agents do take over certain jobs, especially those that are very repetitive, those that can be done faster, cheaper by technology or a machine. But much more often and more common, they’re really handling the background tasks that bog teams down: scheduling, paperwork, answering simple questions, or even basic sorting through data. And what this does is really allow people to use their time and energy on bigger things—on innovation, being strategic, solving problems, working with clients, with customers—whichever one that can’t really be replaced by AI. Coming up with new ideas, building that connective tissue and relationships at work that really drive and galvanize the company to achieve its goals.

I think one really good example is from Josh Bersin’s Pacesetters Report around the Providence Hospital System. And so what they did was they used AI to automate a ton of admin work, like all the shift scheduling task assignments. And what this meant is: okay, there’s definitely less need for certain support roles, a couple of them, but it really helped free up doctors and nurses to focus on patient care, on boosting morale, on having the whole place run smoother and cheaper. And really, which is the end goal, and which is what we kind of want to expect from hospitals and medical care. So I think this real change is: sometimes agents replace people, but most of the time they change how teams work together and really let people do the kind of things they excel best at, and making sure that they’re supported through it, and taking away all the busy work and the less meaningful work.

Conor Volpe 23:51

The Pacesetters Report is a perfect example because you hit the nail on the head with which roles this particularly impacted, which was doctors and nurses. We as patients, where do we want our doctors and nurses to spend the most time? Patient care. Where do doctors and nurses want to spend most of their time? Patient care. So how do we help them do less of—like you mentioned—logging time spent, taking notes in patient intake or in appointments? How do we help them do less administrative work so they can spend more time doing the work they and we actually want them to do? So that, to me, was a perfect example of the kind of impact that, as we have on the screen, AI can have on jobs that people can do, the parts of their jobs that only they are uniquely qualified to do.

But as you mentioned, too, this does have an impact on how we think about an organization. Right? Like I think on the left, we have what is a pretty traditional, hierarchical organization, how probably most every company that is on the line is roughly structured today. But in a world where certain skills, tasks, roles, projects are completed by an agent or partially completed by an agent, it might force us to rethink the structure of our organizations and how this all actually comes together if we have digital employees working right alongside of us. And I know probably many folks on the line aren’t quite there yet in terms of their transformation, but as you mentioned about our customer who is in the office, their stance is: “This is inevitable. We are going to get there. So we’re going to help everybody get there with us.” But how do you think about, Jaclyn, like, how agents will ultimately reshape a traditional org structure, like the one we have on the screen? I mean, the one on the right, the diamond structure—who knows if that’s what it’ll actually look like? We’re still very early in terms of agents actually getting infused into work with us. How do you see it impacting things like org design or traditional roles?

Jaclyn Zhuang 25:48

Yeah, I think even taking a step before the agents and impact of agents, my personal perspective is that within companies itself, you’re going to see a bit more of a gig economy. And what this means is that people kind of… yeah, they have a job, but that definition of a job starts loosening up, and people will be moving across teams and work and projects and tasks more dynamically because of what they can do, the skills they bring, and the problems that have to be solved, rather than like which part on the org chart that they’re at.

And again, my personal belief is that skills become the currency that connects people to work, and that matching of what you bring to the table—the skills you have—and the work that needs to be done will happen on a more continuous and faster basis, not just doing annual planning or re-orgs. And really there’s a lot of this is in response to what we’re seeing on a macroeconomic side right now, where things are changing so quickly. And then add in what we’re talking about here, which is Agentic AI automation and all as well. But anyway, so that’s my perspective. That’s where I come from when it comes to this org design piece.

I think yes, org charts still exist, but from a leader, from a manager perspective, we’re going to be thinking about not just headcount, but this portfolio of people and agents, and managing it and redeploying it as priorities change. And the questions managers and leaders have to decide on, along with HR, is: which tasks should agents own? Which really need a human? How do we manage this? How do we manage the group of agents that are available in conjunction with it as well? Because agents, ultimately, too, are sort of an IT asset, even if they’re helping humans get the work done. So that’s kind of how I think about the world. This is, again, not today. We see very few companies actually doing this today. But I see this coming pretty rapidly, especially with how fast we’re evolving in Agentic technology.

Conor Volpe 27:59

And again, it’s very fresh of mind—or fresh top of mind, I guess, rather, is the way to think about that—with this customer who was in the office yesterday. But they literally showed a role at their company, and the skills that this role maybe needed in the past, which skills this role will need in the future, and which parts of this job today an agent might be able to help them do. And it wasn’t one or zero, it wasn’t “this whole task or process.” It was 80%, 50%, 20% to show how this role might evolve and which parts of the role this person might not need to focus on anymore, how that impacts the skills this type of role might need. And it was very instructive to see it broken down to that level, and how they’re thinking about agents and AI augmenting the roles and skills that we have today so they can get to that level across the entire role library architecture that folks have.

But I’d love to hear some concrete examples, Jaclyn, on Agent AI and particularly around some of these HR workflows today. Like, how is Agentic AI actually changing or transforming some of these workflows, especially compared to what folks have today, which might be just standard automation, or things that we’ve seen in the past? Like, how is Agentic going to change some of these things that are happening in HR?

Jaclyn Zhuang 29:17

Yeah, so let’s take automation. In Talent Acquisition, you might have automation sort of sending calendar invites, maybe screen resumes, do some sort of… this is more key machine learning, doing some keyword matches there right now. With Agentic AI, you can have an agent open a req, build a skills-based profile, source candidates, screen for fit, schedule interviews, support the hiring manager in getting the interview notes all written up nicely. Just a plug for Eightfold solutions there: we’ve got the AI Interviewer out. It really speeds up the screening time, the processing time, so you can really get through and speak with a lot more candidates and provide that instant feedback, the more quicker turnaround and feedback than you can before. So that’s on the Talent Acquisition side.

Then we think about the Talent Management development side. Previously, static development plans: it’s in the system. Sometimes people update them, sometimes people don’t. Maybe you have some automation around there. There was a really honestly about that. But with agents now, agents can see your skills, see your roles you’re interested in, prompt your manager to have a coaching conversation with you, understand where you’re progressing in your career, and really bring together and connect better the employee, the manager, and really HR relationship to help you grow.

And then, if you think about it from a Workforce Planning, Workforce Readiness standpoint—which is a huge topic that we’ve been spending a lot of time chatting with customers about—an agent can automatically and always-on see a business unit, an org, understand where skills are, where skills are thin, where potentially AI automation may come in and disrupt things. Understand successes, succession planning. And then, instead of spending lots of time pulling reports, the HRBP, the Talent Intelligence function, can get a list of options of what to do with people: where to move them, what skills need to be done, what training and coaching investments need to be made, and then really have a good discussion with business and make those things happens. So there is a lot of change that’s taking place here that I think is super, super exciting.

Conor Volpe 31:42

And again, I think we’ve touched on this a little bit, but as you mentioned, all these different changes that are happening, and I think that was a great overview of how some of the roles for HR are changing. But again, we’ve hit on this. But let’s be more specific. There are skills or things that people do, aptitudes that people have that are going to be even more important as agents get infused into the flow of work. Like, for example, connection with another person. As much as agents are getting better—and as you mentioned, we have our own AI Interviewer—the ability to bring people together, to create a human connection, to create a relationship, is something that is distinctly human, right? Or even Jaclyn, I think you mentioned, companies are trying to help their employees be more agile, be more curious. Think about taking risks with some of these tools so they can, yeah, fall down, fail maybe once or twice, maybe three times, but ultimately find a path forward that works for them. So these are things that ultimately are going to be even more and more important in the Agentic Era.

But again, you were mentioning skills people need to learn to thrive in this era and also balance that with, from a company perspective, agents have so much promise in terms of expediting things, being just faster. But if you over-rotate into that, you leave the human quotient out of it. It’s a whole jumble; it’s hard to kind of parse through. So the question is: how do you think organizations can best balance the efficiency that agents can bring to the table with the need to preserve some of the things that are distinctly human? And also, as we think about still making some of these decisions, people still need to be involved heavily with making decisions, too. So the balance there is tricky.

Jaclyn Zhuang 33:25

Yeah, absolutely. And I think this is like a pet topic, talk-about topic for me, especially with people talking about how AI technology can take over things, can help people be more productive. But the piece we don’t spend enough time talking about is: you still need humans to evaluate the success of AI, of technology, of the agents in executing on that task. Which means that the people doing that still need to know what good looks like. Still have to have the skills, the knowledge, the experience, on what good looks like before the agents, automation, AI can come in and take away the repetitive, less meaningful tasks.

I think that’s the number one piece, and honestly, my number one piece of advice to customers when they’re thinking about putting in any sort of agentic technology, whether in the HR space or outside: people, you still have to invest in people. People still need to have the skills and have the knowledge and the experience on what good looks like for that area of work.

And then going beyond that, I think it’s very clear: it’s not an “outsource to agents and forget about it” kind of situation. Definitely let the agents handle the how. But people, humans, should own the why and the answer, “Should we do this?” And it’s because technology is great at speed, pattern recognition, understanding large parts of data, but people are the ones answering the questions of: “Should we even do this at all? Is it fair? How will this land with other people, with employees?” We’ve talked a little bit about change management—so crucial. And this is where a lot of skills like just the judgment, the empathy, the big picture thinking, are things which—you know, on your slide too—but are things which agents don’t have today. And I think it’s going to take agents a while to even get there.

So that’s the overall framing of this. I think when you go down and peel back the onion, it’s also thinking about which decisions are “human in the loop by design.” So meaning, yes, an agent can come up with a recommendation, but is not going to immediately act on that recommendation. Things especially around workforce planning, around promotions, terminations, race-sensitive stuff—agents can surface it with all the data involved, but humans still need to make the decision, right? We can’t outsource these things to agents. And so I would think about it in terms of using agents to augment what humans do with some of in especially in these areas, rather than bypassing them.

Conor Volpe 36:17

And something that’s not on the screen, but I think you essentially said was: I think we still need to be able to trust our expertise in terms of what good looks like. Just because AI has produced a piece of content, a decision, there’s a certain amount of, “Hey, is this actually maybe not even necessarily right? But is this what good looks like? And do I know that from my own experience?” Because not every time it gets it right. I mean, I’m sure we’ve all had experiences, yes, with hallucinations, but even something more like, “I don’t think that’s quite it. I’m going to need to try that again. Or that process, we’re missing some key steps that are unique to my organization or I’ve done in the past that I know will be useful.” There is that part of human intuition that is still very needed at this step to help guide agents and guide our AI to turn it into something that is really useful. So I think you’re kind of getting at that, but it’s the “What does good look like,” and that can be harder to express or harder for AI to nail out of the gate, and that requires the phrase that we’ve used, and a lot of people use, which is “human in the loop.”

Jaclyn Zhuang 37:21

Yeah, that’s right. And remember, agents are only able to make decisions based on what information you feed them, and that information is something that humans choose to put together to feed to the agents. Whereas if you think about the human brain, it’s a lot of your experiences, your skills, your knowledge, that kind of thing. Being able to transfer everything in human brains down to a machine is… well, it’s kind of impossible right now. And so that’s why, again, humans making the decisions, understanding what good looks like, is something agents can’t replicate today, and that’s why humans really need to focus on that.

Conor Volpe 37:58

Now, let’s talk a little bit about some of the agents that Eightfold is bringing to bear, and I think how we’re seeing that actually impact work. And we’ll kind of get into those specific agents in a moment, just to give everybody an overview of what we mean by that. But I think the question that for you, Jaclyn, to start, is: when you think about the agents that we’re actually building today, like, where do you see them ultimately helping—like, bringing the biggest reduction in workforce barriers, for example? Whether it’s something like access to information, stop wasting time on manual tasks, clarity about next steps in the process. Like, how do you see some of these agents specifically that we’re building for employees, managers, HRBPs? Like, how are they actually impacting the work that HR is doing and reducing some of these barriers?

Jaclyn Zhuang 38:43

Yeah. So these are things which we’re building and deploying with customers, and the technology is so early and in development that honestly, we’re all learning together as we deploy. But right now, the biggest pieces are, for example, with a Career Coach Agent: going beyond telling you, “Hey, here’s the HR policy,” but explaining, “Here’s what the HR policy means for you with your personal context,” highlighting what skills you should build given all the changes that are happening in the world, what’s a realistic next step in your career that you can take? And how do you get there? And who can help you get there? What can you do to get there? And not just that, it’s also interacting with the employee in their experience, and if the employee so chooses, flagging it to managers as well.

We hear a lot from our customers who are doing employee engagement surveys that they don’t always feel 100% supported by their managers. They want more career development, more support there. For online managers—I touched about this just now—managers are being crushed. Lots of goals, immense pressure to deliver while maintaining static or decreased headcount. And so with a Manager Coach Agent right on the manager side, it’s flagging to managers: “Here are the skill gaps. Here’s when you’ve not had a development or coaching conversation in a while.” And it’s helping the manager and supporting the manager to still achieve their business goals, but really thinking about: how do we get the team there? Because no manager can achieve their business goals alone. It’s about bringing the team along, having the right mix of people—humans as well as agents and AI and technology—to do that, but really nudging, and again, a companion to the manager to make all this happen.

And then we also have a Talent Agent that helps on the HR, the Talent Intelligence, Workforce Planning side of things, which keeps the organization aligned on headcount, on skills, on risk, really understanding it from a system basis—the enterprise view of the workforce—and really helping HR make sure that the workforce is future-proofed for whatever might come down that way. So all this just means less time tracking information, looking at data across spreadsheets and databases and PowerPoint slides, or really chasing approvals.

Conor Volpe 41:20

And showing this on the screen right now, just like in terms of our approach, but to double down on some of the things you were saying there. I think it’s important to talk about because I don’t know how much visibility there broadly is into how companies are building agents today. So I hope for everybody on the line, this is just instructive of one vendor’s approach. Because, as Jaclyn mentioned, these agents are not—we’re not replacing managers. We are augmenting managers, right? We’re helping them, frankly, be better managers. Or helping an employee… I think about in my career getting career advice, there are lots of people maybe I would have wanted to be able to talk to for mentorship, but I didn’t know how to have those conversations, or maybe how to best even phrase up my own development. Or am I at the phase where I can go ask someone three or four levels above me for that? To be able to have an agent, an always-on agent, who can help me with my own career pathing development, get answers to some of the questions that I don’t have access to today without bugging someone down the line—like, these are things that can be really impactful to again, augment the employee experience, and not just for the sake of efficiency, but also to help me be a better employee, or to help me be a better manager. So this is just again instructive of how agents can be used to help augment something like the HR function, or employees and managers at a company. So just want to be able to have everybody give a little bit insight to that.

Jaclyn Zhuang 42:44

Like I… building on that, I’m excited about the Career Coach Agent because of what I’ve seen over the years, just working at different companies, managing teams of very different sizes. And I think the most common questions that people want to ask, oftentimes they don’t dare to ask. And it’s: “How do I get promoted? How do I get paid more?” And generally, “You know, I like my job. Can’t quite say I like my manager, but I really want to stay in this company. Is there something else I can do? Where can I find that?” And when people don’t feel safe asking those questions, they go to online, third-party anonymous sources to go ask those questions, and sometimes you get really troll-like, very negative answers there. So that Career Coach Agent is really there to help provide this advice and help grow employees, help keep them engaged, in conjunction with the Manager Agent and the Talent Agent too.

Conor Volpe 43:40

Or they keep it bottled up, and all of a sudden they leave. And it’s surprised anyways, things we’ve all seen before. But I do want to ask you, too, and you were kind of getting at this as well, but just like with agents like this in tow, what becomes possible for career development, for growth, for mobility, that wasn’t really before without the introduction of agents like these?

Jaclyn Zhuang 44:03

Yeah, I think a lot of this is like real-time, personalized guidance and nudges. Like we spent a little time of talking about the Career Coach Agent. On the Manager Agent side, really highlighting strengths, gaps, growth opportunities tailored to each person on the team, so that you’re simultaneously helping your team members grow and figuring out and giving them the skills in order for you as a team to hit your business goals, which is, again, always the tension that any manager faces. And it’s something that happens every day, in line with work, with tasks, with projects that come up, rather than like a ritual, a company ritual of looking at things every three months or every six months. And then on the Talent Agent side of things, really breaking down barriers to internal mobility. Again, highlighting roles, gigs, new opportunities, new skills that both employees need to think about and managers also need to think about for their teams in line with future-proofing the workforce and having that whole enterprise move together towards the future.

Conor Volpe 45:11

And to add on to that, I think there are lots of things that we’re unlocking for employees and managers, but as Jaclyn, I believe I mentioned too, like Eightfold has an AI Interviewer, and we’re using it ourselves as, like I said, as a company who drinks our own champagne. And one of the things that we’re seeing that wasn’t possible before was a huge impact on the candidate experience, and a really positive one. Because I’m sure we have all applied for many jobs that we have never heard back from. We have sent a resume off into the abyss, and that’s it. What we’re seeing from our ability to use the AI Interviewer is so many more candidates can get an interview. There’s just only so many interviews humans and recruiters are capable of doing, but there may be more candidates that we actually do want to engage with and candidates who want to engage with us. So we’re seeing an uptick in candidate experience rates because they can interview. They can interview with an AI Interviewer, feel like they’ve been heard by the company, and the company can hear more from them. They can get updated details or information on their skills and capabilities from the AI Interviewer. And that might change their assessment of this person if they weren’t able to talk to them in the first place. And that’s again, something that wasn’t possible without the kind of scale that agents can provide. If you really want every single candidate who applies for your jobs [to] get an interview with an AI Interviewer, to think about how many recruiters or human beings you might need to make that possible… it’s a little staggering.

We’ve got a few minutes left, and I want to spend a little bit of time, as we mentioned, we’re in the early innings of agents and digital employees and working alongside agents and org design and all the things we’ve talked about today. So a lot of this here is prognosticating, and I want to spend a little bit more time doing that with you, which is largely speaking: Jaclyn, what do you think in the nearest term it actually looks like when people and agents just collaborate naturally? When that is just how we work, is we work alongside an agent and that is just part of the day-to-day. What does that actually look like to you?

Jaclyn Zhuang 47:14

Yeah, near future, mostly immediate future. I think I like, I love this: “Let’s have AI do all the boring stuff, the repetitive stuff that I actually don’t want to do, and give me the time and the space to think, to slow down, to focus on creative projects, to get in a room and problem solve with my colleagues rather than doing admin tasks.” I think for managers: less chasing, less “Where is this thing? Is it due? Are you on track?” and really more coaching, being able to up-level on a more strategic level.

Conor Volpe 47:49

And as you think, perhaps even further along about the next chapter of work? I mean, you were kind of getting at [it] right there, which is: “I want to do less, less admin, the stuff that I don’t necessarily want to spend my time doing.” But like, what do you think about the next chapter of work, even going past that? Like, what else just excites you about having agents in tow?

Jaclyn Zhuang 48:08

Yeah, I think, like just a plug out for how we’re thinking and how we’re building the Manager Agent together with our customers. You know, asking a question here: how many people can tell and talk about a manager that has truly helped them and truly made a difference in their lives? I think this is a question that most people will be hard-pressed to answer. But the opportunity to change that dynamic, change that relationship—starting with the manager, that then impacts their team, their employees, and how people work together to be more innovative, to grow—is super, super exciting.

Conor Volpe 48:54

And last question for you, because we are almost at time. This is something again, as we think about more and more proliferation of AI and agents, not just from employers, but also from candidates and employees. There is a world where more and more AI is just talking to AI, right? And that might sever some of the human connection that is really valuable, a) in work, but then b) in these HR processes about career development, about finding candidates that make a good fit for your organization. So in a world where, hey, we have more and more agents in tow, they’re part of our workforce, essentially, they’re digital employees; candidates have them too to help position themselves for an interview or to help coach them. How do we balance that with making sure that some of this human connection isn’t lost? In a world where AI might be doing a lot of talking to AI on behalf of people?

Jaclyn Zhuang 49:45

Yeah, I think this is about something I mentioned earlier on, which is: where do humans stay in the loop? How are decisions made? Humans still need to know, and should still know, what good looks like, and make the final decision—whether this is on hiring or performance or promotion or exits. Right? Agents can recommend and prepare, but it’s ultimately people, humans, who own the decision and own the outcome.

I think the other piece too is how AI is being designed and really around creating, enabling better human interaction rather than replacing human interaction. So for example, we spent a little bit of time talking about personalization and the guidance there. So giving managers richer context before a conversation, so that when the time spent together with an employee is more structured, but yeah, more honest, more specific, rather than some sort of hand-wavy piece. Agents can also coach employees on how to show up well in a conversation with managers to make that the most productive time together on growth. So a lot of this also relies on transparency and choice. So showing people when AI is being used, how it’s being used, what data it’s based on, how it’s making decisions, and give people a chance to correct it—because again, AI is not going to get everything right—or override it. And I think this is how you know humans can still maintain that human touch, which is so crucial, even in this new world of agents and AI.

Conor Volpe 51:20

I think it kind of elevates the importance of the human touch, and that’s when agents are done well, that’s what they should do. Like again, to think about it from an interviewing perspective: if, depending on how many rounds of interviews all of you on the line do for different roles, if the first round or two or three can be done by an AI Interviewer, but by the time a candidate sits down in front of a hiring manager or a panel of interviews… if there is a robust amount of information, if people have all the right context and they know the questions to ask, that interview can be better than it was today, right? Instead of kind of fumbling around trying to figure out competencies or whatever that looks like, by the time that person sits down with a person, with a human, they can do this. It can be much more fulfilling, interactive relationship building.

But I think that is all the time we have for today before we go. I do want to make sure that everybody out there, if you’re interested in learning more about Eightfold, if you want to see the actual product in action, we do weekly live demos for everybody out there, so you can get a taste of what Eightfold does today for our company, our customers, including our agents, but also including the rest of our platform across Talent Acquisition, Talent Management, Resource Management. So we do this every single week. If you’re interested, scan the QR code and take a look. But again, I started with “Thank you.” I want to reiterate, thank you. Getting an hour out of anybody’s day, like I mentioned, is no small feat. So we really appreciate you spending an hour of your day with us here today. That’s all we’ve got. Hester, I think we’re back over to you.

HR.com Moderator 52:54

I’d like to thank Conor and Jaclyn as well as all of you for joining us today. If you’d like to view this webcast again, the archived recording will be available on the HR.com website within 24 hours. The webcast credit will show in your HR.com account within two business days, and we’ll also send you an email with your credit information. Your feedback is important to us. Please take a moment to fill out the exit survey that opened in a new browser page on your computer. This concludes our webcast. Enjoy the rest of your day. Thank you, everyone.