Podcast

HR needs AI-ready talent

AI is changing how we work, and HR teams are poised to lead the way. Learn more in this research-backed conversation with Forrester Principal Analyst Betsy Summers.

HR needs AI-ready talent

Overview
Transcript

HR needs AI-ready talent, with half of HR leaders now prioritizing the technology — nearly double what it was just three years ago.

Lead the change in becoming a high-functioning, cohesive HR team that aligns talent strategies to your overall business goals for the good of all.

Forrester Principal Analyst Betsy Summers joins The New Talent Code to share how you can achieve this AI-ready status. She also shares the latest in Forrester research and why HR has a critical role in every business success story right now.

In this episode, you’ll also learn:

  • Why taking a skills-based approach to talent planning matters.
  • How to embrace AI in the HR tech stack.
  • And how HR can be the leading player in driving change.

[00:00:00] Ligia: Welcome to the New Talent Code, a podcast with practical insights, dedicated to empowering change agents in HR to push the envelope in their talent functions. I’m Ligia Zamora. 

[00:00:19] Jason Cerrato: And I’m Jason Cerrato. We’re bringing you the best thought leaders in the talent space to share stories about how they are designing the workforce of the future, transforming processes, rethinking old constructs, and leveraging cutting-edge technology to solve today’s pressing talent issues.

[00:00:34] It’s what we call the New Talent Code. 

[00:00:38] Ligia: So if you’re looking for practical, actionable advice to get your workforce future-ready, you’ve come to the right place.

[00:00:50] Jason Cerrato: What do Shakespeare and HR have in common? Diving into the same age-old problems, miscommunication, often to painful results, and making the same mistakes over and over again. Betsy Summers from Forrester joins us to share how to save your organization from becoming a Shakespearean tragedy. Instead, you can help lead the change to become a high-functioning, cohesive HR team that aligns talent strategies to your overall business goals for the good of all.

[00:01:17] During our discussion, she talks about why HR has a critical role in every business success story right now. From taking a skills-based approach to talent planning to embracing AI in the tech stack, HR can be the leading player every company needs to drive change. Our episode with Betsy starts now.

[00:01:40] Ligia: Betsy, thanks so much for joining us again. Lovely to see your face. It is a pleasure to be here. Thank you. As a way of introduction, I think you know that at Eightfold, we’re fascinated by non-linear career paths and we’re Firm believers that people should try new things and that they should be hired for their potential.

[00:02:00] Tell us a little bit more. How did you get started? Did five-year-old Betsy always aim to be an analyst at Forrester? 

[00:02:09] Betsy Summers: Probably the part that loves to be a know it all or loves to like have an answer, yes. In the preparation for the podcast, I was actually counting out all of the careers I’ve had or the career trajectories, and I think I’ve had three and a half, four, definitely been working most of my life since I was 14, but the first time I started really carving out a career was in theater, and I started that Definitely in high school, but when I was in college, I was doing it more professionally, doing a lot of behind the scenes work as stage manager, dramaturge.

[00:02:48] Set designer and builder. And I did that even after college as well. So there was definitely a really big theater vein and I really considered it as a career for a while until I realized that I needed some financial security. And that was the same thing that kind of pulled me away from sailing as a career, but I got pretty far down that path in terms of certifications and licensure.

[00:03:13] But. I landed in the kind of corporate development world. So being a corporate professional, but always in the realm of human capital management or talent management across the advisory and kind of management consulting part of that, you know, telling people what to do, but then also doing it, got trained to be a coach and then working in the marketing side.

[00:03:37] So talking about it and positioning it now. I guess going full circle into being an analyst. So now having kind of walked around the block enough, I, I’m able to tell people or give people advice. I kind of had a love hate relationship with the expert label, but I’ve definitely acquired a lot of skills along the way.

[00:03:58] And most of, I think my big learning moments happened on the deck. Of a ship and also like backstage in theater because you have to be scrappy, you have to work together, you have to think on your feet, you have to practice, you have to drill, and there’s just a lot of respect I have for using your hands as well.

[00:04:20] So that’s just always something I carry with me and try to work with my clients on in terms of like, let’s put this into your body, you know, the knowledge, you know, like what to do, but let’s actually practice doing it. 

[00:04:32] Jason Cerrato: Every time we have this conversation, it’s amazing how the stories weave into where the people are today.

[00:04:38] You know, I had a little exposure into the analyst world. And when I was going through onboarding and getting trained, someone explained, you know, analysts have to dazzle on the phone, on the page and on the stage. And I never thought about that third part on the stage and think about all the presentations that you have to give as I’m listening to your background and thinking about it, it makes perfect sense.

[00:05:01] And part of what brings us here today was we had you on the stage at Cultivate earlier in the summer and I really enjoyed your session and I’ve listened to the recording and I’ve made it required learning for a lot of the people here at Eightfold and for anyone else that I can send it to and share it to, because I think there were so many golden nuggets and little tidbits that we wanted to have you out here on the New Talent Code on the podcast because we are here To crack the New Talent Code and learn about how organizations are trying to tackle this.

[00:05:34] And when you were on stage and Menlo Park, I just think the way you phrase what’s happening in the world of HR and some of the challenges that’s happening and how people are both trying to address this as well as potentially getting stuck or maybe even framing some of this incorrectly. Really resonated with me.

[00:05:56] So kind of want to just jump off the conversation with fast forwarding the conversation to where we are today, but recapping, you know, where we left off. The last time we saw you at Cultivate, where do you think organizations currently stand as we talk about talent, intelligence, and skills based organizations, you know, one of the things that you framed very succinctly is that this is not just about skills.

[00:06:20] There’s a heavy focus on skills, but it really is about skills, intelligence and their application in context. So can you talk about kind of where you think people are either applying it correctly or potentially getting lost? 

[00:06:34] Betsy Summers: Yeah. Oh, what a great question because the context piece is so important, right?

[00:06:39] Because the context helps us understand how it really shows up, like how the capabilities really come to life. And part of that understanding of talent intelligence, the kind of more holistic approach to understanding how can someone actually bring their skills and knowledge to work was really drawing on a lot of my training as a coach because we know that Knowing what to do or knowing how to do something is only part of the puzzle.

[00:07:10] A lot of times we have other things that either are holding us back or helping us be more successful. I talk about it as the skill, will, hill triad. You have the skill. You also have to have the will, the motivation, the desire, the aspiration, the interest to want to do something. And then you also have to address the hill.

[00:07:29] Are there things in the way? Right, do people have the right resources, the right time, the right space, the capacity, the energy, the engagement that they need to actually do the work? Do they have the money, the resources, et cetera? What’s the hill aspect? Part of that hill aspect can also be an interior hill, the confidence to do it.

[00:07:49] And so that’s something that as I think about more broadly that the talent intelligence angle, if people drive your business, why do you know so little about them? That’s what I keep saying to people over and over. Just asking that rhetorical question because At the end of the day, skills data is just data about your people and you desperately need it.

[00:08:12] Also engagement data, interest and aspiration data, right? Because we need skill and interest and aspiration to serve our career pathing and our succession planning and the various learning paths and intentional upskilling programs that we want to create to help them be more efficient and effective.

[00:08:30] And so we need all of this data. And yet we are still hampered by these very disconnected systems that might have pieces of that data, but nothing is bringing them all together. And then if we’re not leveraging something that can keep up with how dynamic people are, like how much we actually grow and change, right?

[00:08:51] We’re not like widgets that are just sitting there. Not changing and stagnant until we get an upgrade. We are constantly shifting, changing our mind, going in different directions, acquiring skill through experience. That’s how people learn is usually through experience. And unless we are actually creating those data pathways to ingest that information and then using a technology that is capable of keeping up with how people are learning and growing, which is basically AI.

[00:09:21] Then we are not actually able to leverage any of that data at all. And so it’s, it’s almost having a back to basics conversation with people without even talking about, you know, what vendors are in this space or what does a skill strategy even look like? It’s just talking about like, look, This is very important people data that you need and you need to uncover whatever is blocking you from getting full access and realizing the full potential of the data that you have about your people and that they need to take a data approach and that, you know, skills is just one piece of data, but they have to think about it from the experience that people will have in the organization and the outcomes that they’re trying to drive.

[00:10:08] So It’s so funny. Some of like to your question of where people are getting stuck. And this goes back to theater. So much of it is Shakespearean in nature. People are not talking to each other. They are not having the conversation. I have had so many conversations with people in the same company, but in different functions about skills about the same problem that they are having.

[00:10:35] But yet they are not talking to each other. And then it’s me who has to connect the dots to be like, Hey, James, you should probably hook up with Michelle because she’s an HR, you’re an IT, you’re talking to me about the same problem, but you need to talk together. I always think about what could be possible if people could just collaborate on this issue more, because it is something that affects the entire enterprise so deeply.

[00:11:02] Jason Cerrato: What are the themes that we’ve had? As we’ve been talking to leaders on this journey is part of this really is focused on a specific business problem. So one of the things you just mentioned as you’ve been working with companies at Forrester is that, you know, you’re speaking to someone in HR who’s working on an initiative, but also speaking to someone in IT

[00:11:22] who’s working on the other side of maybe the same initiative. Right. So is part of this also that the application of a lot of this capability and these technologies really do need to tie to some business problem? And part of it is, this isn’t just an exercise for HR sake. It’s really trying to identify and solve what it really is the problem we’re addressing.

[00:11:46] Betsy Summers: Yes. I mean, Absolutely. Excellent. HR can really take this role of advocating and amplifying the pain that exists within the organization, right? They need to be going and talking to their functional leaders, asking them specifically about the skills, challenges that they have, whether they are skills shortages that they’re experiencing, or a lack of career pathing.

[00:12:08] Or confusion with the job families and job architecture taking too long to hire someone because the recruiting process is clunky or just outdated, even asking what about our current skills approach is not working like so many times I talked to the functional leaders who say, Yes, we have a skills approach that H.

[00:12:31] R. Has given us, but we have to do a bunch by ourselves on Excel because they gave us, you know, 10 skills for our function. We got to go deeper and deeper level two, level three of those skills to make it actionable for us. Like if you want us to make talent decisions based on skills, you better get us accurate and precise enough skills data to actually act on.

[00:12:58] That tends to be the biggest disconnect when it comes to HR, really understanding the business problem. I think if they took a different approach around really amplifying the voices that already exist and then figuring out how can we centralize this effort, how can we help people come together on this issue and being more of an enablement function rather than being maybe where they’re more comfortable being the command and control or kind of top down policy moderators.

[00:13:30] I think that will really serve them. The other thing that comes out a lot is, is sometimes it takes a lot of work before You can really achieve those business results in a huge way. Like, yes, you can make big advances in any of those use cases right away, especially leveraging AI for sure. Just like how I just bought a house.

[00:13:58] I want to put a playset in my backyard, but I can’t do that playset until I move that shed that’s in the way. But to do that, I have to build a foundation over here and a place for the shed to actually go. It’s the same thing that I see with skill strategy. In needing to really clean up your job architecture first before you expect any of this like magic to happen from a career pathing recruiting workforce planning perspective.

[00:14:22] So there’s sometimes I think some surprises because a skill strategy actually exposes a lot of things that had been kind of latently collecting dust. In the corners of our org structures that we didn’t want to talk about, we would just sweep it under the rug every three or five years and hope that no one looks at it, but just the level to which we don’t update our job descriptions that we don’t standardize our job families that we don’t have data that the system can use to actually help us create career paths for us, everything turns out to be super manual, and that’s what people don’t have time for, and that’s why career pathing doesn’t exist if you don’t have the technology to support it.

[00:15:05] I concur, and 

[00:15:06] Ligia: I’m listening to you and smiling because you’re taking the questions out of my mouth. But isn’t the beauty of it that their technology exists, such as artificial intelligence. So you don’t actually have to clean up, like in your example, your backyard just yet. The technology is built in such a way that it will make sense of those constructs, those architectures you already have and come back and sort of fix it in the process.

[00:15:33] Thanks. 

[00:15:34] Betsy Summers: Using AI for this, especially for job architecture, is brilliant because Even if the AI is able to deliver a job architecture that’s even 50 or 60 percent accurate, like that’s a huge level up from where the organization was. So there is like a huge benefit from zero to one and in order to get from one to whatever.

[00:15:56] Then there is some back and forth that you need to do or the training and tuning, or that’s where the human in the loop comes in to say, no, actually customer service means a different thing for us. And this is that particular job family, or this is how we might want to specify that these jobs are different from those jobs or whatever, with all of the.

[00:16:17] Paper, Excel, and reports, the data that we do have in these systems, they’re just kind of sitting there as systems of record, not systems of intelligence, which we desperately need them to be. But it’s also the human in the loop that is part of this conversation. And we can’t let AI run everything because it’s not going to know.

[00:16:39] all of the intricacies and nuances that we want it to understand, especially when we get into the realm of durable skills or some of the soft skills, some of the leadership skills. We do need to teach it exactly what we mean. We need to define it for it. Because there are so many different definitions that exist out there, that’s where I’m hoping to see a lot of the skill strategy evolve is for the humans actually in charge of the skill strategy, take a lot more ownership, willing ownership of the definitions for skills and breaking down the proficiency levels to really help managers understand the observable behavior of these skills and what should I look for and how are we going to assess and verify those skills?

[00:17:24] I’m excited for that. To come into the skills conversation. We’re not there yet. We’re very much at the beginning where we’re still seeing some of the magic of skills intelligence at work at the outset, but I’m really excited for those organizations who were able to like really. Deepen and like mature their processes over time.

[00:17:47] Jason Cerrato: But Betsy, there’s a lot of discussion going on right now of organizations trying to get their hands around the difference between optimization and transformation, right? And what this means and how you drive it and shifting from cyclical processes to, you know, through the use of talent, intelligence, and AI, this becomes increasingly continuous and the willingness of operating that way.

[00:18:16] And there is that significant benefit of even just the accomplishment, like you said, of what it takes to go from zero to one and 60 percent to 70 percent and the accomplishment of how much progress that means. But it’s hard for people to kind of wrap their head around that and understand. Operating in that type of a, of a way.

[00:18:40] So one of the things that I know Forrester has been working on is this line of research, this kind of IHR paradox. How are you seeing this play out in some of the conversations you’re having with organizations that are thinking about coming to grips with this and going back and forth between optimizing processes and transforming the way they operate?

[00:19:02] Betsy Summers: Doing this research, especially on this HRAI paradox. It was very illuminating, and I think this will probably resonate with you too, that as an analyst and also having worked on the vendor side as well, we’re always a little ahead of where user organizations are because they are doing the work and every day, day in and day out, they are having to muddle through all of the various permissions and budgets and approval processes and all the things.

[00:19:34] And we are like, come on, go to the future, see the next thing. It’s just around the corner. You can do it. And I think what’s interesting about the skilled strategy is it typically is a transformation, especially if the organization hasn’t modernized a lot of its HR systems, but also its strategies, its policies, its procedures to date.

[00:19:58] There was a great study out of Harvard Business School. Their leadership studies program did a specific survey to leaders about transformation and it found that the least affected or impacted processes after a full business transformation were talent processes that like usually don’t change how they recruit, how they internally promote people and their performance management process.

[00:20:24] And those are exactly what need to change. After you do a transformation, because you have to show people that the way that you are working is now different. And so we will reward and recognize you in different ways. It really signifies for me that people had not really been modernizing the way that they were doing talent or HR or workforce planning in the past.

[00:20:49] And maybe they were applying a new tool to something, but their strategy and their process at the core wasn’t changing. And so if you’re trying to do a skill strategy or adopt a skills based methodology, become a skills based organization, you will experience a transformation if you really want to see those outcomes, because you’re going to have to change things culturally, you’re going to have to change how you incentivize people and reward people and recognize people, you’re going to have to change the way that you promote people internally, how you manage performance.

[00:21:26] how you recruit people. I mean, so much is going to have to change. And the optimization angle, I think people who maybe want to take an optimization approach or like an incremental improvement approach will actually find themselves more moving towards transformation as they go. It’s almost inevitable if they haven’t done anything like this before, if they don’t have a lot of the internal capabilities.

[00:21:56] For data analysis or talent, intelligence, skills, intelligence, owning governance like this in terms of a kind of cross functional talent strategy. And it came up in a lot of the interviews, it’s really shaking things up for people. Org structures are happening. People are now. Taking in AI And technology as a part of their roles instead of it just being an isolated team on the side, like the H.

[00:22:26] R. I. T. Team that handles it all. 

[00:22:28] Ligia: So I love this. And as part of this transformation, my follow on question is how aware do you think H. R. Is in terms of how they’re going to show up, how their role changes and the skills that they’re going to need as part of this transformation in the future. 

[00:22:45] Betsy Summers: Yeah, that’s a great question because it is really, it’s all about the skills, right?

[00:22:50] Like in order to be confident in your approach, you have to know what you’re doing or you have to feel like you know what you’re doing. And in a lot of these things that are new, it also takes this kind of mindset shift and this willingness to take on a more experimentation approach or a learning approach rather than a, we will only rely on things that have been done before, which is historically legacy of HR.

[00:23:17] And at least from the research that we’ve done and the surveys that we’ve conducted, We asked HR leaders three big questions about their entire function. We asked them specifically about AI for each of these questions. So we asked them, how important are the following issues for you in your list of priorities?

[00:23:36] Basically, give us your priority list. We also asked them, how confident do you feel in your own HR organization’s capabilities in these areas? And then where are you prioritizing skills investment? Where are you actually going to develop people’s skills? Because that is a very important question. So we found when it comes to AI.

[00:23:59] In 2021, only 28 percent of HR leaders said that AI was a priority for them. The good news is that now, having rerun the survey this year, we see that AI and machine learning is now maybe 50 percent of people say it’s a priority. So that’s at least an increase, some good news. But then when we asked them about confidence level in 2021, only 19 percent of HR leaders were confident in their team’s abilities around AI in 2024.

[00:24:30] So the number actually slightly went down. In terms of the ways that they are prioritizing investment in skills development for HR in 2021, 32 percent of HR leaders were investing in AI skills for HR and now in 2024, so we’ve only seen it go up just a little bit for me. It’s not enough. Because HR is at the crux.

[00:24:58] They are the linchpin for AI success within the organization because they are the ones who have to help other leaders navigate what these changes will bring. Like if we introduce AI into our team, either horizontally, vertically as chatbots, however, they look. It’s HR who’s going to have to advise on the skilling requirements, how jobs will need to change, who needs to be hired now with new skills, and who are going to promote into different positions, and overall workforce planning.

[00:25:33] How is this going to change our overall makeup of the organization now and in the future? So a lot of OD conversations have to happen because of this. So if HR doesn’t feel confident having those conversations, they don’t know what they’re talking about, how successful will they be in navigating the rest of the organization through it?

[00:25:53] They also have to carry the added burden of their own jobs changing. So our jobs forecast research shows that. Between 15 and 30 percent of an HR admin’s job could change because of AI. And so having to navigate that personal change while also then having to shepherd the entire organization through those changes.

[00:26:14] That’s incredibly heavy for a person to carry if they don’t have access to the skills and the resources they need to be successful. 

[00:26:22] Ligia: Do you think that some of this lack of confidence in AI might be tied to fear of AI taking over their jobs? There’s been a lot written about this, whether exaggerated or not.

[00:26:35] I think some of it is sort of futuristic potentially, and maybe even delving into the not possible and not true, but I wonder what is your sense of the employee and then again, HR is receptiveness to adopting AI. And do you think that is tying into some of the results you’re seeing in the survey? 

[00:26:55] Betsy Summers: We tend to fear things we don’t understand, right?

[00:26:58] And so there is a connection between The understanding, the skills around what AI can and cannot do, how much it needs humans that if more people have that understanding, maybe they wouldn’t be so afraid of it. I also do, and this is part of the paradox because HR is in the position as a protector of the organization, protector of the employer, and rightfully so, they need to keep that compliance angle of their job in order to help the organization manage risk.

[00:27:31] When it comes to those AI use cases that have to do with employment and promotion, it’s incredibly important that someone is there to say, let’s make sure we are doing the right thing. HR can carry that responsibility as they have in the past. We also do want them to have more of that mindset of what if, what would be possible?

[00:27:54] And that only really comes through that upskilling is like, Really understanding what it’s capable of, getting their hands in it, understanding how the training and tuning really does impact the outputs, understanding the benefits of a I when it comes to mitigating bias, but then also understanding the risks of a I and bias, right?

[00:28:18] Because it’s encoding a lot of the biases of the people who might have developed it or trained it or tuned it. And so that holistic understanding, we want them to embrace. I think as a badge of honor too, for really holding the responsibility of both of those things, using AI for growth and also protecting against any of the risks of AI.

[00:28:42] Jason Cerrato: Yeah. I was just going to say a few minutes ago, you were talking about how. You know, we need HR to kind of stand up and lead for talent enablement and for being a growth champion. So here we are as an HR function, finding ourselves at a crossroads, right? 

[00:28:58] Betsy Summers: Yeah. And it’s complicated, but who better to manage complexity than human beings?

[00:29:04] We hold paradoxes as true all the time for ourselves. And I think both are possible, both to be protective, but then also be a growth enabler. More often when I talk to talent leaders, and I guess it’s helpful to note whenever I’m talking about HR, I mean, like the broader people function. It’s not just people within HR operations.

[00:29:28] I’m also referencing talent, people in culture, employee experience. In the interviews, I talked to a number of leaders who were saying, yes, it can be scary. The new is always a little scary, but it’s also quite exciting. And being able to lead and take charge of something that’s new is. Very personally gratifying and also does look great on her resume that you can stand up and lead through uncertainty and navigate ambiguity because only more of that is coming in our world.

[00:30:05] If we had a crystal ball, if we had peer reviewed papers on everything, if we had IO psychs with 10, 20 years of experience in a particular area. That would be great, but we don’t have that about AI applied to talent use cases. We’re learning as we go. And there are a number of resources that organizations can draw on, right?

[00:30:30] It’s not just the vendor responsibility. It’s also the consultancies that they might bring in, the peers that they have in their broader community, who else is doing this together at the same time. Knowing that they are not alone and knowing that they have a broader value network, I guess it’s Forrester calls it the value network of people and institutions who are there to help them in various ways.

[00:30:55] So then they’re not over relying on one or two of those institutions, but rather kind of drawing on from whatever they need. 

[00:31:04] Jason Cerrato: So we’ve already talked about kind of the continuous nature of skills, intelligence, and. AI, how this changes some talent processes and HR processes. You and I in the past have talked about different from how things may have been done in the past, where you may design how you’re going to manage this or how you’re going to push out different programming in the past, you may have tried to do it from the top down with things like skills, intelligence, or with talent intelligence, you also have the opportunity to get information in real time from the bottom up.

[00:31:38] And kind of learn from your workforce and from your people and from skills kind of in context from what’s happening as people are developing skills and working in real time. Do you think that’s another way that we can manage in this kind of future of work in times of uncertainty? Because now we have more immediacy of information.

[00:32:01] Betsy Summers: What you said is spot on in terms of the. Rapidly changing timescales that people are having to make decisions on. Like people are transitioning from being a program manager type of role, which is like, you do deep discovery about a particular need, spend months developing something, and then you roll out this program that will exist forever into being a product manager, keeping your eye on how are people using this thing?

[00:32:29] How is it working? What new information can I ingest at any moment keeping that rolling road map going with enhancements, innovations, whatever, but even H. R. Taking that new approach to the role, it does mean they need better data. They need access to more information. They need the platforms to allow that connectivity of data across their functions, right?

[00:32:54] We don’t want talent acquisition working off one set of data. And learning and performance management from another, we want them all to have access to the same data, same conversation so that people are not looking different. Just depending on what system you’re looking at. The bottom up side is for me, mostly.

[00:33:16] Like, it’s an equity conversation in action for me, which if you take career pathing, for example, and the way that career pathing or talent mobility typically works at an organization, it’s informal. It’s like, who do I know who could do this? Or maybe career pathing could happen if you have a great manager who has time to spend with you to explore what career paths are available.

[00:33:39] But rather, if you apply a I and technology user experience to it and you give people a place to go self service so that they can explore themselves, they will be much more likely to give you the information that you need from a leadership level to even make those talent decisions. And so there is a virtuous cycle of the equity, the access of information.

[00:34:05] Overall, I think that’s the story that I hear most often. 

[00:34:09] Ligia: Well, especially if they’re seeing the value, what’s in it for me, right? Then you’re more likely to contribute more of that information or even correct information that might be deemed incorrect, sort of fill in the gaps. So, I’m curious, Betsy, in terms of talking to customers, I know in the past, especially with the democratization of AI with ChatGPT and everybody sort of testing it, trying and understanding just the nuances, the limitations, but also the power behind AI, there was definitely a push, I think, from the CIO’s office to bring in artificial intelligence to the company.

[00:34:45] Are you seeing this still with your customers, the C suite buy in in terms of successful AI adoption? Do you find the CHROs or other executives are potentially hesitating to bring in AI and deploy it along talent processes? 

[00:35:03] Betsy Summers: Yes, I’m overall seeing The same plans to bring AI into the organization, like when I think of the year over year comparison of some of our AI specific surveys and data, there’s still a large segment of our survey respondents.

[00:35:23] Actively pursuing piloting or kind of POC for various use cases, there’s still a lot of very healthy adoption and exploration with a lot of these use cases in primarily around productivity as the intended general or Uber use case for it and kind of that desired outcome to drive productivity benefits.

[00:35:48] When it comes to this, I do see some reticence bringing AI into all HR use cases, but usually that reticence is mostly reacting and responding to threats that they might have seen either in the media or they’ll always point to some kind of newsworthy or like news story of AI gone wrong. And In reality, when we tell them AI models have been active in many of the tools that you’ve been using for a long time, did you know that then they’ll kind of walk it back and say, Oh, actually then, you know, it’s not as scary.

[00:36:31] We’ve been leveraging this successfully before. And now, especially bringing in generative AI, we are building from a a foundation that we had already built for more predictive forms of AI. And so we can just build on what we’ve already done in the past in terms of the internal capabilities and governance structures and risk mitigation, et cetera.

[00:36:53] So reminding people that while it’s making a big splash in the news, it’s It’s not actually new to the industry. That’s very helpful in mitigating a lot of those initial concerns. And I think also, I don’t know if it’s really hitting home for user organizations yet, but. I do think that the responsibility and onus that some of these newer regulations that are coming through, the responsibility they put on the vendor or the AI developer, as well as the end user organization who might be deploying, That particular algorithm, I think shared responsibility is helping boost confidence that it’s not all on the end user organization shoulders to make sure that it’s a shared responsibility across the entire AI supply chain.

[00:37:51] I think that helps. Reduce some of the anxiety that leaders have. 

[00:37:57] Ligia: Yeah, it’s an absolute partnership. 

[00:38:00] Jason Cerrato: Betsy, if you listen to the news, the news will tell you that AI will replace jobs. If you listen to the researchers and the academics, they will say AI will help create jobs. I see an application of skills intelligence in helping organizations understand Kind of the skills that organizations have and kind of how skills are emerging and how skills are developing to at least help prepare for the new jobs that’ll be creating or the increasingly hybrid specialized roles that are kind of co-mingling between functions.

[00:38:37] Where do you fall kind of in that debate or what is Forrester say in their research? 

[00:38:42] Betsy Summers: Forrester says that, yes, there will be some job loss. With AI, it’s inevitable, but it’s only some, the majority of jobs will just be changed by AI. And when we surveyed leaders, just last month, When we asked them, what do you think will happen in terms of your workforce?

[00:39:03] Will it increase or decrease because of AI? We asked them in the next 12 months and we also asked them 13 to 24 months, so out to two years, the majority of them responded that it will actually increase the number of jobs. They will have to have more people because AI needs to be managed. It’s not like we’re unleashing AI and letting it kind of run rampant within organizations.

[00:39:27] It needs people who know how to monitor, manage and train, tune and, and use it effectively. So they at least are saying we anticipate that it will actually create more jobs for those organizations than it will deplete or make jobs obsolete. So that at least should be good news for people. Now what you said about.

[00:39:52] AI is part of everyone’s job, or like the implication of most of these jobs will be changed because of AI brings with it this assumption that AI is now going to be part of everyone’s work, how they get work done. There are different levels of AI skills and AI confidence and comfort that everyone will need to have.

[00:40:12] Our data shows that less than half of employees know when to trust the outputs of AI. Thanks for watching. Bye. And that’s a problem, right? Like that’s where HR learning organizations need to step in to say, what kind of enablement do we need to provide to each segment of our population, depending on their proximity and level of use of AI, because it’s really helping people be more confident about using AI.

[00:40:41] And maybe part of that will be actually. Being very clear and transparent about how, hey, this career pathing tool that you’re using, it’s made possible by AI, that AI can actually help make all of these things accessible to you. It can help identify great talent and the ways that AI can benefit people.

[00:41:06] Leah, you were talking about what’s in it for me, right? Like, we have to make sure that anything we do with AI. We have that end user, the employee or member of the workforce in mind because we want to drive adoption. We want to drive participation. We also want them to give us feedback. Hey, this is not working or I need to escalate this or I have a question about this.

[00:41:29] Sometimes when we think about people who know when to question the results of AI, Those are people with a lot of experience. Those are mid-level to professional level. employees. What about the early-stage career people? What about the people who don’t have enough experience to know when the output of AI

[00:41:47] is a little suspect, and they need to maybe run it themselves just to check. So we have to put those safeguards in place so that everyone feels confident using AI In whatever use cases we choose for them. To me, I think that confidence angle is really important, both for H. R. To feel confident for themselves but also To help enable the workforce overall, 

[00:42:11] Ligia: are there any areas organizations and leaders aren’t addressing or paying attention to in this skills-based or AI.

[00:42:19] adoption conversation. So, in other words, as you talk to clients, should people be talking about certain things that they’re not talking about, such as bringing in AI and transforming? I think 

[00:42:34] Betsy Summers: the training or the ways to enable confidence, making sure that AI readiness is really at the forefront of people’s minds and the what’s in it for them.

[00:42:45] Like how will this help them personally do their job better or improve their employee experience? What will they be able to do now that they weren’t able to do in the past? And making sure that that’s really clear for people. The thing that I do see lacking, especially when it comes to skills, is Is that this is a journey like this is a skill strategy, like basically being able to leverage skills data across all of your talent decisions, having precise and accurate access to skills that has the potential to really transform the growth opportunities for organizations.

[00:43:28] It will improve their competitive advantage over time. It will improve their access to talent. It will make sure that they are de risking their organization from a workforce perspective, reducing attrition, managing costs. It will have a really big impact on operating margin, but not overnight. There are a lot of outcomes that are available for people even within days and weeks of turning on these tools.

[00:43:57] As you well know, because you work for one of them, right? And you get to see it every day. But the long term impacts, and yes, there are only a handful of organizations who are skills based, truly skills based at this point. And so we can only point to their stories and. They have different contexts and we don’t know exactly what other variables contributed to their success.

[00:44:19] But my hypothesis would be that over time we will see those organizations that have invested in AI-based skills intelligence and more broadly talent intelligence trying to bring in all of those disparate pieces of information about the employee experience. Those organizations will see outsized growth and outsized success in the market over those organizations who are still clinging to Excel or kind of system of record approach.

[00:44:48] Ligia: Well, historical success, as you said before. 

[00:44:52] Jason Cerrato: Well, this was why we wanted to have you back and have you join us on the podcast. We have commented and mentioned that you are a wealth of knowledge and would have a bunch of golden nuggets. And I think you brought the goods here today again. Thank you for joining us and spending the time with us.

[00:45:08] But we appreciate all the conversation and anecdotes here on the New Talent Code. Thank you for spending the time with us, Betsy. 

[00:45:14] Betsy Summers: Yeah, my pleasure. Thank 

[00:45:16] Ligia: you. Thanks for listening to the New Talent Code. This is a podcast produced by Eightfold AI. If you’d like to learn more about us, please visit us at eightfold.ai

[00:45:26] And you can find us on all your favorite social media sites. We’d love to connect and continue the conversation.

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