5 Game-Changing AI Skills HR Leaders Need in 2026

This transcript has been generated by AI and may contain slight discrepancies from the audio or video recording.

Nichol: The new word of the year is work slop. Because now that many people have access to AI, the volume of what's being circulated inside of organizations like new proposals, new initiatives, et cetera, it's higher than it's ever been.

Alex: We're diving into a topic that's not just timely, but absolutely essential for HR leaders. Right now we're talking about AI skills. With AI transforming the workplace at lightning speed, HR leaders are being called to step up and develop new capabilities to stay ahead of the curve.

Nichol: That's right. Today we're breaking down the top five AI skills that every HR leader needs to thrive in this new era. We'll talk about why these skills matter, how to develop them, and most importantly, how to apply them in real world scenarios.

Alex: We will also discuss what HR professionals are saying about their own readiness for AI and where the biggest gaps are. Plus, Nicole and I will also share actionable tips to help you start building these skills today.

Nichol: AI is clearly reshaping the workplace, and HR leaders are right at the center of this transformation. But with so much change happening so quickly, it can feel overwhelming to even know where to start. So before we dive into our top AI skills for HR, let's take a step back and think about the big picture.

Alex, if you had to describe the relationship between AI and HR in one sentence, what would it be?

Alex: I would say it is no doubt the empowerment and enablement bridge that will drive the future of work. How about you, Nicole? What's your one sentence take on AI and HR?

Nichol: Exciting and complicated. HR leaders are always in the room when it comes to AI implementations, the way that internal AI implementations and the way that companies are bringing them inside, bringing AI inside. The HR leaders are always there from learning and development to workforce optimization like in every stage.

And also they are being challenged and questioned as to the role of HR because of AI tools. So it's exciting and it's also complicated and it requires really leaning in.

Alright. Now that we have set the stage, let's get to the heart of the conversation. The top five AI skills that HR leaders need to thrive.

Alex: It's fascinating because these are skills that everyone is talking about today, right? And I think about specifically how these skills are being brought to bear, especially amongst HR leaders, right? These skills aren't just about understanding technology, they're about bridging the gap between AI and human intelligence to create better outcomes for employees and organizations.

So let's start with the first skill. Nicole, what's one skill you think every HR leader needs to develop today?

Nichol: I would say the baseline skill really is prompting for HR workflows. And I want to start there because in the HR profession is at different levels of proficiency. One of the things everyone that we're really fortunate to have at SHRM is we have an army of researchers. They actually are on Alex's team. And so we get such great data.

And so one of the things that we saw in our last SHRM research was that the majority of HR leaders today consider themselves to be beginners or just slightly after beginners. And so I would say the number one skill, if an HR leader doesn't have it already, is prompting for HR workflows.

Because it's more than having a recipe in iambic pentameter and being able to do just basic prompting, it's really prompting for your role and being able to write prompts that produce compliant job descriptions, structured prompts for all of the different HR service centers, reducing the admin load.

And so it's really, we're moving past basic prompting into HR workflow prompting and having that as a base skill.

Alex: As I think about that, one of the things that stands out to me about that in particular is it also relies upon the kind of development and or education that's necessary for all of your processes and what your workflows look like in terms of HR, right? And as we think about yesteryear in terms of HR, we always used to think of functions. We used to think of what it was that the processes were, and we used to think about what your centers of excellence needed to do.

If you were an HR business partner, for example, how did you go about actually making sure that you brought to fruition something that was a desired outcome, but what were the steps along the way?

Tomorrow is not like that. In fact, today is not like that. We actually have to be ready to kind of make those things come to life and really identify where it is that we can gain efficiencies by being AI fluent in many ways, right? I think that you're absolutely right. One of these things that makes this so important is about that efficiency.

What's that one tip that you would give someone for developing it tomorrow? In other words, if you were talking to a CHRO, let's say you're talking to Donna Morris at Walmart, what would you say to her, this is the one skill you need to develop, but then more than that, how do you advise her to go get that skill development?

Nichol: It's not just the prompting, but it's redesigning the workflows. And so that means really knowing where the holes in the problems are. And so the first AI step is actually not with AI at all, it's just sit in a room with your team to identify where are the big gaps in your offer to the company?

And then also where are the big gaps in the company? What are the things that you've always wanted to do that you haven't been able to, or where do you really feel like, where does the CHRO really feel like her or his organization is not doing everything they hoped and aspire to do? And it's sitting down and walking through those things and then bringing in the points of where to bring in technology.

Oftentimes when people start with the tech, then they end up with either the solution that the vendor has. It's like if you go into a vendor conversation without a really clear idea about what your goals are and where your problems are, you'll end up with a problem that looks a lot like their solution.

And so step number one actually doesn't include technology at all. It's really sitting down with your team and identifying what are the gaps that you want to fill that can be filled by AI.

And then the other thing that I would say is when people ask me this question, they're like, okay, where do I start? And I know you've done some great research on this too and have some thought process on it, but I tell them, avoid the three C's.

And so the three C's are, number one is commitment. If you're making a commitment to someone, don't use AI to do it. My personal opinion. So that's that last mile hiring decision. Like you can use AI to look through resumes, but it's like, really, who are you bringing in? So I don't use AI for commitment.

I don't use AI for crisis. Like if there's an issue, if there's someone in the organization that's having a problem, do not send them an email, an AI generated email about this. Especially if something tragic has happened in their lives.

And so don't use it for crisis and don't use it for conflict. Conflict, and there's all types of conflict in organizations and we certainly see with civility that there's that, but anytime human beings have a disagreement or a difference of opinion that should be handled in person.

So those are my three C's. Don't use AI for commitment, crisis or conflict.

Alex: You know, it's funny because one of the things that I do think that is a viable way of using AI, I call it the three C's as well, but it's three C's in different ways, right? It's creativity, it's collaboration, and then it's anything having to do with contact, right? And making sure that you're building in the kind of contacts that you want to have, right?

And so I think of these kinds of things as really the three pillars of the three C's you should take advantage of, and the three C's where you should never take advantage of, right. When I'm thinking about those pieces of guidance, I couldn't agree with you more, Nicole on how you do that.

The last thing that I'll highlight is sometimes change, especially when it comes to building in change. I will say that that's sort of a toss up. You never know what is the right application and or good use of change processes and really using AI in that space. So I tend to be someone when thinking about that organizational behavior, I try to think about where is it that those kinds of tools will be helpful and where is it that they can be detrimental? But it's one of the few that where I don't know that I have a great answer.

And then the last thing I'll say is when it comes to compensation, I worry about not having that last human in the mile, to your point around the human in the last mile.

Nichol: Would you put compensation in commitment?

Alex: I would. Yeah. Because it really is part of that big commitment. And candidly, it's where people, where you're tying something that is a dollar amount and a reward to a commitment that's been made for someone's work. So I fully agree with you on that.

Nichol: You know, Alex, every time I talk to you, I think I don't talk to Alex enough because I just, you're such a deep font of experience and research and understanding of this profession. I think we've just made a framework because there's another three C's that I tell people about when it comes to actually getting ROI from AI.

You don't actually get ROI until whatever you've bought is specialized for your context, your culture, and your customers. Because if people are using off the shelf whatever, then they have the exact same capacity as their competitor. And if they're first, it might give them a little bit of a leeway, but it really starts to deliver when you get into that specialization around context, customer, and culture.

And because all organizations have their own unique culture. And what I've seen in terms of companies that are really landing their implementations and their transformations, it's when they've specialized that.

So now we have three C's. We have when not to use it for commitment crisis or conflict, when to use it for creativity, collaboration, and context, right?

Alex: Yeah.

Nichol: And contacting and then how to make money off of it and or how to really make it transform your organization culture, context, and customers. Okay. We have a new infographic.

Alex: I know. You make me laugh because I was with Dave Ulrich at the Global Peter Drucker forum just this month, and one of the things that he's focusing on is what is the next generation iteration of true HR excellence. He was basing a lot of his work on things that are related to stakeholder value, right? And driving stakeholder value.

And one of the things that he always highlighted was, what is the responsibility of HR? Even in an era of AI, it's the, so here's your goal, what you're trying to accomplish, but so what you can do with it, right? Everything is designed to be stakeholder value.

And when I think of your three C's, the context, the clients and or the customers and then the individuals involved, I really think specifically that is about how you tie stakeholder value from what it is that you do when you use AI and HR. I love it. I see all kinds of synergies and it makes me think of Dave, because he refers to his own training. He is, even though he's the father of modern HR, as many people like to refer to him, he is one who will tell you right off the bat, all he is is a simplifier. He is a taxonomist. He wants to have taxonomies that he can build in.

So I think we may have just found a new framework that we can toy with. Maybe all three of us can start talking about it at some point.

Nichol: I love it. I love it. And so, alright, so far we've done two skills. One is prompting for HR workflows, and then the next one is workflow design, redesign and integration. And that's sort of like what in talent onboarding, L and D or performance can be AI supported. Where in your process we kind of talked about that.

What do you think your next top five is?

Alex: Ooh. My next top five is data literacy and more importantly, data governance and manipulation. And I say that in large part, well, our research speaks to that, right? When asking specifically AI responsible HR professionals within their own organization, what is the one skill that they really think they need more of and ties directly to their responsibilities?

It's really data governance and understanding the data that is fed into any form of AI, right? We've heard this repeatedly over the course of the last one hundred fifty years garbage in, garbage out, right? And so half of what you gotta think about is understanding what it means to have data, what kind of data is used, how it is functioned, how it is analyzed.

More importantly, how it is used to create specific outputs. And in an era of AI that is even more salient in terms of what it is that HR leaders need to be doing in terms of thinking about not just what data to protect and keep out of the AI pool, but more importantly, what kind of data is being used to create these workflows, as you described, Nicole, but more importantly, to revise them, to rethink them, and then to think about who it is that is part of the inputs into these workflows.

And how they generate outputs like productivity, how they generate outputs like success and greater creativity, greater collaboration. And so, as I think about it, to me, the one thing that I wish every person that's in the HR profession could take right now it's actually a data governance and or data literacy course.

Not just in terms of how they use AI, but more importantly just thinking about how they think about business as nothing more than a shop or a place that creates and trades data. And so to me that's the next one on the list.

And when I start thinking about what the future looks like, because people will ask me, well, you say that because you're sort of jaded, right? You're or you're biased in that you're a data guy, so you're gonna care about data. When I think specifically about what the future looks like when we start talking about agents that orchestrate and read data and start to act for us and predict what kind of actions need to be taken, like that next step in HR where you see an opening over here, you see a person who's got some skill sets in a different part of the organization, and then that orchestration starts to help.

Bring that job to light and bring that individual with those skill sets to light. And before you know it, that agent is doing all these things and kind of orchestrating this entire move for you as an organization, you want to know what kind of data it's taking into account. Because the worst thing that you want to do is because of an opening you create all mismanagement and disengagement or a loss of what is worker value in terms of how you go about doing these things, or employee value and productivity.

So in my mind, I really think data is the next key component. And understanding the data layer that is being used and leveraged by your AI.

Nichol: There's so many good things in that because I don't know if you remember, but probably like last year you and I talked about responsible AI becoming, it's home, or, and this is for internal use, everyone, this isn't in the product lines, but how it's being used internally being something that's going to sort of come home to HR in a way.

Because on the other side of the data is the employee who's saying, how is my compensation calculated? How is it, they're gonna be asking questions. And what they fundamentally wanna know is they wanna know was it used? Did people do it or did people plus AI do it? Was it used, was it fair? Is it transparent? Can I see, can I understand? Tell me how I'm being evaluated.

And so the employees on the other side of the data story is being able to honestly, and authoritatively, or knowledgeably is a better word, tell employees how AI is being used to manage the workforce in all of the different ways.

And so it's really about glass boxes, not black boxes. Which is one of the reasons why the overall fluency that you mentioned is, and literacy is really important because HR leaders when they're sitting across the desk or having that coffee walk and talk with an employee and talking to them about their career projection, because also the other thing in this transformation, as AI starts to take up or starts to pick up things like service desk calls, et cetera, and HR leaders at different size of organizations are going to have more time to really coach managers into their fullest potential.

They're gonna get these questions. And so having that data literacy and that governance and knowing what responsible AI is in terms of being able to answer the questions of the workforce, it's gonna be really important.

Alex: One of the smartest year-end moves investing in yourself. Use those remaining dollars to join your HR community at SHRM twenty six. Learn more at SHRM dot org slash SHRM twenty six.

You know, I think about a lot of what we've been talking about here today, and it really is sort of fascinating. Because I could picture a scenario whereby people think about responsible AI use and how governance falls within the skill set and the toolbox of the HR leader.

More often than not, and obviously we've seen stories like for instance, where the CHRO is becoming the CTO or there's a mixing of the responsibilities in some way, right? Everybody knows the Moderna example, and there's other examples that we're seeing pop up here and there.

One of the things that strikes me when thinking about this data governance and really understanding the data layer of your organization as it relates to artificial intelligence is also about understanding the opportunities that come to life. When you take into account what data is put forth, but then what kind of operations you might have in place to say, okay, here's what I need to have happen. Here's what I would love to understand as the art of the possible. Here's what I would love to understand as how I would leverage the talent that I have in place and how it is that we can both achieve what is the necessary as far as the what needs to happen and the art of the possible.

What's fascinating to me is it all points back to your top skill that you mentioned, which is really understanding those workflows, designing those workflows, and understanding how to prompt for what your purpose and your workflows in those purposes are. So it's, I raised that because in the world of systems, right? We've known for years, and Nicole, you having been at numerous tech conglomerates over the years, you know, this, and a strategist at all of them.

One of the things that stands out to me is the word that we always lost sight of or we always kind of got hung up on in the tech sector was interoperability, right? And just like any other set of systems, any other set of tools, AI requires that heavy duty interoperability and even amongst our own skills, right?

I dare to ask, right? Because I think we, I want to know that, I know we're trying to aim for five, but what's your fourth skill? What's that one that stands out to you? Another one that you think HR leaders kind of either they often overlook it or it's something that they should be doing but aren't necessarily doing. But which one is it that stands out to you?

Nichol: I would say the next one is really AI assisted decision making and data-driven decision making. One of the things for HR and at the top of our conversation, you said, this is such a great opportunity for HR and it really is because there's a lot of points of view that HR leaders have had about really unlocking the potential of a workforce that hasn't had the data for it.

And we are going to be at a place where we actually do have the data for it. The new word of the year is work slop. Because now that many people have access to AI, the volume of what's being circulated inside of organizations like new proposals, new initiatives, et cetera. It's higher than it's ever been.

And actually, in early November of twenty twenty five, the volume, just to give a context, the amount of AI generated content and bot traffic, surpassed human content and bot traffic on the internet. So there are now, there's now more synthetic on the internet than human as of early November.

And so for AI assisted decision making. There's a nuance to it. It isn't just, oh, suddenly you have a bunch of data that you didn't have before. So it's probably gonna be in steps. Like, first we're gonna start to get data around things we haven't had data on before, and that's gonna be really fun.

But then it's like being able to understand the nuance of how to use it, when to use it, how to, when to rely on it, when not to rely on it. Knowing that before you use any technology, you sit in a room with your team and you talk about what the issues are or our three C's.

Bringing that in and really understanding how to use it, it's gonna be like when we learn how to drive cars or when you learn how to ride a bike, it's rough at first, but then you really learn how to use it. So I think that is gonna be the next level skill because it's a easy thing just to use all the data and sort of lose the heart and soul of what someone's trying to do. And so it's like when to bring it in. So it's gonna, it's an art, it's an art, but it's also a skill.

Alex: You know, it also makes me think about a skill that I think is particularly critical that gets lost sometimes. And that's really the true science of future HR, which is really around experience engineering, right? How do I engineer experiences that make it so that people are productive, satisfied, and or engaged in some way and willing to do the three things that we need them to all be doing in our organizations.

One is attracting others. Two is making sure that they are making, keeping their peers communicated and collaborated all the way through and through. And then three is making sure that everyone understands what their clear goals are all the way through in good work, right?

And so I look at this and I say to myself, any good HR professional who has this new tools toolkit at their disposal needs to become and recognize that they are without question an experience engineer. And that means that you've got a little bit of brand and marketing in what you do. That means that you've got a little bit of sales and service in what you do, and that means that you're doing everything you can to generate those kinds of experiences that people will take advantage of and more importantly, see as the kind that were what drew them to the workplace that they belong to.

For me that is the, I've always wanted, and I hate to say this because I know that obviously we both are part of the SHRM team, but one of the things that I've always wondered is, is there an era in which experience engineering is actually the name of this profession? Right? That's how much I believe in that skill.

So yeah, I really appreciate that. I like where we're headed there.

Nichol: Yeah. And I'll add one more, which is just sort of something that I talked to someone about a few weeks ago and it blew my mind a little bit. Is that to the AI decision making. It's as an HR leader in that role, but also in evaluating and supporting other people in the organization.

So managers to be able to also do that. Because if you think about it, there is, we have managers in organizations, and also there's quite a few people who are not managers and being able to prompt and all the things that we talked about is a little bit like there's elements of management in it.

I do not think that bots and people are the same thing. Absolutely. Full stop. I don't, but there has been some interesting research that people who are really good managers also tend to be good at prompting because they ask lots of follow up questions. Why did you do it that way? What about this? Did you think about that?

And so as HR leaders are defining learning and development and raising the fluency of the entire organization, not just HR. They're going to need to translate that AI decision making and sort of AI management to the whole organization because everyone is going to, you need some of these skills to be able to be really great prompters for the business.

And so there's like, everything you and I have talked about isn't just for HR. It's like HR is gonna do it in HR first, but every other department has got to do the exact same thing. So to the extent that they develop that expertise for it, that's how they're gonna be able to be business partners to the entire organization.

Alex: Yeah. You know, I think about that in large part, and it takes me back to a stat that we actually ran many years ago. I was once asked, what is it that is how much of what HR does is actually a function of people, managers and how effective they are and we ran a sort of pseudo study, a really small kind of analysis, and what we found at that point, this was back in twenty twenty three, I wanna say, we found that forty one % of the variance or the variability in how people rate the HR department as effective within their organizations is a function of all sorts of tasks that actually belong to a people manager, right?

So to your point, the more we drive this down into the organization, the more that all the groups within the organization do this, the more effective that not only HR will be, but the more effective that everyone will be in terms of how we serve, not just our purposes and our money objectives, but also our mission objectives, right?

And so it's no surprise to me that we're doing that. And by the way, you taught me a new word. Every time I talk to you, you teach me a new word, which is awesome. Because I remember even the first time that we started working together, you taught me about slip streaming. You taught me about all kinds of stuff, and now you taught me work slop.

It made me think of my favorite example. How many of us have been on a thread, right? Where it feels like people are responding to each other and nothing but chat, GPT responses or responding to each other. And copilot to copilot. I've had that experience to the point where I was like. Hmm. That's interesting. Something's not right there, but I hope it doesn't kill communication that way, right?

Nichol: Yeah, I mean, I think it's like we're learning how to use it and I remember, this is definitely gonna date me. I remember the very first time I saw a cellphone and it was the size of a brick and I was in a restaurant and there was a couple and they both had bricks and they were yelling to their cellphone while they were at a dinner table and it was like before cell phones. And I thought, oh, that's really weird.

And then we had a period of time where people really did talk in shared spaces, in restaurants and now we've kind of moved on to a place where there is sort of a general etiquette and understanding of how to use cell phones.

So what I think will happen with AI is or in this AI world is one I think that people are really gonna value human connection to the point that that's how, so anyone out there who follows this conversation, one of the big things in life is how do you get out of the people pile?

Like, there's the people pile and it's got a big stack, and then there's the people who get extra attention because they've gotten out of the people pile. The way out of the people pile is that deeply human touch. It's going to be establishing connection because we see it with what's happening in recruiting and application right now? It's really a volume.

And so human connection. That's, we're gonna start valuing that more and more and more. And then the second thing that's going to happen is that people are going to really value events meeting live. Because if you weren't there, you don't know if it happened.

And also people are really gonna appreciate, because they're gonna know that there was no copilot involved or there was no chat GPT involved. Because they were right there. And that also, it's one of the reasons why we've designed the AI HI summit this year to be the way it is, is like we're gonna, all the skills that we've talked to you, everyone about, we have live simulations and we're gonna teach you how to do all of those things.

But the value of events of being together is human beings are gonna value that more going forward. Because of these ten message copilot to copilot responses.

Alex: You know, it's funny you mentioned maybe that's a better third C in my space of where it works, right? Because I think when you're thinking about or where it could work or doesn't work, I rather than contacting, maybe it's about connection. Whenever you're connecting with somebody, maybe that's a good opportunity to think about that.

I feel like we've come up with ten different C's. Yeah. I like it. You're brilliant, Nicole. I love it when we get a chance to talk. You're absolutely right. We should talk more often. I feel terrible about that.

Nichol: Well, I'm so grateful to you, Alex. I'm coming up on two years and I also learned something from you every time I talk to you, and it's just so fun. And so as we're moving into this season of gratitude, I'm just grateful to be able to work with you and the rest of SHRM.

Alex: I'm humbled and thank you so much. So let's see if we can do a little bit of a quick wrap up here. Because we've talked about all these exciting skills, right? So we know, for instance, that AI is opening up so many possibilities for HR leaders to make a bigger impact than ever before.

So as you think about where we're wrapping twenty twenty five up and where we're thinking about these kind of skills, let me ask you this one thing. What excites you the most about the future of AI in HR? And what opportunities do you see for leaders who embrace these skills?

Nichol: My passion and also what brought me to SHRM is unlocking human potential with technology. And so I think that the opportunity that really excites me for HR is that for those who lean in and embrace the skill, I mean embrace the tools and also develop the art and the nuance of it.

We finally have the tools we needed to do what our heart most desired, which is to help people find their place in the organizations where they can do their best work and contribute, because that's what the dignity of human work. People want to be a part of something and HR leaders, they come to organizations not to dig through Excels for compliance issues, but to unlock human potential. And so we're finally gonna be able to really deliver on that promise for HR leaders at scale. And that I think is truly exciting.

Alex: And for me, I think the number one thing that it unlocks is really the opportunity to take away things like barriers. Not just the unlocking of human potential, but actually the opportunity to remove barriers. When I think about what AI can do, especially in a talent-based skills economy, there is no doubting in my mind that what it creates is an opportunity for the HR profession to really be the determinant in many cases of whether or not an organization is going to be truly successful and the degree to which that organization is gonna be truly successful.

So naturally I'm biased towards the HR profession having started my career in the HR profession. But I do believe that this is not that first reset. Because I believe we all know that COVID was that first reset, but AI is the lasting reset. It's the lasting component that allows us to think about how this profession drives the future wholeheartedly.

So to me, that's the thing.

Nichol: Yeah. Yeah. Oh wow. So we, I know we could just keep going, but we're gonna stop. So that's it for this week's episode. Thank you for joining the conversation with Alex and I, and we will catch you next time.