Can HR lead AI without being AI literate? A guide for HR leaders

A CEO tells the leadership team the company is behind on AI and someone needs to go do something about it, and the mandate lands on a function that was never set up to lead it. HR holds the widest view of the workforce and the change any AI rollout depends on, yet often waits for IT or finance to hand it a plan. Kristin McDonald, who has spent most of her career in HR technology and now builds AI roadmaps, argues that HR should lead the AI conversation, and cannot until it gets AI literate first.

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How should HR buy new HR tech when there is too much of it?

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Start inside, not in a vendor demo. Before HR shops for a tool, McDonald wants an internal conversation about who is affected and whether the current system already covers the need, since a business partner's request is often something other units share or a capability nobody switched on. When a real gap remains, weigh the return honestly, because a new tool might close 80% of the gap rather than all of it. Integration then decides whether employees get a smooth experience or one more system to jump between. As she puts it, "a huge part of that conversation needs to be about integration."

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What is the most common HR tech implementation mistake?

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Handing the finished system to a team that never watched it get built. McDonald tells HR to document its processes first, then treat the build as training, with the people who will support the system after go-live sitting beside the consultants as it gets configured. Something always breaks at go-live, and a team that knows the setup can answer why on day one instead of pointing at the vendor. Her rule: "you should see your implementation as training for your teams."

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Why should HR lead the AI conversation?

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Because AI reaches every role and every strategy, and HR carries the change-management view other leaders miss. "And AI touches everybody and every strategy," McDonald says. Skills, learning, org design, adoption, and communication are HR's home turf, and they are what an AI rollout runs on. If HR is not invited, she says to build the case anyway: run a skills inventory showing whether the organization has the AI skills it needs, and pair every finding with a recommended action.

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What does HR need before it can lead AI?

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AI literacy, and McDonald's catch is that HR cannot lead what it does not understand. She does not see enough companies building that literacy in the people who need it first. Leaders who cannot explain how the tools work cannot advocate for them, teach them, or drive adoption. Building the skill is unglamorous: experiment, take a course, use Copilot inside your daily email, and learn in a community while everyone is early. Her question cuts to it: "if you don't understand how it works, how are you supposed to lead anything?"

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Where should HR start on an AI roadmap?

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Start with the data before the tool. The oldest rule in analytics still holds, McDonald says: "garbage in and garbage out. It's the same thing with AI." Before pointing a bot at employee questions, make sure the policies it will draw from are documented and easy to reach. Then aim it where it helps most: "You want it to like augment your people. Where can it help them the most?" Early wins tend to sit in places like recruiting, while governance and the build-versus-buy call are the longer game.

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Her final note is permission to be a beginner: "just have grace and we're all learning together." The one move she warns against is doing nothing while the field is this young.

Logan (00:00): Kristin, is there anything else that you would like the audience to know about you?

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Kristin McDonald (00:03): Well, that's a great intro. I would say I'm an HR tech nerd at heart, and it's been most of my career. I don't want to say how many years, I don't want to put that out there, but it's been most of my career working in HR technology. I love it. It's a passion of mine and one of my favorite topics to talk about. And I love following everything that's happening in that space, and it just keeps getting wilder and wilder. It's a fun ride.

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Logan (00:29): What have you seen? What are the biggest trends and differences that you've seen lately?

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Kristin McDonald (00:35): Well, of course, AI, you know, that's one of them. I mean, yeah, I don't think you can go through a conversation with technology without talking about AI. But I think trends are just, things continue to evolve as usual. And it's nothing new either, right? As long as I've been in HR technology and following this space, there is always,

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Logan (00:38): Talk about AI.

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Kristin McDonald (00:58): Always trends, always things that, you know, whether it's talent acquisition is the big trend of the tech season, or whether it's employee experience. You know, it just ebbs and flows, and there's so many vendors out there. As technology does evolve, it's a lot to keep up with. So I think the trend is just the fact that it's almost overwhelming now at this point.

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And with the AI conversation, how does that weave into your current tech stack? Because that kind of changes the equation a little bit. Does their current tech stack have those capabilities? Is it on their roadmap? Do you need to build versus buy? So I think that is very much opening the door for a lot of questions, and a lot of people just not knowing, kind of, where does this go? And then how does it affect your roadmap?

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Logan (01:56): Well, let's start there. So the landscape is shifting. I mean, one of the hard things about tech in general, like I spent a lot of time buying MarTech. And it's like, what do you actually buy as there's a ton of tools coming in? And how do you get tech that actually solves business problems, rather than seeing how cool the technology is and trying to fit a business problem? Really, it's how do you purchase tech into your tech stack that's strategic to where your actual tech roadmap is going?

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Kristin McDonald (02:30): Yeah, it's hard. Like, you know, do you want the latest shiny new thing? Because there's a lot of cool tech out there. But it used to be where people would have these conversations that would include, you have tech sec just for this space, TA, or just for compensation, right? And then that evolved to consolidation and these bigger ERPs like Workday and SAP that now allow for you to have all of those capabilities within the system. So people started letting go of texts, other tech stacks, whether they have just a few.

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So as I think about technology and I think about the conversations, yes, it's aligning with your business strategies and the goals, but it's also, if you are looking at new tech, a huge part of that conversation needs to be about integration. You don't want to just look at a new tech without it being able to integrate with current tech and have a seamless experience. So at the end of the day, we have to remember, especially in HR technology, our end users, our employees, our managers, and they need something that's easy to use. And it's not jumping from one system to the next.

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So quite often, you know, if you are saying, okay, I have this business need, maybe talk to your current vendor. If you feel like it's not addressing that need, maybe it's on their roadmap, maybe it's something you don't even know that they can do. It's really having that conversation and being thoughtful about it. Because also, we know budgets are tight. So I think asking for new tech is also a hard part of the conversation.

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Logan (04:04): Yeah, especially right now. I mean, before we jumped on here, we were talking about just tech purchases in the macro environment. And I don't think anybody can escape what's out there, but that's not what we're here for. So you talked about integrations and choosing tech that integrates well. Like if you're thinking about adding a tool, what are the three questions you should be asking, or five questions? What are the key questions you should be asking before you do that, before you add a tool?

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Kristin McDonald (04:17): Before, definitely. And you're saying more so like internally, like the question you talk about internally first, or as you're talking? So sometimes I see this a lot too, where people, whether that be business partners, people in business units, HR COE, is like, hey,

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Logan (04:43): Correct.

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Kristin McDonald (04:56): I want to do X, Y, Z. We're going to go out and we're going to look at tools that can solve this problem for us. And it's very easy for them to just say, I want to go talk externally. But there needs to be a conversation internally, where you don't want to just buy it for one segment either. So I think that's the other thing, is who is being impacted, who actually receives the ROI of this tool.

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Because things can happen, especially in HR. HR business partners, for instance, they support a client group and they'll have a very specific need. And they think that their need isn't a need that other business units have. So they think, when they have technology needs, that it's just their own need, when that may not be accurate, right? Like another business unit, all employees, could benefit from it. So coming back to the table and being, we have a business unit that has this need, but let's talk about, could other employees, like employees or managers, could they utilize this? Could this help us in some way? Do we already have this capability, or do we maybe not have something turned on? Right? Because that could also be the fact that, you know, technology comes with a lot of functionality. Maybe things aren't turned on because at the time it wasn't found as a need.

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So it's really just having an internal conversation. You know, what is the goal? What's the outcome? We don't want it to be just necessarily one population that we're looking at that has this new work and potentially be scalable and needed by more. And then if there is a gap, let's do that analysis and see if the ROI is worth going out to purchase new tech, or look into new tech. It may not, the ROI may not be there. Like maybe you can get to 80% of the gap, maybe not a hundred percent of the gap between what a new tool could do versus your current tool.

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And then the other thing is, even if you want to go look at the new tool, make sure you're seeing where there is the integration. Because I still think that's very key. Even if you purchase a new tool, you don't want it to be a fragmented experience for the employees that you're trying to actually probably make things easier for, you know? And then of course, you just always want to make sure that there is a true measurable outcome, like ROI, that's impactful enough that it makes it worth it.

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Logan (07:19): Yeah, and on the integration side, I've had experience where there was an out-of-the-box integration, but it wasn't very robust. So we ended up having, later, unbeknownst to us, to do a custom integration anyways. And then it's like, gosh, we would have known that. So that's such a key piece.

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Kristin McDonald (07:35): Well, that's why you bring your HR, you know, your IT friends along for the ride. They need to be part of the conversation.

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Logan (07:50): Yeah, and they'll know exactly what needs to happen. And they're going to have a whole set of questions. You just hope, if this is your preferred vendor, they know how to operate through that environment, because they'll get all the tough questions asked.

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Kristin McDonald (07:55): Yes. I'm not that technical, as the true technical people. They know the terms, they know what to ask for. They know what you know, but they need... so they are definitely a big part of the conversation.

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Logan (08:20): Exactly. I want to go back to something you had mentioned around point solutions and then going into all-in solutions, and how, you know, we see these ebbs and flows, I think, in tech in general, where everybody's going to point solutions and then you consolidate it into all-in-ones. Do you have a preference for when you would go for a point solution versus all-in-one solutions?

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Kristin McDonald (08:50): I think it really comes down to, does it really address a huge need, or like a business problem? Otherwise, most of the bigger systems these days have enough of what people need for their processes. You know, whether that starts with talent acquisition and onboarding, all the way through talent development and performance, and like, the whole employee life cycle. It's very hard-pressed these days to find a tool that doesn't have those capabilities that are bigger.

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But to be fair, that also is expensive. So there's going to be smaller companies that can't afford those bigger, like, Workdays, SAPs potentially. So maybe they have to have smaller tools, or points.

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So it just depends, right? I mean, it's possible, it allows for everything to be in one place. Data is in one place. It's easier to grab what you need, like with your data warehouses. Or if you're feeding data elsewhere, you're not getting it from different places. I can't tell you, like back in the day, how to create like a map of where all the data is coming from, and to go into a secure data warehouse. It'd be like all these different systems of where the data is: my talent acquisition data is here, so I have to grab requisition data to pull in here, my worker data is here.

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Now, with the bigger solutions, and there's even smaller solutions now that have most capabilities that you'd need within HR, your data is all in one place. Your processes are in one place. HR does not work in silos as far as processes. What you're doing in talent acquisition, there's impacts to your hire process, talent management. It's very hard these days to find processes that don't impact other areas.

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Logan (10:38): Yeah, that's a good point. And I have drawn those maps of where all of the data flows, and it is insane to try and map it.

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Kristin McDonald (10:45): Yeah. Messy.

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Logan (11:05): But I think the point here for the audience, or a point, I shouldn't say the point, is just, as you're thinking about having to communicate to the rest of the business and your technology, it's a complicated thing to do, and you have to be pretty thoughtful about it.

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So let's say you've brought in... I want to transition a little bit to, so you've brought tech in and now you have to roll it out, get it implemented, get it used and make it effective. I kind of want to see, what traps or pitfalls do you often see once, I mean, it's called once the contract is signed, and then you start implementing new software?

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Kristin McDonald (11:36): There's a couple of things, and I think this is true regardless of its implementation, a full-blown of new tech, or just if you're bringing or changing processes within your current tech. One, you've got to know what your processes are. You can't go in and say, I want to implement this, and just kind of, likely, will, open-ended. Yes, the system will have its own capabilities, but you need to understand what your processes are in general, right?

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A lot of businesses do not have their processes documented and mapped. They don't even know what they are. And then, where do you make sure that you're not leaving any gaps, right? That when you're going through your implementation and you're thinking about your processes that you're developing, that you are being considerate of everything that you need to. It's a lot of work. If you were to take everything you've built for your global workforce, for instance, different countries have different compliance, or different segments have different processes that they follow. It's a lot, right? So it needs to be a very thoughtful and thorough implementation, to make sure you have everything figured out and know everything that needs to be configured.

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And while you're doing that, involve your internal teams. The big one, and I saw this in implementations, especially with like Workday: when you are not making sure that you, one, have a team that's going to support the system post go-live. And two, you're not training them alongside. Like, you should see your implementation as training for your teams, and they should be there right alongside your implementation team, those consultants, working alongside with them, seeing how systems are being configured, like all of the back ends. So that once the system gets handed over to them, they know how to not only maintain it, but also optimize it. And they can know enough about what happened during implementation that when you go live, and this will happen no matter what, things aren't going to be 100%. Things will not be 100% working. Hopefully you tested everything, you did very thorough testing. But sometimes things happen.

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You need to be able to answer those questions, like, why isn't this working? You can't be sitting there going, I don't know what they did during implementation, I don't know how they configured it. That's just, you're not going to get adoption. People are going to be like, I don't know if I trust you, I don't know if I trust the system, because they're not going to see it as a you problem. They're going to think it's like the tech problem, potentially.

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Logan (14:13): Always. It always comes down to the tech problem. And that can be frustrating. When you go live and you have bugs that you have to work out, and you always do. I worked for a company and the CEO would release product releases, and he'd be like, well, you just hit release and then duck under the table and hope that it doesn't go too bad. And I just always thought that was such a funny line.

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Kristin McDonald (14:14): Cross your fingers. Yeah. It's hard, you know. Everybody's so busy during implementation, of course, they have their own day jobs. You roll out a new tech, it has to be something that you feel confident that your teams can support post go-live. And technology is always evolving. It's not how maybe it used to be, when you didn't have ongoing releases, that you need to know about the system so that you can know, like, this is where this release impacts this, or this is what I need to do to configure. There's constant releases, constant updates. Technology is changing so fast. You have to know the system inside and out so that you can handle those.

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Logan (15:24): And do you recommend that the support lives within like an IT function, or do you have a support function for a tool within HR?

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Kristin McDonald (15:37): That question has come up again lately. Like, where should HR tech sit? And there've been some companies that have started to put all tech under one organization, whether it's finance tech, HR tech, travel and expense. They're all sitting under one, like the chief tech officer or something. But I still think there's more pros and needs for, if it's a technology that is paid for by HR, it's managed by HR, it's supporting HR processes, even though the employee is the end user, I think that support should sit under HR, and there should be a dedicated team.

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There needs to be people that understand the system. They need to have strong partnerships with process owners, with their stakeholders in HR. And that comes much more easily if you are in the same organization, you're up to the same leader, you're hearing what's going on within HR, but also the business. And you're supporting a technology that you need to have strong partnerships and understanding of what the needs are. It's just much easier when you're sitting in that organization. I think that supports all that.

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Logan (16:57): Yeah, interesting. I've heard a few times now, companies moving everything under one area for tech. And I don't know. I mean, interesting. Some of that stuff really just depends on the org, right? Like the org setup. And you can't always have one size fits all. But I would agree with you. I know from the marketing tech side, somebody in marketing has to know what's going on. Like somebody in the department using it, or what the actual thing is doing, has to know what's going on. Otherwise, it ultimately then becomes difficult for execs to then figure out what's happening and make business decisions, I think, as well. So you have to have some way to manage that up, all the way.

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Kristin McDonald (17:44): Yeah. And it's about, you understand the terminology, you understand the processes, so it's much easier for translation, right? And being in HR technology, sometimes it can feel like you're talking a different language when you're talking to like your HR COE or execs. They're like, what do you mean when you say configuration, or sandbox, or a business process, or something that's more, you know, tax. You have to remember that translation sometimes. But it's much easier when you can translate it in a way they understand, because you're talking about like their world. You're talking to a talent acquisition person and you're talking in their terms. It's a much easier conversation.

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However, with that being said, I can see why there's merit to putting everything under technology, because you don't want people buying tech and not having a larger enterprise strategy around tech, and making smart tech decisions, right? And with AI, that's probably changing the conversation also. Because when you think about utilizing AI in the organization, you say you want like a knowledge agent, or an employee agent, where it can answer all my questions. That's not just HR. You're getting information from your travel expense system, or maybe your ServiceNow, where the question could just run the gamut of what information they're looking for. And an employee is not going to see it as talking to... they're just trying to get their questions answered. So you can understand why, if you look at something more enterprise-wide, you probably need it to all be kind of centralized in some aspect.

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Logan (19:31): That's a really good point on the AI agent. And if you want to roll something out for HR, really you have to think about the employee experience, because they don't want to go to three different AI agents. They don't want to go to an Ask HR agent, and an Ask Product agent, and then an Ask Marketing agent. They want to go to the company's agent, ask, and then get the answer they need from everywhere.

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And so that's a really good callout, and a really good segue to talk about probably the most interesting topic that we're going to talk about today, and that's AI. Probably not just in HR tech, but in general. And I guess, in what we know now for this year, I mean, when I started really dabbling in it in like January, to now, it's like entirely different of what's happening. For AI and HR, what are you seeing and thinking about that's like actual usable stuff now, versus, you know, just people talking about it, like writing a post on LinkedIn?

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Kristin McDonald (20:37): The conversation's constantly changing and getting more complicated by the day, it shows. So I see it sometimes as twofold, the way we have to think about it in HR, because I think we forget that HR should be leaders when it comes to these kinds of transformational changes, right? But in order for HR to pave that path or lead that path, they have to be AI literate. Like, they have to have that capability. And I don't know if we see enough, or hear enough, about that capability being built, or that investment being made by companies, on the people that probably need it at least first, right?

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If I now think about what that means, I think you want employees to embrace that AI, you want employees to utilize AI, but you need your leadership, your managers, your talent, your people that are leading talent and creating talent strategy, to be as well versed, right? Because if they can't understand it, they can't advocate for it, they can't teach it, they can't help with adoption. So I think that's a really huge part, is that capability building of HR professionals and AI.

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Kristin McDonald (21:57): And then it's about, all right, we know that it's chaotic out there regarding CEOs. They're like, go do something with AI, we're behind the curve. Like, they feel like we're not doing enough to be, like, have an AI roadmap, or using AI. Well, it's not like a one size fits all, you know. It's what would make the most sense. You should look at, what are our processes today? Where can we automate? Where do we have gaps, or places where it can have a really big impact based on our business, not other businesses? They might be doing something, but that's maybe because it makes sense for them, and then we'll have that impact. And so it's not just you push a button and AI happens. I think that's the thing. Do people... is that just... I think that's a misconception of what it takes before you can even make a decision on a tool.

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Logan (22:58): Well, and if you think about, I mean, we've lived in being able to build business process workflows for, you know, with the kind of, I guess you can call it the SaaS revolution of the last 15 years. And how many businesses don't do that because of how difficult it is to do automated workflows, and how hard it is for businesses to do it? And then to flip a switch on AI, it's going to be as difficult, I would imagine. And if you see somebody posting all the great stuff they're doing with AI, it could just be that they created a slide with a workflow on it. It's not really happening the way that they've said. You never really know.

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But I wanted to touch on something you said. You detailed a little bit of it, but so why do you think that HR should lead in this AI knowledge, and bringing AI into organizations? I haven't heard that before, and I'm just curious.

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Kristin McDonald (23:34): Yeah, that's true. When I think of HR, and I think about them being a strategic partner, that means that they need to have that seat at the table with any sort of big transformation, change to the talent strategy or business strategy, right? Because people are such a big portion of any of those changes, any of those strategies. And AI touches everybody and every strategy. So not only is it how you're using AI, you know, as an employee in your day to day, or if you work for a company that's creating AI tools, or looking to build or buy.

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You also are, if you are looking at your talent strategy, what AI skills do we need to have? But then you, as an HR user, also will need to use AI as well. So just think about the gamut of what your role in HR encompasses. Knowing if AI is such a big part of the strategy, you want to have that seat at the table. You need to be seen as a true partner in creating that strategy. Whether it's helping identify, do we have the skills that we need within the organization to be able to take your roadmap, your strategy with AI, forward? But in order to do any of this, you need to understand, I think it's just as basic literacy. Because I think if you don't understand how it works, how are you supposed to lead anything?

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Logan (25:34): Yeah, that's a good point. I think the really interesting thing that's out of this, that not just HR folks, but business execs and anybody should be thinking about, is that AI is going to impact your people. Like, especially in office-based work, it's absolutely going to have an impact, whether they're using it or any of that. And so HR should be in those conversations.

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I guess I have two follow-up questions to this. The first is, let's start with, how do you think HR folks should become more AI literate? What things can they go do, outside of, I'm just going to say maybe this is the best place to start, but outside of ChatGPT or something like that? I mean, obviously that's a good place to be, but what advice do you have?

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Kristin McDonald (26:22): That's a hard one. It's like any of us, right? How are any of us learning AI? So much of it's experimentation, trying things out. There's a ton of courses out there, free or whatnot. I do think with AI, it's basic literacy of what it means when you talk about gen AI versus agents versus, then like, you know, underpinning that, LLMs, natural language processing. Just general knowledge that you need to have as a foundation. And then going out and experimenting. Yes, ChatGPT is a great way. If you have Microsoft Copilot, really start utilizing that, understand how it works. Like, how does it get incorporated into your day to day? Because the other thing I think that is important about this is that AI is changing the way we work.

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Like, don't even think about it like in your role where it can help with automating some tasks, or helping you. You can go into Outlook, for instance, if you have Copilot, and you can say, summarize my emails, where am I mentioned, where I have an action item. There's so many things that just help you in your day to day that is important as part of this.

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And you sometimes just have to play around. Sometimes I think there's a lot of validity to just having a community, which is a little harder right now. I think the HR community of AI is a harder one. There's people out there, they're doing it, they're trying to lead the charge. But I think that's where there could be so much more value, because we need to learn together. It's just new for so many of us, and you just kind of need to learn together and share what's working, what's not. What did you try that you had lessons learned from? In building that community, I think, would be really helpful.

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Logan (28:18): Yeah, the community aspect's good. And I like the callout that we're all just learning together, and learning is hard. Learning is very, very difficult. So you don't want to downplay that at all.

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The second follow-up question I wanted to ask was, so we talked about HR needing to have a seat at the table with execs. If people in the organization are saying, we need to use AI, how does HR make that case? To alert people that, if we're going to start going down this really big road of, we really want to get deep into AI, how do they communicate that we need to think about people, HR needs to be in there? How do you make that case? What advice do you have for people to make that case, to ensure that you have representation at the table?

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Kristin McDonald (29:17): When people talk about AI, it's not just a tool, right? And it kind of goes back to what I was saying earlier. I think HR has a really good viewpoint about the change management aspect of this, right? That maybe other leaders aren't thinking of necessarily, where HR has this bird's eye view, and especially their role being focused on talent strategy, but also business, right? Part of their purview is also to make sure that they're creating a talent strategy that aligns with the business strategy.

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And I think they have a unique perspective of everything that's needed as part of this change management, whether it's the people, the skills, right? Think how much they know about what that looks like, whether it's from an external market perspective, or what you have internally. They know what we can do to understand that, and what that looks like. They can talk about learning, right? If we want to look at upskilling people and getting them basic AI literacy, here's a strategy. If we know that we want to figure out AI use cases, because we want to have that conversation about where it even makes sense, that is based on probably people's roles. Again, HR knows, with org design and looking at roles. There's just so many touch points where they understand the change management aspect of it. And then of course, adoption and communication, and everything that will come with this, from end to end.

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So if you're not getting that seat at the table, put that information together. These are the things we need to consider to bring to the table, and the reasons why. I always say this: what's the worst that can happen? They say no. At least you brought the perspective to the table and shared that. And maybe you have some recommendations. I always think that's something that's really impactful, is it's not just sharing information, we need to do this, but actually give actions. In order to do this, we'll need to go do this. Or, we do not have the skills. Maybe even do that skills analysis of, let's go out and find out what employees have used, use AI, know about it. If we know we want to do X, Y, Z, we can do that skills inventory, and we can share that as a data point to be like, we do not have the skills. That means we need to either upskill or go look externally.

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Logan (31:57): And you're talking the skills, or AI skills, across the org in general, or just within HR?

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Kristin McDonald (32:04): No, in general. You know, the skills conversation has been around for a long time too, right? So there's also been a lot of work done to capture worker skills, and also the demand. So both the supply and the demand of what's available to the organization. If you need to do an additional kind of survey, or whatever your process is internally, to capture any updates, now's the time to do that. Did people just recently take some AI courses? Have they played around with AI? Is it a goal? Like, look at their development goals. Has anybody put in a development goal about AI and shared progress? There's other ways you can get to that, but I think that's an important part of the conversation, and that HR has access to, or at least is able to create a strategy to get access to.

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Logan (32:58): Yeah, that's a really good point. And going back, everybody is learning. So even if you have people that are on the forefront of AI, they're still learning. So it's not going to take that long for everybody else to catch up, because you haven't been doing it for that long.

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And I really like the point about putting together courses, or helping empower other employees to learn AI, and doing that as a good strategic initiative. Because, as you said, HR has got the purview of this and knows, and that's one way to kind of help be on the forefront of that. And a lot of our audience works for private-equity-backed companies. And I'm pretty sure a lot of the private-equity-backed companies are being asked how to use more AI. And so this is a very good, very tactical way for HR to get involved in that, knowing that they are going to be asked, in that environment, in those high-stakes environments.

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Okay, one last question on AI. I feel like we should have spent the entire time on this now, after we got through this, because there's so much more, but...

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Logan (34:08): AI roadmap. So you're deep in the thick of doing AI roadmaps. What should people think about, step by step, in adding AI into their tech roadmap, their HR tech roadmap?

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Kristin McDonald (34:19): I think it's about doing your due diligence first. Remember the old adage, even when people analytics was the big trend, garbage in and garbage out. It's the same thing with AI. If you have bad data, if you don't have the information that it's going to feed these agents or these bots, you're going to, one, you're not going to get the ROI you're looking for, and employees are not going to trust the AI, right? Because there's no good data to begin with to use them.

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So I think it's looking at your data. And that can include things like going back to the knowledge agent, or where employees are going to ask questions. Do you have your policies documented? If employees want to go ask questions about their vacation policy, or maternity leave, or what the travel expense policies are, do you have those documented? Where are they stored? Are they easily accessible, that the assistant or whatever you're building can access them, and then employees can get that information? So you need to do a lot of background work and infrastructure work to even know if you're ready, based on what you want to do with AI.

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And the other component is, you can't throw AI at everything either, right? Like, that doesn't make sense. You want it to like augment your people. Where can it help them the most? Where are the real opportunities where things can be automated, to allow people to be more strategic, right? So there's a lot of work that needs to be done to even understand what that could look like. What are people's roles? What does their day to day look like? What are they doing in their role? Where can we have a lot of impact? And I think that is going to be a very long roadmap.

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So when you think of that work, what can you do now, maybe, that will be an impact or value add, right? The bigger use cases right now would be like within talent acquisition, right? Like candidates being matched to roles. There's just things that are probably easier to just do. So maybe focus on a couple of those while you're doing this other work of other ways you want to incorporate AI.

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And then the fun conversation, that is very hot but not hot, no one wants to talk about it, it's like governance, you know? Like, how are you making sure it's ethical? What are your processes that you're putting in place? Your vendor is going to have processes, but you need to also have them internally. That's going to be a lot of work too. So it's almost this, it's the long game, but there's also things that you could probably do now that have impact. They're just easy, probably because maybe your vendor has them already, right? There's a lot of AI that's available now in a lot of the technology that people have. So what can you turn on now to get people more familiar with utilizing AI, see how it works, while you're looking at other use cases or opportunities within your organization?

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Logan (37:39): Yeah, I mean, governance is a big thing, because you can't just have everybody having rogue, consumer-style ChatGPTs and uploading company trade secrets to get help with stuff. And they're probably doing it unbeknownst. It's not anything other than, I'm trying to get stuff, but making sure that you have tools for them to be able to do that in safe environments, like Copilot, I think, is why everybody uses that. It then has the security and the data privacy that you need. So that's a good thing to think about.

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Kristin McDonald (38:10): Right, which is a very important conversation. I think that's why the build versus buy conversation is also a big one. Because when you build, you can control a lot of that, right? You're not as... I don't want to say you're at risk, but you are at risk when you buy, right? You have to make sure you're doing your due diligence with the vendor, to make sure you know what their processes are, how they're auditing. All that work has to be done, so you can understand that. Because, I mean, we know there's already lawsuits out there of how AI is working.

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Logan (38:50): Yeah, I had a tech person that I worked with years ago, and he had a sticker, and this was kind of in the heat of the cloud debate. It was like circa 2015, and people were still debating cloud. And the sticker just said, on his computer, the cloud is just somebody else's computer. And so, like, thinking about, you're just uploading onto... and obviously there's companies that take really good parameters to make sure that it's not that, but in the context.

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Kristin McDonald (39:21): Yeah, it's true. And there's also so much uncertainty right now, and that trust hasn't been, I don't want to say developed, but that trust isn't there yet. That's going to take some time. So...

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Logan (39:36): Yeah. Well, this AI section, I think there is a ton of great stuff for everybody listening, especially if your leadership team is asking, how can we bring more AI into the organization, not even just in the HR function, and how you can be a strategic partner at that table. Kristin, is there anything else you would like to leave the audience with today? Any other parting advice?

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Kristin McDonald (39:39): Just have grace, and we're all learning together. Like, don't feel like you're behind, or if you're just playing around, or if you're doing something. We're all in this together, which is both a good thing and a bad thing, maybe. But also, we're going to learn so much. And I don't think there's any sort of... if you're here, but other people are here, that doesn't mean anything. At some point we're all going to catch up, you know? But I do think, don't not do anything. I think that's the worst thing you could do. I think if you're just experimenting, if you're just trying to learn, that sometimes that's a leg up right there with AI.

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Logan (40:43): Yeah, that's great advice, Kristin. And I want to thank you for taking the time to join us today and talk through tech and AI, and how everybody is learning together and should be learning together. And last thing is, where would you like the audience to connect with you?

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Kristin McDonald (41:02): Well, you can find me on LinkedIn. I would say that's probably the best place to connect with me. And I'm always looking to connect and learn from each other. I'm learning just along with everybody else. So find me there.

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Logan (41:15): Great. Awesome. Well, we will link that in the show notes. And I want to thank everybody for sticking around and listening today. Thank you.

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Kristin McDonald (41:23): Thanks, Logan.