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MIC'D
The AI‑Ready HR Leader
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HR is staring at a crossroads where AI is no longer a headline but a daily reality shaping how we recruit, support, develop, and plan our workforce. We start by celebrating new members and incoming board leaders, then move straight into a candid, practical guide to using AI with wisdom, not hype. From resume parsing and candidate matching to chat-based HR assistants, policy summaries, and risk-sensing analytics, we map the real use cases you can deploy now and the pitfalls to avoid.
The heart of the conversation is governance. We dig into data privacy, bias, explainability, and the growing regulatory landscape, making it clear that employers—not vendors—own the outcomes. You’ll hear a field-tested story of automation turning eight hours of toil into 30 minutes of oversight, and why that mindset shift matters for every HR leader. We lay out guardrails you can use immediately: minimum necessary data, human in the loop for high-impact decisions, and radical transparency that earns employee trust instead of eroding it.
We also tackle the human side. Most jobs won’t vanish, but tasks will change fast. Reskilling cannot be a slogan; it must be funded with time, training, and manager accountability. We frame HR’s evolving role as interpreter and architect of decision design, translating algorithmic signals into fair, defensible choices. Scenario modeling, forward-looking analytics, and AI literacy become the bridge from reaction to strategy. And we close by redefining human advantage: let AI handle the predictable while people lead with creativity, judgment, and empathy.
Ready to lead the future of work with clarity and care? Follow the show, share this episode with your team, and leave a review with one action you’ll take to build better governance and trust around AI.
New Members Welcomed
SPEAKER_00Naira would like to welcome the following new members Sean Braden from PNC, Angela Young, Lutheran Social Services of Indiana, Alexa from Ruroff Mortgage, Cody Woods, Barnes and Thornburg, Allison with Marathon Health, Keisha with Marathon Health, Brian Cromwell from Endeavor Talent Solutions, James with NCW, Lauren Tucker, Blue Scope Recycling and Materials, Ron Bortner with CSP, Matthew Storm from Indiana Tech, Julie from Multimatic, Colette Schlegel from Multimatic, and Kerrigan Benilla from Multimatic.
SPEAKER_02Welcome to Carrie Isley, who will be joining the Naira board as program director in 2026. Carrie, tell us about yourself.
SPEAKER_05Thank you for having me. So yeah, I've been a HR for going on about um 20 years, but I'm married. I have, and if you believe it, two grandchildren. But I received a bachelor's degree from Indiana Tech with in business management with a concentration in Hustently received my graduate certificate in HR as well in Indiana Tech. And I've always lived and worked in the Northeast region and look to continue that and look forward to being Sarah. So just to kind of talk about a little bit further in the journey, I like I said, I've been in HR for going. Currently the HR business partner at MedPro Group, which is a medical liabilities organization. Previous to that, I to my current role, uh MedPro Group, I worked in various HR roles, long-term care, and health care through the years of passion for working in HR and the aspects that that come uh come along with that. I wanted to be on the board not only to help further promote our chapter, but bring additional value and utilize my existing knowledge to help where I thrive, really. Being the programming director starting in J, I feel I can continue the tradition of bringing excellent content with value centers and the information we gain from them. And when it comes to HR, the laws continue to change, right, and expand. So the expansion expansion from HR departments within organizations can be tough. So it's important for NIRA to continue to help our local HR members stay knowledgeable and keep on going change changes we experience every day.
SPEAKER_02So what's your favorite part about NIRA, Carrie?
SPEAKER_05How do I pick just one part? I don't think I really can. You know, besides of course the things and the content that comes available from the great presentations that we get to experience. Um it's the opportunity to network with other people in HR and talk about our our current issues and challenges or talk about the successes we've we've experienced and learned from each other. I've always enjoyed the annuals, of course, and especially the holiday celebrations like the one we just had this December.
SPEAKER_02There are always a lot of Do you have anything else you'd like to share with our listeners?
SPEAKER_05Um no. I just well, I guess one thing is if you're not a member of Naira or Sharm, I encourage you to to become a part of NIRA. Make sure you attend the events if you're not already doing so. Come on, love to meet you. I'd love to connect and um experience, help you experience what I have already experienced in the presentations and the content that we can learn from each other.
SPEAKER_02Thank you for your time today, Kiri.
SPEAKER_05You're welcome.
SPEAKER_02Welcome to Emily Kumfer, who will be joining the Naira Board of Directors in 2026. Emily, tell us about yourself.
SPEAKER_04Hi, Mike. Thank you for having us and having me on board. A little bit about me. I am a teacher department of one at Skypoint. I originally from California out to Indiana to play awful Indiana tech. I now reside in the Fort Wayney area with my husband and our beautiful children.
SPEAKER_02So, Emily, why did you want to serve on the Naira board?
SPEAKER_04I'm super excited to serve on the Naira board team. Really excited about networking, connecting with others in the field to be able to help strengthen our HRT.
SPEAKER_02How long have you been part of Naira?
SPEAKER_04I've been a part of NYRA for almost three years now.
SPEAKER_02And what's your favorite part of Naira?
SPEAKER_04My favorite part of people and the community and the amount of inspiration and ideas from it. You know, going to luncheons and you are talking to professionals and they might bring up an idea, and the idea just sticks in your head, and you can kind of bring it back to the T or to help.
SPEAKER_02Do you have anything else you'd like to share with our members?
SPEAKER_04No, I'm just really excited to be part of the board. I'm looking forward to 2026.
Board Appointment: Valerie McCain
SPEAKER_02Well, thank thank you for your time today. Yeah, thank you so much again for Welcome to Valerie McCain, who will be joining the Naira Board of Directors in 2026. Valerie, tell us about yourself.
SPEAKER_03Hi, Mike, thank you. To be on the board. I am originally from Fort Wayne, and currently I'm the owner and consultant of Hope Advisory for a boutique HR firm advising in small business where we also offer operation for I'm a giant nerd at heart of everything and anything HR the good, bad, the ugly, and I'm there.
SPEAKER_02Why did you want to serve on the board?
SPEAKER_03I've been involved with Naira for over 20 years. I was a returning student to IPFW at that time and got involved in the term student chapter as the student. I did different HR with the group and introduced to NYRA by professors and the professional environment that I could learn from other HR professors. You know, HR is a very profession, especially if you are an HR department of one. There's many of us out there that have been or are HR department. So it's a great place for you know people to come to talk about the important topics, to receive the great education, to network with other HR professionals. And I want to help continue that legacy and mission of that has been created over the years. I know we're a a great large teacher, and I'm looking forward to working with the other bright and brilliant people on the board. For recently, it was a great time to have kids that are older and in the the day in and day out, and you see people to practice and all of that. I'm I'm definitely ready to to go all in with Naira.
SPEAKER_02And so you kinda you kinda mentioned it earlier, Valerie, but what what what's your favorite part of Naira?
SPEAKER_03Lunch. No, I'm kidding. I do keep our our lunches that we have. It's a great way to to see peers from college, peers from other companies that we've worked at before. The monthly networking events are fantastic to get FaceTime with other individuals. As a Sherm certified profession, I love Naira because I've been able to continue to expand on my education with the different speakers that we've had, whether it's the leaders, the legal easy webinars, the amazing conferences. I think that Naira has so much to offer to Cindiana as far as advancing the HR profession and great, and I I love being a part of it.
SPEAKER_02Well, thank you for your time today, Valerie.
SPEAKER_03Yes, thank you. Thank you for having me. I'm really excited to to see you after.
AI, the Workforce & the Role of HR
SPEAKER_02Welcome to the program. Today we're going to talk about AI, the workforce, and the role of HR. Welcome, Ed.
SPEAKER_01Hey, glad to be here, Mike. It's been a while. I'm glad to be back in the saddle with you, man.
SPEAKER_02Yes, it's very nice. It it's been far too long.
SPEAKER_01We're we're excited to get this podcast back on the road. We have a lot of important topics to talk about, and we hope that you as a listener get something from this because me and Mike were very intentional. We we do this because we love this. But if we can if if we can educate and and help maybe spark some interaction and conversation around important topics, that's our goal.
SPEAKER_02Today we're going to talk about AI. So let me first define what artificial intelligence is. AI is software that performs tasks that normally require human judgment by learning patterns from data. In practical terms, AI does one or more of these. It classifies spam versus not spam. It predicts who will churn what will sell. It generates text, images, code, it optimizes, it routes pricing, schedules, and automates decisions at scale. People have talked about the percent of jobs impacted or that will be eliminated because of AI. And research from organizations like McKinsey and Company and World Economic Forum shows 60 to 80% of jobs will have at least 10 to 30% of tasks impacted by AI. Five to ten percent of the jobs are likely to be fully automated end to end in the near term. Most will impact task transformation, not elimination. So is there an adaption curve? Well, it took 10 years for cloud computing to reach mainstream enterprise adoption. It took 15 years for the internet to reshape most industries. Generative AI reached 100 million users in months.
SPEAKER_01And when you look at those numbers, it brings a reality, Mike, that AI isn't, it's not coming. It's already in your organization. And my daytime job, I I'm a recruiter. So I own a recruiting agency. And I just spoke to a candidate yesterday. I and I'm I want to tell you a quick story. So I a lot of the recruiting I do is very technical engineering related, and we do other things, a lot of skilled trades. But um, I spoke to a software engineer yesterday, and he told me a story where when he was early on in his career, he had a job where basically he was responsible for keeping a very large technical environment running. And he told me it was essentially roughly 200 Linux servers in a data center. So basically think hundreds of machines that run business critical applications behind the scenes. And a lot of his day-to-day, it was repetitive. I mean, things like monitoring systems, checking logs, restarting services, running maintenance routines, and essentially fixing the same type of issue over and over. But but if when when he accepted the role, instead of just accepting that as the job, he started building automation around it. And and you got to keep in mind that this is before AI really started taking headway. So naturally kind of attributing AI to and with automation. And so what he did was is he wrote scripts and he wrote tooling that could basically automatically handle most of those repetitive tasks, actually turning manual work into a reliable process that they can lean on. And and what he described was is he he described automating it to the point where what used to take eight or so hours literally took him 30 minutes in one day because the system was doing the repetitive work for him. And so I think here's the important part. His manager nor he reacted with fear. Matter of fact, they both acknowledged how valuable it was because automation it didn't just save time, it reduced errors, it improved consistency, and it made the environment more stable. So if we take a step back, we we can find a lot of correlation to how we work and applying automation into work. But with this situation in particular, what happened was is he moved into a new role focused on automation, on scheduling workflows, on basically designing the systems that automatically run the tasks at the right times without having humans to babysit it. And so I think as we're describing AI and the implications of the workforce, I think it's a good story. And and that story uh fits perfectly in the lens for AI because the best people they don't fear automation, they build it, they they see the bottlenecks and they ask, why are we still doing this manually? And and that same mindset, I think, is exactly what HR and workforce leaders need to be are are being asked to adopt right now.
SPEAKER_02If AI is already here, what's HR's role? Gatekeeper, guide, or firefighter? The current state or reality where AI is already touching HR. We'll go through some different things. The first is recruiting. Resume parsing would be an example. Modern ATS platform automatically extracts work history, infers skills, standardized job titles, and detects career progression patterns. This replaces manual screening for structured data. The impact is recruiters spend less time formatting and more time evaluating. Candidates matching AI models match candidates to open roles based on skill similarity, suggest internal mobility options, and ranks candidates by likelihood of fit. Systems like LinkedIn and Eightfold use large-scale skills graphs to power this. The reality check is the recruiter still decides, but the shortlift is often machine generated. Interview scheduling. Automated scheduling tools include sync calendars, handle time zones, and reduce back and forth emails. This is simple automation, but at enterprise scale, it saves thousands of hours annually.
SPEAKER_01And I can tell you as a recruiter, those that is music to my ears. When when you can speed up processes, naturally recruiting will always there will always be a human element to hiring people, right? But but those are perfect examples of how we can work a little more efficiently. Yes.
SPEAKER_02In HR operations, chat bots for FAQs, AI-powered HR assistants handle PTO balances, benefit questions, policy clarifications, payroll timelines, many are embedded in platforms like Workday or custom enterprise co-pilots. The impact is faster response times, reduced ticket volume, and 24-7 support. For policy lookup, instead of search of a 70-page handbook, employees can ask, can I carry over vacation days? And a generative AI retrieves and summarizes relevant policy instantly. This reduces friction and improves compliance. For case management, AI can categorize employee relations cases, flag escalation risks, detect sentiment in complaints, suggest next best actions. This doesn't replace HR judgment, but it does improve prioritization.
SPEAKER_01Mike, I'm sure you're not excited about AI handling a lot of the uh nuanced questions of employees coming in and asking the questions that, well, they're in the handbook. How many times do you have to say, well, that's that's in the employee handbook?
SPEAKER_02Far too many. Yes. For learning and development, it can create personalized learning paths. AI can recommend courses based on role and skill gaps, adapt content based on performance, suggest internal career pathways. Platforms increasingly integrate skills, inference, and dynamic recommendations. The practical shift is from here, here's the LMS catalog, now go find something, to here's what you specifically need next. For workforce analytics, AI models analyze tenure, promotion velocity, compensation changes, engagement survey trends, and manager turnover. To estimate the probability of a voluntary exit, it's used responsibly. This allows targeted retention conversations and proactive mobility opportunities. Used poorly, it becomes reactive or ethically questionable. For engagement signals, AI can detect patterns in survey comments, internal communications metadata, participation rates and pulse trends, natural language processing flags burnout signals, cultural friction, and declining moral clusters. The key shift is HR moves from retrospective reporting to forward-looking insight.
SPEAKER_01That's a lot. That is a lot of things AI can and is doing. Yes, it is. And when we look at all of the the entirety of the scope and the potential impact of the application of AR in our workforce, frankly, it can seem daunting for a lot of people. And it is because they don't really know where to start on integrating AI into the workforce. And so naturally, as HR leaders, we have to look at ourselves and really ask the question: what are we actually doing with AI? Are we using AI unofficially? Are we using AI not telling IT? Are we not telling legal? And and here's the real danger with AI in the workforce. It's not AI itself. It's it's HR using AI with sensitive employee information like it's Google. Because when HR pastes things in like performance issues, medical accommodations, harassment complaints, termination documentation, you're not asking a question. You are potentially disclosing a protected, uh, you're you're potentially disclosing protected data to a third party. And so legally, that can create exposure under privacy laws. It can trigger breach reporting requirements and act and it can absolutely become discoverable in litigation. I don't know how many times we've sat through a legal seminar and and the the topic of social media comes up. An HR's role or should be lack of role in using social media. Just because you have the legal ability to look someone up on Facebook does not necessarily extinguish any sort of litigation threat. Just because you can doesn't mean you should. And so what this means is if if you end up in an EEO C claim or a wrongful termination suit or an ADA dispute, the question becomes did you use AI in this decision? What did you input and who had access to it? Because HR data is it's really some of the most sensitive information in the entire company. And the moment you treat AI like a harmless search engine is really the moment you're playing with fire. And so right now we're we're able to see where the cracks are showing in A in uh in AI, right? So here's where AI starts to crack in HR. Garbage in, garbage out. And I'm gonna explain what that means because AI doesn't magically fix broken problems, it just makes them faster. And so if your job descriptions are outdated, if your performance reviews are inconsistent, if your comp data is messy, if your organizational structure is unclear, AI isn't is it all it's going to do is amplify that chaos. It's it's not gonna clean it up for you. And so the scary part is the output, it's gonna sound polished, it's gonna sound confident, and so leaders are going to assume it's correct. But AI, it can't tell the difference between a healthy process and a dysfunctional tone. It just reflects whatever you need, it just reflects whatever you feed it. And so there is inherently a lot of bias baked into objective, these objective tools. There is an and there is an engineer on the other side of this building this engine. Well, what are those? What is that engineer's inherent biases? Are those being built into the platform? And so uh the question for you is uh are we using AI to augment humans or are we quietly replacing judgment? And so if AI, and this is just my opinion, but I believe if AI becomes a substitute for judgment instead of a tool that supports it, we're not innovating. We're just outsourcing leadership. I mean, HR shouldn't just implement AI. HR should be designing AI. It should help in this design process. This is HR's new role. Design decision. That is the power position of HR right now.
SPEAKER_02So some core concerns HR must own topics like bias, ethics, and trust. Regarding data bias, AI systems learn from historical data. As you pointed out, Ed, if historical decisions were biased, AI can learn and scale that bias. Example risks include overweighting pedigree schools, penalizing career gaps, rewarding historically dominant demographics, learning from past promotion patterns that were inequitable. If your workforce historically promoted one group more than others, a predictive model may interpret that pattern as success. The model isn't racist or sexist, it's statistical. But that statistical bias becomes operational bias. So what HR must ask is what data train this model? Is historical data representative? Has disparate impact been tested? Who audits the outcomes? There needs to be algorithm transparency. Many AI systems, particularly deep learning models, are not easily explainable. That creates risk in HR. If a candidate asks, why was I rejected, or an employee asks, why was I flagged as attrition risk, you cannot respond with the algorithm decided. That is legally and ethically insufficient. That's a nightmare waiting to happen, isn't it, Mike? It is. The practical governance standard says that HR should require clear documentation of model inputs, audit trails of AI influenced decisions, human review checkpoints, and explainability at a level a non-technical stakeholder can understand. If a vendor cannot explain their model at a high level, that is a red flag. Many enterprise platforms, workday, SAP, etc., now include AI governance documentation because clients demand it. That pressure must continue.
SPEAKER_01And I think it's going to continue to evolve. These policies, these standards, we we have to understand there should be a baked-in level of pliability into these policies because naturally things are going to change, just like our workforces change. So we have to be ready to continue to adapt and change what we view as that AI policy.
SPEAKER_02Regulatory momentum includes the EEOC, state laws, and EU style guardrails. In the US, the Equal Employment Opportunity Commissioner EEOC has issued guidance that says employers are responsible for AI tools they use, disparate impact standards still apply, vendors do not absorb the liability. Several states now require bias audits for automated hiring tools. Disclosure when AI is used in employment decisions. Every HR leader should be able to answer. Where is AI influencing people's decisions? What level of autonomy does it have? What human oversight exists? How are biased audits conducted? How are employees informed? And who is accountable when harm occurs? If those answers don't exist, you are operating on vendor trust, not governance.
SPEAKER_01And I think that's that's the key. If ultimately, if if your employees don't trust the system, how can they trust leadership? Because they won't. And really, systems are where strategy becomes reality. And with AI specifically, I think we really need to avoid the I would term it automation theater, where AI becomes a shiny layer on top of broken processes, right? And and and AI really shouldn't be implemented to look modern. It should be implemented to create more of a measurable operational value, right? I mean, fewer handoffs, faster decisions, better service, and less wasted effort. And that's really the hope and the focus for early adoption is to speed up your current processes. And like we've talked about, your processes are a mess. If your systems are discombobulated, it really is going to accentuate that. Automation and AI isn't going to fix your core issues, but I think there's a valuable, it's it's an extremely valuable tool to get you to where you need it in a healthy Head Start.
SPEAKER_02Compliance, privacy, and risk for data ownership. Critical leadership questions include Does the organization retain ownership of all employee data? Can vendors train their models on your data? Is your data used to improve models across other clients? What happens to your data if the contract ends? Many enterprise HR platforms provide contractual clarity, but that clarity must be verified by legal and HR together. If AI models are learning from your workforce patterns, you need explicit governance around that. Employee surveillance concerns. AI makes it technically possible to analyze communication frequency, collaboration patterns, time on task signals, productivity metrics, and sentiment in written feedback. Even if used with good intentions, it can feel like surveillance, and perception matters as much as reality. Once employees feel monitored rather than supported, psychological safety declines. Decisions need to have explainability. There are some guardrails that need to be in place. The first, minimum necessary data. Collect and guard only what is necessary for a legitimate business purpose. Another guardrail is human in the loop. No high impact employment decisions should be fully automated. And the last guardrail, radical transparency. If you would be uncomfortable explaining it publicly, don't implement it privately.
SPEAKER_01Absolutely. And and these guardrails, Mike, I think they're extremely important to keep in mind. You mentioned a lot of things that makes it technically possible for AI to analyze. And these things really can't be overlooked. But to your point, it can lead to a path of perhaps micromanagement. And my my head takes me back to the days of COVID when everyone was working remote and you had certain operational structures that they just operated more of in a in a micromanagement type of feel. And these organizations they they felt very felt very at ease. Let me say that when COVID hit, because now they had no way of micromanaging. Now think about implementing AI to really micromanage those same people. Compliance, it isn't a label that you buy, it's it's a responsibility that you own. And it's really about how you use the tool. It's about what data you feed it, it's about what decisions you rely on it for, and really the safeguards you put around it. Because if something goes sideways, the vendor isn't the one sitting in front of an employee telling explaining them why they didn't get that promotion. It's you. AI is not going to do that job. That's that's your responsibility. And so this is the part that I think gets scary fast. When AI starts influencing promotion decisions, performance ratings, who gets flagged as a risk, or who gets a or or who ends up on a pip? Because the question shouldn't be, what did the model say? The question should be who signed off on this? Who owns it? Who's accountable when it's wrong? Because AI can surface signals, but if it becomes a decision maker by default, you're gonna lose trust with your workforce really quickly.
SPEAKER_02Skills displacement and workforce anxiety. Roles evolving versus disappearing. AI will eliminate some tests. In some cases, entire roles may shrink. HR cannot promise no change. But HR can promise transparency, investment, skill development, and fair transition support. The worst outcome is not automation, it is unmanaged transition. So skills half life shrinking. Historically, technical skills have lasted ten to fifteen years. Even management practices remain stable for decades. Today, digital tools evolve annually. AI tools update monthly. Workflow expectations shift continuously. The relevance window for certain skills is compressing. What was advanced five years ago can now be automated. This doesn't mean people are obsolete. It means continuous learning is no longer optional.
SPEAKER_01HR is essentially caught right in the middle of this, Mike. You've got employees who are scared and not irrationally scared. They're watching automation and AI rollout, and they're thinking, is this going to replace me? On the other side, you've got executives that are chasing efficiencies because they're under pressure to do more with less. And HR is that bridge between those two realities. Trying to keep people engaged and stable while also driving transfer uh transformation, you know, that that's a tough spot to be in. And so here's the part that I think gets overlooked in a lot of AI conversations. Reskilling isn't a slogan, it's a budget decision. Everybody says we're we'll reskill our workforce. But, you know, if there's no time carved out, if there's no training investment, if if managers are not held accountable and there's no real plan, it's just words. And so reskilling only becomes real when leadership funds it. When they protect time for it and treat it like a strategic initiative instead of just a nice idea or the flavor of the month.
SPEAKER_02The goal is to shift from fear to ownership. HR uniquely positioned between tech, leadership, and people. Historically, HR focused on policy compliance, documentation, manager training, investigations. Now HR must also focus on data governance, vendor risk review, model transparency, ethical boundaries, and cross-functional oversight with IT and legal. The HR leader of the AI era is part talent strategist and part risk steward.
SPEAKER_01Absolutely. And you know, I think one of the biggest shifts we're about to see in HR, Mike, is HR becoming the interpreter, not the implementer, because the technology is going to move faster than the policies and the organizational design can keep up. So HR's role becomes translating what the tool is saying into what it actually means for the people, for fairness and for business decisions. You know, I've we we've all put it in a prompt in AI, and all of a sudden it spits out a 15-page report. What does it mean? How does this applicable for me and my business? And not just rolling out the tool, but interpreting it in a way leadership and employees can trust. Because if HR can't explain it in plain English, you shouldn't deploy it. AI is going to generate insights. I mean, it's going to identify patterns and flags and recommendations. I mean, you named a lot of them, Mike, but the organization still has to turn that into a human decision. And that's where it gets messy. Because insight isn't accountability. I mean, a model can say the person is a retention risk, but it can't own the conversation with that employee. It can't defend the decision. It can't carry that legal or ethical responsibility. So basically, what happens is HR ends up being the translator between what the algorithm outputs and what the leaders actually do with it. And so ultimately, the algorithm does not have the answer for it. Leadership does.
SPEAKER_02We need to make better decisions, not faster ones. Yep. For data-informed workforce planning, historically, workforce planning has often been reactive, spreadsheet driven, based on last year's headcount, and influenced by short-term budget pressures. AI enables a shift from backward-looking reporting to forward-looking modeling. Scenario modeling. AI-enabled scenario modeling can simulate economic slowdown, rapid growth, skill shortages, automation acceleration, regulatory shifts, and attrition spikes. And test, what happens to labor costs? Where do capability gaps emerge? What rules become bottlenecks? And what reskilling investment offsets hiring demand? This turns HR into a strategic risk advisor, not just a service function.
SPEAKER_01And one of my biggest concerns with AI, Mike, is that it can create speed without wisdom. And speed without wisdom just gets you in the wrong place faster. And you can automate decisions, you can automate workflows, you can automate recommendations. But if you don't understand the context behind the data, you're just scaling mistakes. And AI, yes, it can make you faster, but it can't make you more thoughtful. And so this is where HR protects context, because people aren't data points. They're stories, they're circumstances, they're managers, they're team dynamics. HR is the function that understands the context behind performance, behind retention, behind engagement, the why, not just the what. And so AI can surface patterns, but ultimately HR is there to make sure that the organization doesn't turn patterns into bad decisions. And so AI scales outcomes, good or bad.
SPEAKER_02We need to redefine human work. Creativity, judgment, empathy are premium skills. Creativity becomes differentiation. Generative AI can remix patterns from existing data. What it cannot do independently is set original direction, define a vision, challenge assumptions, or connect seemingly unrelated domains with lived experience. Creativity in the AI era becomes problem framing, idea selection, strategic synthesis, and narrative shaping. The human advantage is not raw output, it's imaginative direction. Judgment becomes a core leadership skill. AI produces probabilities, recommendations, and options. It does not own the consequences. Judgment requires ethical reasoning, risk assessment, context awareness, and accountability. The more data we have, the more disciplined our judgment must become. Empathy becomes strategic. AI can detect sentiment patterns. It cannot sit in discomfort with someone, navigate grief or burnout, repair trust after conflict, or sense cultural nuance in a room. As automate automation handles administrative load, HR's human responsibilities intensify. Empathy is no longer a soft skill. It becomes a competitive advantage. Because in environments where technology accelerates everything, people crave understanding.
SPEAKER_01I think the healthiest way to look at AI is this. AI handles the predictable, humans handle the complicated. Let AI take the repetitive, the administrative, and the pattern recognition, the first drafts. But the complicated stuff, the judgment, the fairness, the nuance, the leadership decisions, the coaching, the conflict, that still belongs to people. And honestly, it should. And that's the opportunity for HR because AI, it can elevate HR, but only if we step into it. If HR stays passive, AI is going to become something that happened to us. But if HR takes ownership of governance, of ethics, of decision design, and how the tool is used, HR becomes more strategic than ever. And so the role becomes less about pushing paperwork and more about shaping how decisions are made. And I'm going to tell you, Mike, with all of throughout all the HR people I've ever talked to, I don't know if I've ever talked to anyone that said they got into HR because of all the paperwork and all of the administrative aspects of the of the role. It's just going to allow you to focus on, well, maybe why you got into it in the first place.
SPEAKER_02So what's the future outlook three to five years ahead? The likely realities, AI governance policies, AI literacy expectations, and new roles. The next five years won't eliminate HR, they will elevate it. HR leaders who embrace governance, literacy, and strategic workforce design, as well as ethical clarity, will move from administrative support to enterprise risk and strategy partners. The future is not about AI replacing HR. It's about HR leading the responsible integration. Integration of AI into the workforce itself.
SPEAKER_01Here's my hot take, Mike. HR leaders who avoid AI, they won't survive the next decade. But HR leaders who blindly adopt it, they won't either. So I think the future belongs to HR leaders who can sit, I think, right in the middle. Those who understand the technology, understand the workforce, and build the governance and trust around it because AI isn't optional anymore, but neither is wisdom. So, question to our listeners for you to reflect on is your HR function reacting or shaping the future of work?
SPEAKER_02Wrap up and takeaways. AI is impacting far more jobs than it is eliminating. Most credible workforce research shows a majority of roles will see 10 to 30% of tasks altered. A much smaller percentage will be fully automated. The shift is task level, not job level. That means the real story isn't replacement, it's redesign. HR is not preparing for mass disappearance of roles, but for continuous evolution of work. Before expanding AI use in HR, we should map where AI is already influencing decisions, define clear guardrails, and invest in AI literacy for leaders and managers, as well as establish human oversight for high impact decisions.
SPEAKER_01The mindset shift is this AI, it isn't an HR tool. It's a leadership tool that HR has to govern. The uncomfortable truth is this. Think of the Industrial Revolution, electrification, the internet, the smartphone. AI feels like we're standing at the start of one of those cycles right now. But here's what history teaches us the boom doesn't come from the invention alone. The boom comes when leaders build the infrastructure, the skills, and the trust around it. And that's where HR has a real seat at the table. Not to be cheerleaders for H for AI, but really to make sure that it's implemented in a way that's responsible, transparent, and actually improves the work instead of just creating anxiety. Because as HR leaders, we're not just watching a new tool show up, we're watching decision making change in real time. And the biggest mistake that we can make is treating AI like a tech project. It's not. It's a trust project. If employees don't trust the system, they won't trust leadership. And with AI, there is a real risk of automation theater where we roll out something that looks innovative but doesn't actually improve outcomes. AI can create speed, but speed without wisdom, it just gets you to the wrong place faster. HR's role is protecting context, turning insights into decisions that are fair, defensible, and human. That means governance, transparency, accountability, not just implementation. And honestly, this is an opportunity. AI should handle the predictable so humans can handle the complicated. And if HR steps into that role as the interpreter, the guardrail, the architect of decision design, it elevates our profession. AI won't replace HR, but HR leaders who don't evolve might just replace themselves.
SPEAKER_02I'd like to thank all of our guests that we had today.