Matt Burns from Atlas Copilot | Harnessing AI in HR Without Losing the Human Touch

Christine: [00:00:00] Welcome to another episode of the HR Scoop today. I have for you, Matt Burns, the co-founder at Atlas copilot. And I’m really, really excited to bring this conversation because I’ve. I’ve, you know, worked with Matt in the past, and I think what they’re doing is really amazing at the forefront of AI and how it intersects with HR and the people space.

So really excited to bring you a little bit more tactical, relatable information to our corner of the world than just generically talking about AI. So welcome, Matt.

Matt: Thanks for having me. Looking forward to the chat.

Christine: Yeah. So, I think one thing that is going to be important for our audience to kind of get grounded in is the fact that you do have HR experience.

You’re not just a, you know, a tech person who maybe is on the forefront of this new technology, but you’ve been in the trenches with us. So, do you want to give us just a little bit of [00:01:00] your background and how your personal experience in HR kind of has shaped your understanding of well-being in the workplace and all the things?

Matt: Yeah, we’re in some ways, the HR is Trojan horse in the world of technology. It’s interesting time. I spent 20 years in the corporate world, 15 of them were in HR, five as an executive. Um, I worked for some big companies. Worked for some small companies, worked for some multinationals, family led, publicly traded, and everything in between, and I really enjoyed my time working in the HR profession.

I really enjoy watching people have success. I enjoy being part of strategic decisions that involve and affect people. Um, and for me, I always seemed to find myself in HR business partnering roles until I was eventually moved into more transformational roles. Think like restructuring projects, digital transformation, mergers and acquisitions, things of that nature.

Uh, and I was lucky to be paired with a number of really great leaders along the way that took me under their wings and, um, rounded off my rougher edges and helped me build out a portfolio of skills that I use to this day. Uh, Atlas Copilot is [00:02:00] the solution I always wanted as an HR professional. It’s a solution I always wanted when I was in HR consulted after I left the corporate world and was helping companies on the other side with digital transformations.

Um, generative AI is a game changer for HR because we’re so dependent on administrative activities and we’ve all been lamenting for the 20 years I’ve been in this profession, how we need to spend less time doing manual administration and more time with relationships. And I’ve been personally talking about things on my podcast for seven years.

I’ve written countless articles about it and every time I get a chance, I’m trying to help people digitize something else so that they can spend more time with their people and it’s a tough challenge because we seem to add more paper all the time. Uh, companies get more complex, COVID didn’t help and Atlas Copilot with Generative AI makes all that easier.

So, it’s been a really fun journey to learn from this and to keep in touch with the HR community because ultimately we’re building it for you guys.

Christine: You’re so right. I mean, we all I mean, I remember the literal [00:03:00] filing cabinet paper days. Yeah, for sure. Yeah. And thankfully, we’re not quite there anymore. But we’ve just moved to a digital file cabinet.

And I think everyone wants to do less of it. But there’s the trust factor and knowing it’s reliable, and we can find it and it’s correct.

Matt: Totally.

Christine: So it doesn’t actually help us do a thing, right? So how do you think organizations can leverage AI tools to foster the things that we really want, like workplace well-being reducing employee burnout, supporting mental health.

Is there a connection or is it truly just operation admin support?

Matt: I don’t think those two things are separated if you do them well. And that’s been kind of my bias the whole way through in terms of how I look at. At my HR practice. I’m not the traditional typical HR person. If you met me at a conference, you never go.

There’s the guy in HR. I talk more like a chief operating officer or a chief marketing officer. I’m really good at reading a PNL. I endear myself to board members and to the C [00:04:00] suite executives. And it was a large part of my success as an HR executive was my ability to interact with the CFO and the CIO and the CMO do so with success.

Um, because we talked about the business and the impact of people on the business and we always brought things into dollars and cents and metrics, but I was always able to make the case for more investment because if you did it well, the company would have more success. Andrew, you know this better than most with your role, right?

If you make smart investments in your people, you can get great returns and you I was really lucky that I worked for organizations that if you built a business case and you showed results, they bought into things. Um, it wasn’t just about politics and putting, you know, like, shiny objects. If you actually could show benefit, they would put more money behind it because they knew that it was in their best interest to do so.

And, um, when I think about GenRevAI now, I think about all the activities that we’re presently still doing that are not value add. Let me give you three examples. Who is writing a job description? Why? Why are we writing job descriptions? We, it’s the same 1, [00:05:00] 000 words reorganized for the same 30 documents in every company.

Like really, it’s not that much different. If I, if we polled 10 software companies, we’d find 15 points of differentiation between all of them. It is what it is, and we’re all stealing from each other to build best practices off of it. And if you’re using ChatGPT now, it’s even more consistent because everyone’s pulling from the same one source.

So, uh, job descriptions being one. Uh, interview guides. Now, this is where it requires context, and this is where I get in trouble with my Talent Acquisition friends because I don’t want to denigrate their profession. I think part of Talent Acquisition is what happens in the conversation. That the interview guide is a guide for the conversation, but that you really learn more about people having a conversation than you do if they answer templated questions in a sequential order.

So what I would say is that, um, you can blend information. So I think traditionally people think about AI as chat GPT. It’s their only interest with it or their only exposure to it. But if you’re able to introduce through You know, an [00:06:00] application like Atlas Copilot, your company’s context, your company’s policies, your company’s procedures, your company’s core values, your pay grids, your, you know, your, your equity statements, whatever you want to introduce into that, and that bias, for lack of a better term, permeates to anything that’s created by your large language model.

It means it’s going to reflect more accurately as you’ve defined it, you. And output that makes sense for your job descriptions. It’ll reflect your core values. It’ll reflect the job. It’ll make sure that the last HR coordinator’s job description looks a lot like the one you just put out there because you’re not using a template.

You’re synthesizing information from many disparate sources, and they’re always remaining up to date. So, it’s a really interesting change because it solves two problems, three problems. It solves for efficiency, so you don’t spend your time doing the work. We’ve built an Atlas, Christine, you literally press a button.

You literally press a button, you answer five questions, and it will spit out a job description for you in the context of your company. And we’re trying to get it down to three questions, and two questions, to get to a place where it’s like literally [00:07:00] press a button, get a job description. Because. That’s the level we need to get to.

At least as a starting point, you can always iterate and evolve a document, but we want to help shave seconds off of people in terms of the things they’re spending their time doing. But beyond saving time, you get more compliant. If we’re working from the same consistent standard, then we know we’re operating at the same Basement for lack of a better term.

And then at the same time, you’re also more inclusive and more collaborative. You’re now having not only consistency, but you’re able to draw upon a broad amount of sources, which you might otherwise not be able to. I love about AI is if you’re thoughtful and conscious about what sources you put into the platform.

You can get some really great results. So there’s an opportunity to really bake in your company’s culture into your outputs. And that’s why I get excited about AI is you can supercharge great things happening in your company.

Christine: Yeah. So I got so excited to jump in this conversation. I completely glossed over the fact that our audience may not know what Atlas Copilot does.

Do you want to give us just a brief summary? Because you’ve [00:08:00] hinted at it, but Just for clarity’s sake,

Matt: well, maybe shift for context sake. Atlas Copilot, for lack of a better description, is chat GPT for HR, but it’s so much more than that. It’s chat GPT in so far as the interface feels similar. You log into our application on an app or on a web based browser, um, or if you’re in an enterprise account through teams and slack and you type into a chat menu that.

A prompt something you’re looking for what I’m referencing in terms of the buttons is we actually have built 70 predefined prompts or you click on them and get, you know, an answer back and it gives you questions back. You answer those questions. It gives you an answer back. Um, so that’s Atlas and its core.

Beyond that, we were partners at HR leaders that are fantastic. Content creators have great HR podcast put on fantastic events that drew 60, 000 people last year into their digital summits worked with companies like acting HR among others. And put on fantastic conferences. We’ll be getting to host their events in 2025 in the platform exclusively as well.

So you’ll be able to use generative AI live [00:09:00] during an event and ask the event questions, get the transcript in real time, summarize the meeting. Or Christine, I don’t know about you, but I have an inbox full of webinars that I signed up for, that I got the recording for, that I promised myself that I would watch.

But I had not clicked a single one of those things. With Atlas, I’m able to now put it through the application and say, give me the five takeaways given what you know about me. And it just gives me that and I can just check it off my to do list and move on with my life. So it just, it’s going to save us time getting best practices and research and benchmarking and those things.

Um, yeah, to me, it’s, it’s those types of small applications that will make all the difference.

Christine: It really is revolutionary because you can also bring in your own companies. Handbook policies and

Matt: all

Christine: that. So it is more specific to your actual company. Cause that is one thing that if you’re just going out to chat, GPT, first of all, prompt creation is a new skill in itself.

So the fact that there are some pre made pre populated for those on a time crunch or don’t know where to start is really [00:10:00] helpful. And then it’s just, you’re at the mercy of whatever the internet provides, whereas, you know, this is a little bit more specific to where you have your policies and your own company culture lens on it.

Matt: And it doesn’t, it doesn’t hallucinate. Like, I’ve used chat GBT like everybody else. Sometimes it pulls answers. You look at it like, where’d this come from? Yeah, we’ve hand curated every single piece of content on our platform because we know that HR people have to know, like and trust where it comes from, and when it gives you a response, you’re able to find every single source fully attributed that gives you your answer, so there’s no question about where it came from.

You don’t have to do a board presentation and site chat GPT is your source. You can go back to the HBR article or the McKinsey article or the Harvard Business Review, like whatever that place or a podcast with Christine Herron, like whatever that might be. It will give you the sources, video, audio, and text to tell you where the information came from.

It’s that kind of information you have to have on a platform that supports HR people.

Christine: Right, because to your point earlier, as we [00:11:00] are working with C suite and leaders and boards, you know, your reputation is It’s dependent on the quality of information that you’re providing just as much as anything else.

And those relationships, when you are trusted, you’re just so much more influential.

Matt: But traditionally, HR hasn’t had a lot of great access to external information. Compared to our contemporaries in the C suite. So whether we have a wealth of information on the internal context, we have more than anybody else does.

Which is really, really, really, really valuable. But a lot of decisions that affect the internal context happen because of the external context. Think about the current, you know, the more recent election in the United States. However you lean, it’s going to have an effect on the economy. It’s going to affect certain industries more than others.

It’s going to affect certain, you know, certain size companies more than others. There’s a lot of extraneous factors happening into this. The ability for HR to play a role in those conversations in both the internal and external context is so critical. And to do that, you need to have the right information.[00:12:00]

It’s going to support the arguments you’re making. It’s going to allow you to add that to the internal context that you’re already an expert in and make it even more compelling argument because you actually can tell both sides of the story.

Christine: That is a really good point because we are usually, I think of HR people as in our own little bubbles.

And I mean, just look at the COVID response. I feel like we were all trying to create our own individual policies.

Matt: Jody Heroes.

Christine: Yeah. And just like job descriptions, if we put them all together, they probably weren’t that different, but we were in our little bubbles. So, you know, as we can leverage our collective knowledge with good sources, that is a step forward, I think, in the evolution of this industry.

Matt: But I think about let’s go back to the job description situation like what I remember about the jobs of the interviews that I’ve had along the way are the people that I’ve met it was the recruiter that took the time to get to know me as a person or took the time to get personal during the long protracted recruitment process because they actually care like a human being like that met [00:13:00] that meant more to me as a candidate.

Then the great questions they asked in the interview, which I know it’s part of the company. That’s what they care about. They want to have consistency. They want to have make sure they canvas and evaluate certain topics. You and I have written hundreds of interview guides over our careers, and I still want the interviewer to bring their personality to the conversation to show their personality is an extension of our culture and to meet the candidate where they’re at.

Otherwise, it becomes this manufactured conversation where no one’s really being honest. And we’re wasting everybody’s time. So, I want the, I want the interviewer to be real. I don’t want them to show personality. I don’t want the guide to be something that they devoutly follow in terms of tone. Like, I want it to be a more of an instructional, directional document.

And I think that’s how I would look at artificial intelligence more broadly. We can’t always look or expect specific 100 percent clarity, especially now when things are moving so quickly. What we need is iteration at speed. [00:14:00] We need to We need to react. We need to make mistakes. We need to be more reflective, and we need to also move much more quickly in today’s environment.

I wish I could tell you that was something we could stop, but I don’t see that changing. So it’s a matter of how do we best leverage the opportunity in front of us while making sure that we look after the people around us at the same time. And I think artificial intelligence is an opportunity for us to do that if we’re thoughtful and conscious about how we deploy it.

Christine: Right, because the best tools and whatever we can leverage it to do operationally, it never replaces the human at the other end of that conversation or relationship. So you’re exactly right. Just as we can’t take it and copy paste it, you can’t make AI create your own personality, and how boring that would be anyway.

Matt: Yeah, I wouldn’t want to live in that world, and I don’t think people want to live in that world either, but I don’t think either people want to spend six hours a day behind a [00:15:00] spreadsheet. I’ve not met a single person that I know who signed up for the job going, you know what? Spreadsheets is why I’m here.

They do it because they love the job, they do it because they love the company, their co workers, the mission, whatever that might be, but They didn’t spend four years in university and spend ten years in other companies to spend six hours a day behind a spreadsheet, but we ask some people to still do that, and there are a number of people who would absolutely love to have that job.

So, you know, we have to think about putting things into context, but I’m always of the belief that we let humans do their best work. And their best work is relating with other humans more often than not. So I want to create opportunities for that to happen, whether it’s leaders with their coworkers, with their colleagues, with their direct reports, um, or whether it’s HR people with their people they work with as well.

I think it’s a win win for everybody.

Christine: Agreed. I could go the rest of my life and never be behind another spreadsheet and be just fine with it.

Matt: And the moment I can get Alice to turn my thought into a PowerPoint presentation.

Christine: Oh,

Matt: that’d be the last time you see me open up a PowerPoint presentation. [00:16:00]

Christine: It will come.

Matt: It’s going to be here within 2025.

Christine: No.

Matt: Right now you can already turn information into PDFs. So we can already say to convert this output into a PDF. By about the second quarter I’ll be able to put it into a PDF. Excel document, and then we’re trying to get to Q3, Q4, and do a PowerPoint because another thing, how much time have you spent building PowerPoint decks in your career, Christine?

Christine: So much time.

Matt: So much time. When you should be spending your time doing the storyboarding, and the stakeholder relations, and the research, and that should be where you spend your time, Atlas is going to be one of many tools that’s going to help you do that. Microsoft’s going to help you do that, too, because they’re going to embed it into 3SIG Copilot.

But that will be a game changer for consulting practices all around the world. Oof. No PowerPoint decks. Terrifying.

Christine: That’s so incredible. I, I’m excited. Okay. So, if we’re thinking there are so many positive applications, in your experience, have you seen, I don’t know, [00:17:00] barriers to AI adoption? I know it can be scary.

It’s change management, ultimately. But what are you seeing, and how can we help people overcome those?

Matt: Let’s, let’s first honor that the concerns are real. Let’s just acknowledge that. Artificial intelligence is like pouring gasoline on something. If it’s a really good something, you are going to do incredible transformative things for your organization.

If it’s not a good something. It’s going to create bigger problems quickly, um, because it amplifies everything because it moves information that much more quickly through your organization. I think, though, it gives you the opportunity to do what few transformational projects actually do, which is the opportunity to be more efficient and more employee centric without having to trade off one for the other.

That’s awesome. I’ve done so many restructuring Christine where you have to choose one or the other and you try and make it okay, but it ultimately probably comes down to the financial. In most cases, this one with AI, you don’t have to skip that. You can do both because you can be thoughtful about how you deploy it in terms of how it interacts with the people who remain in the business.

I have not talked to a single [00:18:00] customer or prospect that I’ve talked to probably 500 HR executives last year in the Atlas context. Not a single one has said they want to reduce their workforce. It’s always been about complementing, augmentation, enhancing, supporting, that’s what people it’s investing.

That’s the context. So I think that is a really key point of differentiation is is we’re trying to upskill and reskill in addition to it being an administrative efficiency. Um, because I think it’s an investment worth making it in the people that are in our organization. Um, so I think that that part of it is is a really key point of to mention.

Um, I also think when you talk about AI more broadly and HR more broadly, We need to be able to draw upon different kinds of sources very, very quickly to make more informed business decisions, and we need to stop relying on people to be, have photographic memories. Like, I don’t really need you to be able to recite the labor code in your local jurisdiction.

I need you to be able to know where to find the information and apply it fairly, consistently, [00:19:00] compliantly, all the things. Um, We are moving from a culture of deep technical knowledge being highly valued, especially in the HR profession, to more generalist knowledge and the application of that knowledge in that AI accelerates that transformation and allows us to do so.

From the context in which we start and takes you on the path that you need to go on to personalize learning to get you where you need to go. There’s so many great things we can do with this, Christine, but there are risks. There are things like ethics. And when you deploy AI in a recruitment context, you need to make sure that the algorithm doesn’t deploy some implicit bias and screen out candidates with longer last names or from certain countries or certain backgrounds, which in most cases is not malicious.

But it’s really hard to weed out. Embed implicit bias. Everyone’s got it. And whoever writes your code, like it’s, it’s, we, we, we battled with it at Atlas where we’re with an advisory board that keeps it keeps us honest around diversity of sources because [00:20:00] it’s very easy to get insular in your thinking.

And ethics is an important part of this. But I think to your point, change management has what I’ve seen had the biggest effect, which is when you take people with you on the journey, it doesn’t have to be scary if you’re working alongside them to develop use cases that benefit it. What they’re doing And you show them that what we’re doing is collaborative, you’ll buy in if you try and keep it under lock and key and cloak and dagger, and it becomes this like big reveal every six months.

You’ll terrify people in today’s environment. So I think it’s about transparency. It’s about bringing people with you on the journey. And I think it’s about helping people understand this journey is an iterative journey. We are in one. We are just beginning. The amount of evolution in this space is going to be monumental in the next two or three years.

So it’s a situation of Figure out how you’re going to ingest the change now and how you’re going to make it part of your practice so that you can ingest what’s coming down the pike, because it’s going to be a lot,

Christine: right? Come along, learn along the way.

Matt: Let’s do this together. Cause anyone tells you that an [00:21:00] expert is not telling you the truth.

12 months ago, nobody asked my opinion about artificial intelligence. And now all of a sudden I’m an expert. And that’s how fast things change is because a year working in an AI company is a significant amount of learning for the market, but we’re all going to get a crash course in AI very, very quickly.

And it’s going to be really fascinating to see all the great things that we can do with it, but there are risks. So it’s about us to understand what’s possible so we can potentially ward off what is. And part of our motivation in starting Atlas was we wanted to make sure this solution was built by HR professionals.

Then we want to make sure we drove the agenda and we can now do that. And I think it’s gonna lead to a better product and ultimately a better outcome for organizations.

Christine: Yeah. So I’m hearing you say we got to make sure that we’re leveraging the content, the data, the efficiencies that it has while maintaining a human centered workplace, walking people through the change management, keeping your culture of psychological safety, all of these things that we know that we need to [00:22:00] do.

Cool. All the time, but it seems like the future is going to be less important of memorization and knowing these detailed laws or regulations and more about how do you incorporate them? How do you influence the business? How do you build stronger relationships? And that is a beautiful evolution of this profession.

I think that’s what Hopefully we all want is to actually help create a better work environment for the people that are there using these tools. And I’m curious, since I guess you are an expert, you know, 12, Sid, um, what, what have you seen about measurement? Because metrics, measurements, ROI, this always comes back.

And I feel like with human centered things, it is not always, well, very rarely is it clear cut. You know, so what have you seen?

Matt: I love this question because I think it’s a really important question that we all have to [00:23:00] answer because we need to determine what’s important measurement is what gets done and what we value. So if this is an exercise in realizing efficiencies and you should do time studies and understand what the activities are before and after the intervention of artificial intelligence, that’s a really simple measurement.

If somebody is spending 12 hours a week doing job descriptions and running interview guides, and now you can use. Another AI equivalent and they spend two hours. You save 10 hours a week. You can calculate their salary and determine that hours be reallocated or however that looks and you can compound those savings.

Um, it gets more challenging when you get into the qualitative measures around, um, this around, you know, I don’t even know if I’d call it qualitative. I would say more in this case, downside risk avoidance. The opportunity, there’s a measurement and my, my statistician friends, my, my, um, my friends in the accounting firm will be able to share with us how they calculate the dollar value of reducing the risk of things and Atlas Copilot, other large language model tools that provide a degree of consistency and application around.

[00:24:00] Laws and regulations went up when done properly will reduce risk so that there is an element of that. And there’s also an element of, um, having access to the world’s knowledge. It wasn’t too long ago when we were in our early on our careers where information. Has significant dollar values attached to it.

Christine: Oh, yeah.

Matt: People would sell their research for tens of thousands of dollars. People would sell like the world has dramatically shifted. If you are an academic or an author or, uh, you know that in that space, because your knowledge, which would have been monetarily prized, just 10, 15 years earlier, all of a sudden became not without value, but valuable in a different kind of way such that you had to give it to people for free and then use it as the next step in a process to potentially generate revenue.

It became this new process, social media, smaller clips, things of that nature. Artificial intelligence allows you to remain [00:25:00] relevant by creating content that serves the needs of people. It can be simulated. Broadly and globally, we no longer have to worry about certain parts of the world, having access to the best practices.

We can share them globally. And one thing I’m really passionate about Christine is that traditionally what I’ve been looking for best practices, a lot of the information I see emanates from North America and Western Europe. Great. There’s some great stuff happening in Africa. There’s some great stuff happening in Latin America.

There’s some great stuff happening in Asia Pacific, but we don’t see it or hear it because it’s usually printed in different languages. And in publications that don’t make their way to North America because we’re getting fed a steady diet of our normal piece. What I’m working with the team now on an Atlas Copilot is, let’s find those cool sources of content in those other languages because we can translate them into 97 percent of the world’s languages.

So if it starts out being in Spanish or in Swahili or in Cantonese, we can bring it over and we can introduce it into the platform and allow it to be used among all the other resources that we’re creating and truly create global best practices. So these are kind of things I’m getting really, really [00:26:00] passionate about, because if you consciously apply thinking like this, you can really affect positive change.

Christine: I mean, wow. Yes, that is amazing. Um, Just to benefit from people all over the world doing the same type of work, because at the end of the day, we are all people. And people are people are people. I say it all the time because we have so very much more in common. Then we have different, and I think you and I would agree, and we do agree that relationships will increase in their value going forward.

So how, how do you think leaders can use AI insights and information to become better coaches and mentors and just better leaders to their teams?

Matt: The only thing how I use it, I think it’s a tough question because I think it’s individual. Here’s how I use it. There’s a little bit of honesty from from me on this podcast.

So what I use it for is a few things. One, I in the past have been guilty of taking too long to write the email. You know, the email. [00:27:00] Like I’ll spend like half of the day crafting the email , and at some point I just need to send the email right? So Atlas will help me send the email by I have what I have in my head and maybe it’s emotionally charged and maybe I’m dysregulated or maybe I’ve just been tired from the night before I have too many meetings or whatever that is.

Just give me a start. Give me a head start on this. And then I can tweak it and know that I have a sanity check. Somebody’s checked this for me because if my if my AI has created this for me, it’s going to be, I don’t have to worry, but I’m missing a piece or something like that. So that for us has been really helpful.

Number two, I got into the over the holidays. I was, um, I was getting involved in deep into the large language models and I asked both chat GPT and Atlas to give me feedback on my performance as a leader based on my interactions on the platform, the questions that I ask. How I asked the questions, the tones that I use, the follow ups that I come back with the, um, the speed at which I seem to [00:28:00] resolve problems.

I’m just asked this big, long prompt and it gave me this way too real piece of feedback that I wasn’t ready for. Luckily, I was in the holidays and I was in comfy clothes because I needed I needed that bowl of ice cream. But jokes jokes aside, um. It really deftly summarized what I thought was a really great synthesis, um, of things and then I basically said things like, what are my blind spots?

What am I not seeing being me? And it, it pretty much nailed them according to my coach. So, in that sense, I, that, that worked out really, really well. Um, those are two. And then I think for me, I think as a leader, You have the opportunity to be exposed to different things that sometimes your team members don’t, whether it’s decisions, whether it might be technology.

I’m trying my best right now to teach the people around me how to use artificial intelligence, even if not in the corporate world. Even if they’re not my generation, because I think it’s a really important skill that we’re all going to have to figure out, it’s going to make our lives easier, but it’s also something that we should educate ourselves on because they’re, in particular, in corporate functions like HR, there’s going to be [00:29:00] significant implications to our profession, so getting the skills, understanding the implications, understanding how we can affect positive change with it.

I don’t know about you, but I’ve, my, My nightmare is being on the on the receiving end of change that I wasn’t consulted in like I have. I don’t want any part of that. I want to be part of the narrative and part of the conversation. I don’t want to be the decision maker. I just want to be consulted. I think the best way for us to do that is by being involved in this innovative effort.

But we need people along the way to help us keep us honest. I’m on the right path.

Christine: I love that. And yeah. I am so curious now to go ask what my blind spots are, and I’m gonna wait till I have my sweatpants on.

Matt: Yep, turn your camera off, sweatpants on. You can tell it to be nice to you, tell it to sugarcoat it, whatever you want, it’s great.

I told you to be brutally honest, it was a mistake.

Christine: No, I’m a, I’m a southern gal, I want all the sugarcoating. So I do really like that, though, for self awareness and improvement where you can take it at your own pace and it feels [00:30:00] less, I don’t say less personal because it’s very personal, but maybe, you know, it’s like coming from your manager where the stakes are higher because it has implications on your livelihood or whatever.

It’s just your own personal, write it in your dear diary and really reflect on what you can do Personally, I love that, uh, and I know we could talk forever about this, and maybe as things progress, you know, we’ll have you back on to see what the next iterations are. Uh, but before I just let you go, I do want to ask you what I ask everyone, which is to share something with us that most people don’t know about you.

Matt: Ooh, uh, yeah, so one thing that I like to do, a lot of my life is very structured and planned. So when I travel, it’s very unstructured and planned. I’m the person who’s gone to the airport now six times without a plane ticket.

Christine: No.

Matt: Bought a ticket at the airport and then went on the vacation.

Christine: I didn’t know you could even do that.

Matt: It is not [00:31:00] easy, depending where you go, but if you pick a bigger city, you have lots of options. So I go to the booth, I give them the dates, I give them my budget. And if you meet somebody who’s really friendly, it’ll be a fun game. And if you meet somebody who’s not that friendly, it’s an irritation. So either way, it’s been a fun experience more often than not.

I think people like a little bit of variety in their travel. And for me, it’s uh, yeah, it’s been a fun little, like, exercise in agility.

Christine: Wow. What has been your favorite place you’ve ended up?

Matt: Denver.

Christine: Denver. Okay.

Matt: Denver. I really enjoy Denver. It’s a really great city. I just think I like being near the mountains.

I like being the people are very, very great out there. Like I just to me, yeah, Denver was and I had didn’t have high expectations. So when I was there like, wow, okay, this was Because the way it works is, again, with the budget and the time, they give you a list of cities and you pick. Right? I’m not going to, I can’t wait three hours for like, you know, Morocco.

If it’s, if it’s Denver or Cleveland, I’m going to probably, in this case, pick Denver. So I did, I picked Denver and I was glad I made that choice.

Christine: Wow. That is very brave. I [00:32:00] love that.

Matt: Bring your passport.

Christine: I mean, I’m not going to do it, but I love that for you.

Matt: Great. Fantastic. That’s the best kind. Vicariously, that’s the best way to travel.

Christine: Yes, we love that for you. Okay. Well, thank you again so much for coming on the HR Scoop. It was an absolute pleasure and hopefully we will hear more from you soon.

Matt: Thank you.

Christine: See you next time, y’all.

“AI is here. It’s fast. But if we use it right, it actually brings us closer to people, not farther.”

This conversation covers:

• • How generative AI is solving the HR admin overload

• • Ways leaders can use AI to coach better and connect deeper

• • What HR can learn from global best practices