Explore how to build more AI confidence and imagination in the workplace with unique, relatable insights from Roy Bahat, head of Bloomberg Beta. From HR’s critical role in fostering innovation to the value of experimentation, Bahat shares practical strategies for navigating this evolving landscape. As he highlights, “AI is like riding a bicycle — and only by riding it can you develop intuition about what works and what doesn’t.”
Explore how to build more AI confidence and imagination in the workplace with unique, relatable insights from Roy Bahat, head of Bloomberg Beta. From HR’s critical role in fostering innovation to the value of experimentation, Bahat shares practical strategies for navigating this evolving landscape. As he highlights, “AI is like riding a bicycle — and only by riding it can you develop intuition about what works and what doesn’t.”
Subscribe to The AI+HI Project to get the latest episodes, expert insights, and additional resources delivered straight to your inbox: https://shrm.co/voegyz
---
Explore SHRM’s all-new flagships. Content curated by experts. Created for you weekly. Each content journey features engaging podcasts, video, articles, and groundbreaking newsletters tailored to meet your unique needs in your organization and career. Learn More: https://shrm.co/coy63r
---
This episode is sponsored by Robert Half.
Ad Read: [00:00:00] HR leaders know hiring is getting harder.
A new survey from Robert Haff reveals companies are hiring for critical roles, making competition for top talent fiercer than ever.
So how do you stay ahead? With insights that matter. The demand for skill talent report from Robert Half dives deep into hiring trends and the impact of AI on critical skills and staffing needs.
Get the data that drives smarter hiring. Head to Robert Half dot com slash demand for skilled talent.
Alex: Hello, I'm Alex Alonso, SHRM's, chief Data and Analytics Officer, and this week we're on the set of the IHI project in San Francisco, SHRM's live event focused on AI. And hi, I'm very fortunate this week to be joined by Roy Baha. From Bloomberg Beta. we're so excited to have you here, Roy, and it's wonderful.
We're gonna be exploring AI and how it's [00:01:00] reshaping transformation across several paradigms, and I'm really excited to hear about what you're bringing to this, uh, event and more importantly to hear about what you'll be speaking about as well.
Roy: Thank you.
Alex: Thank you so much for being here. Uh, so let's talk a little bit about what we're gonna be, uh, kind of exploring this week.
This, the theme of this event is really focusing on transforming the world of work by the, leveraging the concept of AI and hi, so artificial intelligence and human intelligence. Talk to me about your journey. Talk to me a little bit about what you do at Bloomberg Beta, but then more importantly, what it is that, uh, you are seeing out in the wild, so to speak.
Roy: Thank you. Um, and I think that the community of HR professionals. Is maybe going to play either the most significant enabling role within organizations, or as sometimes unfortunately happens, the most significant disabling role. Similar by the way, with technology executives. Um, you know, they're entrusted with the keys to the kingdom in certain ways.
So for me, so I [00:02:00] run Bloomberg Beta, which is Bloomberg's VC firm. We invest in very early stage startups as early as we possibly can, all of which are around the future of work and making work better. We started investing in ai. We were the first VC firm as far as I know, to start to declare we wanted to invest in ai.
We did that in 2014. Uh, it was over my objection at the time 'cause I thought it was too early. I was completely wrong. And you know, what we've seen in the decade plus since is just this explosion of all the different domains where AI can be valuable. And so we can go in lots of different directions with it.
I'll say my own background, I worked in big companies, startups. I started companies government. Academia, I still teach at Berkeley, uh, in the MBA program, nonprofits, and I spent a lot of time with labor unions as well. And I just can't think of a domain that isn't gonna be, or isn't already being rewritten by all this.
So we can take the conversation any direction you want to go.
Alex: So [00:03:00] you brought up HR professionals and I appreciate the, the, the notion of it being enablers and, and disabler. Right. Talk to me a little bit about what you're seeing in the wild when it comes to ai, specifically around transformation of organizations Right.
And what it's doing to the workforce.
Roy: Yeah. It's sort of, here's my analogy. I don't wanna overstate it because you know it's not gonna transform everything today. Yeah. It's happening. It's unrolling in a certain way. It's sort of like as if the practice of writing just got invented. Mm-hmm. And everybody's like, well, what do we do with this writing stuff?
Hmm. I guess I should try it here and try it there. And so we are in this. Figuring out how to do it. Stage. Yeah. Where people are scratching on tablets basically. And that's okay. the, the best organizations I think that get at this are gonna be the ones that manage to figure out how to get rapid experimentation.
Mm-hmm. Okay. That's obvious. The problem is how do you do that in a way that doesn't put the existence of the entire business at risk? And the thing I just say is. Almost [00:04:00] everybody's being far too careful. Far too careful, in my opinion. They're just worried about theoretical things that might go wrong.
The way I think about it is when you have a adolescent, like a AI in some ways is like an adolescent, and I've got kids, and so maybe I'm just speaking from some personal experience
Alex: Yeah, well, you and me both. I've got
adolescents.
running around. How Oh, I've, I've got
Roy: 30.
Alex: Alright. I've got 21 and
Roy: 17,
All right, so you got the whole range.
So my oldest is almost 17
Alex: Yeah. and.
Roy: You don't get them to thrive by telling, by blocking them from trying anything
Alex: Mm-hmm.
Roy: or really limiting how they try new things. You keep 'em outta stuff that's hopefully not gonna cause 'em any long-term damage. And AI is the same way. And you know, the thing I'd say is the number of people in organizations who spend more time asking how AI will affect things than using it.
It's insane. And so I actually think we should have a soft rule that you have to spend less time talking about AI than using the ai because now it's all all available for us. It's not like, I mean, [00:05:00] you look, you've worked in data, you work in data. It's not it, it's different from the big data revolution in the sense that every heard about that, you know, knew that there was a thing that could be done.
How do I do it? Hey, which companies are using analytics, blah, blah, blah. But ultimately, if you were person X inside of a company. And you wanted to figure out how to use big data. You couldn't do it on your own. You had to do it with the experts. You had. This is a lot more like mobile in the sense that how's it gonna affect your company?
I don't know. Just try it. Like, just open up Chachi, pt, open up, claw, open up whatever, and just try it. So that's my kind of general way of thinking about this moment. You
Alex: You know, it's fascinating 'cause I, I, I liken it to something my mom used to always say, which is she'd say there's a difference between keeping, you know, stubbing your toe and
Roy: losing
a
limb.
Alex: That's it.
And there's a big array between the two. But you've gotta try stubbing your toe. It's the only way
Roy: you learn. I think that's exactly right. I mean, look, we invested in Slack when it was still growing rapidly. And [00:06:00] I remember the number of people who would say to me, at the time I tried Slack, it didn't work.
Yeah. And to me, one of the analogies, my business partner James Cha, were three equal partners, me, James Cha, and Karen Klein as our third. And what, what James once said to me is AI now is like riding a bicycle. You gotta get on and figure out how it works. It's gonna be wobbly at first. And the number of people who say, I tried the bicycle but it fell over, it's like, that's not how it works right now.
You have to stub your toe. You have to fall over, you gotta get some scrapes. And the question for organizations is. actually how do you maximize the pace of getting scrapes? Not how do you minimize the number of scrapes that you
get?
Alex: Exactly. And it's funny, I, we see this happening over and over again.
You really do learn quite a bit about an organization and their, their pension or their desire to really try to stub their toe and what they're doing in the world, especially when they apply AI
Roy: or
look
To it
Yeah. I mean, I'm curious what examples you've seen. 'cause I feel like across SHRM you probably have a whole range of them, but,
sorry, keep going.
I, I, [00:07:00]
I, won't. If you let me, I'll start interviewing you and we maybe don't want to go
Alex: you'll laugh, but we actually have a, a series of research when we were trying to determine what is the, the range of organizations. And there are actually still active organizations who are head in the sand choosing to avoid, full blown, avoid
Roy: ai.
I think if you work for one of those organizations, you should quit your job. It,
Alex: It, uh, it's pretty telling, believe it or not, but yeah,
Roy: I, I, I'd
argue
Alex: you're, you're making a point.
Roy: it's, again, it's sort of like, imagine software was just being invented and you're like, this software, it's just not for us. We're like, a, we're a respectable business.
We don't do software. That's how it
Alex: sounds
to
me. Yeah. It, it, it was fascinating. We were stunned by it and the, the two or three cases that we did look into it was almost either regulatory or
Roy: licensure
was
driving
I gotta
say
every single case I've ever heard somebody say that it's been nonsense. Yeah. I mean, a thing that happens here, and this happens with HR professionals.
Yeah. Is there's kind of a priesthood of like they go to their HR conferences and they talk to other HR people and they learn about the law. And then within the organization they say, no, no, we can't [00:08:00] do that labor law. And almost every case where somebody has said, we can't do it.
scratch
at it a little bit, and it just turns out to be nonsense.
And the trade craft for the innovative professional, and look, we've all had, like, there's a big HR group at this company and there's those two people who like, you know, they're always the ones trying the new stuff and it gets really annoying. But, you know, there's a trade craft for how they introduce those things to the rest of the organization without causing the kind of immune response.
That's, let's shut
Alex: everything
down.
So you, you took me there and I'm, I'm gonna go ahead and ask what is that secret sauce, that trade craft?
Give me
Roy: little
bit
about
that. Well, sure. So the first thing is it's,
Alex: I, I'll go back
Roy: the
beginning. Yeah. It's trying the stuff yourself, because only by riding the bicycle can you develop intuition about what works and what doesn't.
And you know, I'll say we've invested in a few companies that enable this, but the big ones, you know, if you are not regularly trying [00:09:00] pick your chat bot. You're missing something. And I use these things all the time, every day and every day I still discover stuff. I was talking to my assistant yesterday, my chief of staff, and she said, you know, we were talking about some email thread that was kind of indecipherable, honestly, between me and somebody else, and she was right that it was indecipherable.
And I said, well, have you tried feeding that into chat PT? And just asking it to make sense of it. And she works on this stuff all the time, and we were both like, oh, I guess that didn't occur to me. So some of it is just trying the stuff yourself. Yeah, because
Alex: that gives you
Roy: that gives you the
knowledge, confidence, and intuition to not say, Hey, let's, back to the biking analogy, let's bike up that trail.
And it turns out the bike just doesn't go up. That trail that that's one thing. The second thing is picking the right size things to move forward and a clear thing I think everybody ought to be advocating for now and to, I don't have any
investment
that
this
benefits is everybody in the company having access to the basic tools.
Everybody in the company needs access to pick your, pick your AI tool that you want. Claude Chat, GBT Perplexity. I just spoke to all their [00:10:00] business fellows. And
then
the trade craft goes from that to, um. Let's try to experiment to find some aspirational things. So let me, let me explain a little bit. I'll give an example and then I'll talk in theory how I think about it.
example is, and here we are, investors. We invest in a company called Repli, which is, it started out as an assistant for helping people learn how to program. Right, but now AI's gotten so advanced IT programs for you and so on a plane, on my way to the last conference I went to, I worked with Rept and in plain English in less than 15 minutes, built a website to do matchmaking at the conference between people with similar interests and I'm. Technical curious at best, like I've programmed before, but I'm a terrible pro. Like my, my any pro professional programmer would just say like, yeah, this is a guy who like, you know, reads English by sounding out the letters. He doesn't know what he's doing here. So I'm not very technical. And I was able to just try something and do it.
[00:11:00] And once you start, it's like, okay, now what can I imagine? And then you get to the theoretical thing is how do you imagine. What an organization ought to do. And here I'll use another analogy, which is some AI is like a loom, like a spinning loom. It replaces something you already do. You work with it the same way a weaver would work with a loom.
Eventually it replaces you. Some AI is like a crane, A crane as a piece of technology is remarkable in that. An infinite number of human beings given an infinite amount of time without that piece of technology or something like it could never lift a steel beam, five stories into the air. And so what we're really seeking out with ai, yeah, we wanna make our days less annoying and more productive, and dot, dot, dot, and we should all learn how to do that. But the real thing we're seeking is to find more cranes and fewer looms, which is what are the things that we couldn't do for our business, for our organization?
But for the existence of this technology, [00:12:00] and then try to bring that to life,
and that's gonna differ depending on the
Alex: company.
I love how you put that because I've seen so many companies, in fact, I'll, I'll share with you just as an example. At SHRM, one of our core principles, it's the absolute utmost core of what we do, is if you are not somebody who is smart and curious, there is no way, no place for you at SHM.
And one of the things that stands out to me is there's a second layer to that, and that's that. What do you imagine us to be? Right? And the humans can do that. But when you think about the AI component and really. That imagination and what it unlocks there is something powerful to that that I find too few
Roy: organizations do.
Yeah. It's interesting. Smart
Alex: sorry, did I
interrupt
Roy: you?
Yeah, no,
no,
Go. Smart and curious can often re It's great. Yeah. And you know, I know you all Johnny create
like a great
Alex: Johnny
and
all
that.
Roy: stuff.
The
most ferocious critics are often the most intelligent and the most curious because they've read some blog post about what Anthropic is doing and that gives them the detail they need to say, uh,
Alex: uh,
Roy: in a
[00:13:00] meeting. And
the,
it's two words. Imagination is one of them. And the other one is intuition is. And the two work hand in hand, which is the more you use this stuff, the better feel you get for, oh no, I think I can go up that trail.
And so the imagination and the experience of use produces intuition and then you can get a lot
of stuff
done.
Alex: Yeah. So you're here this week because of our, our event, and I want to hear a little bit about what you're gonna be sharing with the audience. What is it that you're gonna be, uh,
Roy: speaking
about?
Sure. I mean, to be honest, those listening to this podcast are getting a preview review. Mm-hmm. So, uh. Uh, I think the important thing when folks interact in person though, is yeah, that's great. People can listen to a podcast, but they can't tell us what they are worried about. And so what I'm interested in hearing from professionals here is, okay, cool.
That's nice. You said all those big words. Experiment, imagine intuitive, whatever. Here's where I'm stuck is like, you know, Cindy in, [00:14:00] in accounting says dot, dot, dot. Or I'm worried that if we put in too much of our data, this will happen. Because that's where the rubber hits the road. And our firm, you know, we've been fortunate in that.
Uh, maybe because we're part of Bloomberg, many corporates feel very comfortable talking to us about their issues. And so we often help them with what we call the digital safari. And the digital safari is, I've heard about these animals in the startup zoo. I'd like to go visit them. And then navigating through the specifics is where all the action is.
'cause like, I mean, I don't know if your organization says you don't wanna use ai. I really do think I, maybe there are exceptions to this, I can't think of, but I really do think, I don't give advice lightly. In fact, my series on LinkedIn is called, this is Not Advice, uh, specifically because I think most of us, we can just offer our own experience, but I just can't imagine a reason why a healthy organization would say no to this kind of technology.
Categorically, of course, you could say no to many implementations of it. You know, I say no to many implementations of it, [00:15:00] but. To me, the real question is gonna be, if you're trying to do it, how do you na the tricks and trade the tip tips of the trade of how do you, you know,
Alex: now. To get. So it's fascinating 'cause even in describing the, uh, those organizations who said no, how quickly they all within a year had experienced
Roy: a
full blown
food. That's
Alex: That's amazing. Right.
So it was, and I'll give you two examples. One was, one was actually a laundry service, believe it or not, a dry cleaning service who it didn't see the applications of it. It was a
Roy: very
different
kind
of Yeah.
Not an
Alex: email
business.
not an email business, not what you're thinking of. Not the SAEs of the world or anything like that.
Right. And they pivoted it on a dime and it was, we failed, we fell on our, on our, uh, you know, face, so to speak. And now we've gotta do something. If we're just gonna make it to next year, forget about next decade, next year. Right. And that's a commodity. That's a service that's gonna be around hopefully as long as we're all clothed.
Uh, one of the other things that strikes me though is this other group was one that was pivoting down this one [00:16:00] direction. And it was the leader of the organization who is saying, let's be slow. Let's be plotting, let's be methodical about this. And if it wasn't for the fact that there was a new leader with a different business imperative that came in and said, you know what?
We can't do that. So they went literally from we're only gonna use this one. Kind of generative tool to no, people have access to every tool you can imagine, and it unlocked content creation for an enterprise that did
Roy: not
have
gotten the creation.
I love that. And I do think that the powers available to an individual person in an organization if their leadership empowers them to go forth and do that. I mean, they're just getting more powerful by the day. The, when we first got into ai. One of my teammates said it was sort of like empowering everybody to be the CEO because everybody has an intern who's always on staff and willing to do stuff for you.
I mean, you know, we invested in a company called Textio that started out doing, uh. AI [00:17:00] for job descriptions. You know it. I know. And uh, and you know, the idea that anybody editing a job description would have access to all the data that only the data scientists would have, but it shows up to say, please change this word if you want to get a more, you know, gender.
Balanced group of people to apply. Please change this word if you want a higher quality of applicants. You know, all that kind of stuff. And so I think that there's a, um, a moment where people start to get, oh, this can show up
Alex: almost
anywhere.
Roy: And
Alex: a revelation in reality. I mean, when you think about, that's the definition of a revelation.
One of the things that strikes me is, uh, we see, and you referenced this notion, we see adoption of AI happening really in day-to-day execution. Right? And both for the big things, but also for the small things. And we, we track just with working Americans, we see that about. 48% of them say they're using it almost daily.
Intuitively, seamlessly, without even thinking about how it goes. And that's, you know, everything from the [00:18:00] chat GPTs of the world to Texteo as an example to others. Right. Uh, perplexity being one of the ones that's really,
Roy: you
know,
kind
of
kicking
in
late for people, by the way, who wanna do content creation.
Exactly. Capsule does video editing. I mean the, the, the range of stuff. Every blog post I do right now, by the way, I stopped. I used to, you know, like, go get art made for it. It's like, no, I'll just ask chat GPT,
Alex: but
sorry,
keep
going.
No, no, it's, I completely agree. One of the other things that strikes me though is what we, we uncovered was, and completely self-serving here, is CHROs tend to be the biggest, fastest adopters
Roy: of it,
Alex: it,
In fact, while the work, personally, personally,
in fact, amazing.
So you see roughly seven out of every 10 CHROs is using some form of AI today
Roy: for
their
strategic
work. Well, I do think, well, I want, I'm curious what strategic work mean, but I do think that it is often the most under-resourced parts of the organization that have to figure out how to do this stuff.
And look, the leaders have lots of. Advantages at their disposal, but they also have a lot of pressures on their time. And [00:19:00] so I'm thrilled to hear that. And I'm curious, when, when they say strategic
Alex: work,
what
does that
mean?
So I, I always am very, uh, uh, kind of the, the critic Talk to me about what you mean by strategic, right? Yeah. And what was fascinating is that they looked at it and immediately workforce planning is what they jumped to right off the bat.
Right. But then beyond that, what they talked about was design of work, which I'm an organizational psychologist by training. Right. And design of work is something that has always been the domain of my. My discipline, and I think specifically about when thinking about design of work, HR really hadn't gone into that, right?
They can design what the workforce
would
be.
They can
design a task,
but not designing what the future is. And what was fascinating is in interviewing these, these CHROs, they were very clear about. The strategy that I'm doing now is different than what I've done in the past. I am future casting what our organization will be doing as opposed to what it is that the people will be doing
to
Roy: serve
the
business
model. Yeah, it's very
different.
I, I agree with that. I think that the nature of the [00:20:00] powers available are gonna change, and so we gotta get smarter.
Yeah. I mean, you know, we are, I. Uh, we, we are backers of this company called Charter that is
media
for
HR professionals about this. And a lot of it is the smart people have more questions than answers right now. And sort of what data sources can you get? You know, we are also fortunate to work on workforce planning with a company called Work Helix that was started by the Stanford professor, Eric Olsen and a number of others.
And Eric has this great line. Which may apply to CHROs and to venture capitalists. He says AI is not gonna replace people at work, but people who use AI are gonna replace people who don't. And I think that ingesting the data you need to do your core job better, like workforce planning. Mm-hmm. You know, you can now answer questions like, which roles at my company are gonna be most vulnerable to disruption from ai?
You couldn't answer those questions three or four years ago. You still may not always be right, but you'd be better than nothing. So there's something around how do I use the data? But then there's also, what have I [00:21:00] always back to cranes. What have I always wished I could do that the tools kept me from doing?
And so I think it's a very, I realized in the anxiety producing time for many people. I mean, even my daughter said to me on the way to school, she never. My daughter, when I asked her for a theme song for my job, 'cause we had to do that for some team event, she said, could it be boring and about money? So that's how she thinks of my work.
And then she said to me on the way to school, she said, is AI gonna take over everything? She's in eighth grade. And so I know there's anxiety and I think the best way through is just embrace the optimistic stuff as best we can, and then work with, obviously we have to work on the broader society of how we, you know, train people for new roles, support them when they're in
Alex: transition,
Roy: et cetera.
Alex: So, at least your daughter had a better question than my daughters would've said, you know, my daughters immediately would've said, what
is your
job?
Exactly. Right.
That's the, that happens quite a bit. Yeah. So, you know, uh, we're here, we're talking about HR leaders. We're talking about HR. The question I get all the time is displacement. Right? That's the first question I
get,
and I
get that
from workers.
Mm-hmm.
From [00:22:00] HR leaders. The number one question I get is, what is it that I should be doing that I'm not doing today when thinking about ai? And I always smile. 'cause I think about some of the more recent research, like around CEOs and how they're using it to create digital twins to test themselves and test their read of data as you
just described.
Mm-hmm. I'd love to hear more about what you think HR. Professionals should be doing. And what kinda one piece of guidance
Roy: would
you
give them?
I'm gonna
go back to basics, which is when somebody says that to me, I ask them, how many times did you use a chat bot in the last day? And if the answer is either they don't, didn't, or they don't know the, then it's before you start thinking big picture, you know, you're asking about how to make a Lego sandcastle, go play with some Lego bricks and see how it goes.
So that to me is the, is the, the, the big thing. The second thing is. Uh, I say this at my own expense is. Spend money slowly on this, not quickly. I mean, there's so much temptation to write [00:23:00] huge checks to some mysterious vendor that's gonna have a magic black box. If it seems like a magic black box, don't do it.
I mean, some of the tools start really slowly, you know, donuts start as employee matchmaking tool to help employees within a company find each other. Now it does all kinds of other HR automation, um, and, and video conferencing even, and stuff like that. But you can start slowly. And the last thing I just say is whatever tools you already love.
It. Push those vendors, push those partners, you know, if you're already deeply using Zoom, make sure you're talking to them about what their feature set looks like. Um, and the last piece. So that's the second piece, is pushing the vendors, the tools you're use. The last piece, which has nothing to do with technology at all, is this is a moment of great instability.
It's a moment of great instability. We're sitting here right now in the markets. It's a moment of instability technologically. And so. Just listening to the employees, surveying them about their own worries about this stuff. And [00:24:00] people are afraid about, often about being too candid with employees about what's happening.
I think if we treat people like children, they're gonna act like children. And so for the HR professional to set a tenor of curiosity. Of openness, of expression of worry, but also expression of opportunity. Let's take the person who figured out how to use some new tool and make them a hero. And HR professionals have the ability to do that and shape the entire kind of tone.
They can't decide, but they can influence the tone of the conversation within a
Alex: company.
So I'm known for giving
a
wild
card
at
the end,
uh, during this session. And
Roy: I'm,
at you. you.
Yes. me. You fully
Alex: caught
up
on
my rose.
You
prompted me. Uh, don't give anything away. I haven't watched the finale yet, but anyhow, one thing that does strike me is, um.
You obviously you have access to a variety of different startups out there, different kind of applications. I'm a big fan of your, your x uh, thread and, and, and what to contribute. In fact, I, I appreciate [00:25:00] what you offered. Having started up and been part of the group that started up Shem Labs, I love the guidance that you give about, you know, even working with a venture capitalist or working with a venture capital fund.
When there are specific questions, I agree with you. That means that you actually are closer to getting those dollars, right? That's one thing that I, I remember in, in, in your years of guidance, one thing that strikes me, I, I just want to hear from you. What are you seeing out there that is the newest, kind of, most novel thing that you wanna
Roy: share?
You
don't,
you
Alex: share,
you can share.
Roy: share
Alex: That is just
Roy: holy
crap. that's
gonna,
yeah. I'll just say a funny thing about early startups. We actually don't traffic in, we traffic in secrets only to
the extent
that we
want
to protect entrepreneur founders of companies who are like raising money, that kind
of
thing.
But in terms
of what
they're doing, oh yeah. There are almost no secrets. People often ask me if they're looking for a job, Hey, what's the great new thing? It's like, it's all in the news. Just
go
read
that
stuff. Here's what I would say is the biggest surprise for me. In the [00:26:00] last month, literally in the last month, the degree to which professional people who make software, software developers, engineers have been astonished by how much faster they can work given the tools that are available.
It blows my mind. I mean, we had an emergency meeting of our whole portfolio to talk about this because everybody's like, I think I can go 10 times or 50 times faster than I was before. Just compared to a few months ago and in the last month, new tools, rep's, one of them people use a, but Claude code is something people talk about a bunch.
If you want to see where the future is going with ai, actually it's true. In general, I believe this and we as a firm believe this generally, I. The future is here. You know, the sci-fi line is the future is here, it's just not evenly distributed. Okay, that's very helpful. But then the question is, okay, where do you look?
You wanna see what the future of working in an organization is gonna look like. Look at how software engineers work, because they tend to be the ones who embrace the future the fastest. And right now, even in the last month, the [00:27:00] speed with which they can do much, much more
Alex: has
accelerated.
It. Fascinating. I really appreciate that. Roy,
it's
been a pleasure.
Roy: you. for having me.
Alex: here with us today and, and, and really thank you for this week's episode. I hope everyone in the audience enjoys it.
I know that we are
Roy: grateful
for
all
the
insights
you've
shared
Well, I appreciate it. If folks want to find me on the internet, I'm pretty easy to find, uh, my only constraints time.
But this is not advice. Dot work has the repository of all those questions, um, from when I've spoken to folks and we thrive on people asking us more questions so we can just try to share and learn together 'cause. It. Look, I, I don't know, as expert in AI as many other people, not anyone else. There are people who know more than I do, and I'm still trying to
Alex: figure
it
all out.
Yeah. I appreciate that. To our audience, we hope you'll join us for the next episode of A IHI and that you'll join us in 2026 for the IHI project.
Till
then,
sign up for our weekly newsletter by going to SHRM dot org [00:28:00] slash aihi. See you next
week.
Ad Read: Hiring is evolving is your business. Explore the demand for skilled talent report from Robert Half to see how AI is shaping the future of hiring. Visit Robert Half dot com slash demand for skilled talent.