How to Build an HR Tech Stack Employees Actually Use
In this episode of the HR Leaders Podcast, I had an inspiring conversation with Arun Serikar, VP, HR Technology, Digital Platforms & AI Innovation, Corp Functions at Schneider Electric, to unpack what it really takes to simplify HR technology, scale AI, and build a better employee experience across a global enterprise.
Arun shares how Schneider Electric went from 545 HR applications to 303, reducing tech debt, breaking regional silos, and building stronger governance around the tools, data, and platforms used across the business. He explains why employees are not looking for the “best system”, they are looking for fewer systems that actually work together.
Most importantly, Arun breaks down how Schneider Electric is using AI to move HR from a back-office function to an intelligence layer for the enterprise, from internal chatbots and ticket reduction, to performance review AI assistance, agentic workflows, and a future where employees can complete tasks without jumping between systems.
🎓 In this episode, Arun discusses:
Why employees want fewer systems, not more “best-in-class” tools
How AI is reducing HR tickets and improving employee service at scale
Why Schneider Electric reduced its HR tech stack from 545 applications to 303
Why governance, data quality, and integration matter more than buying more tools
How agentic AI could reshape HR workflows, manager support, and employee experience
What if AI agents were not just another way to create more learning content?
What if AI agents could help talent teams find real skills gaps, build the right intervention, and deliver it at the moment employees need it most?
That is what Arist is building with the first end-to-end AI agent for enablement.
Instead of relying on slow needs analysis, outdated content libraries, and one-size-fits-all training, Arist helps organisations move from guessing what people need to identifying real gaps in real time.
Its AI agents can interview employees, uncover talent gaps, create personalised learning, and deliver it directly through tools like SMS and MS Teams.
Because the future of enablement will not be built by more content or more manual workflows. It will be built by teams that can spot business needs faster, deliver learning that fits the moment, and prove impact.
With Arist, AI agents become a way to close skills gaps faster, improve performance, and help employees get the right learning before the business has already moved on.
[00:00]->[00:36]
When you talk to like people, right, employees, they're not looking for like the best system.
They're looking for fewer systems.
So you could have the best system, but like, you know, what good does it do?
It has to fit in.
So that's where like, you know, I focus on for employees as well.
Like, you know, it has to fit into the ecosystem.
It's not about the best system because there are just so many of them.
Arun, welcome to the show, my friend.
[00:36]->[00:41]
How are you doing?
I'm doing well, thanks.
Thanks for having me here, Chris.
I'm very excited to be here.
[00:41]->[00:42]
Where are you joining us from?
[00:42]->[00:59]
So I'm joining from Austin, Texas, the second capital of the technology, like in after the Silicon Valley.
So I'm very excited.
Plugged into the tech space here, moved here about four years ago, but been in the US for about 20 plus years.
I'm excited to be in the technology hub.
[01:00]->[01:07]
Amazing.
Is that official now?
How long has it been weird at second hub?
Has that always been?
Since when?
[01:09]->[01:16]
Since like major companies started to move here, right?
Like, you know, if you talk to anyone who's not in Austin, they probably disagree with like, you know, that's true.
[01:16]->[01:23]
That's yeah.
I mean, the only, the only big one I remember is when obviously Elon Musk moved.
[01:24]->[01:27]
Yeah.
Oracle.
[01:27]->[01:28]
Oracle.
Yeah.
That's enough.
Yeah.
[01:29]->[01:48]
Stuff like and then also like you know you we have AMD now I heard like Nvidia is moving here oh like you know
they're opening up an office here there's meta there's Google I actually joined Google and then that's when like I actually moved to Austin
Prior to being Tata Schneider, but yeah.
Amazing.
I have to come say hi and come visit.
[01:48]->[02:04]
We're always in the US, but I've never ever visited Austin.
I really want to as well.
Before we jump in, tell everyone a little bit about your background and your journey to where we are now and your current role
that you have, which is super exciting, the current role you have.
[02:04]->[02:37]
Before I jump into the current role, like in a little bit about myself, born and brought up in Hyderabad, southern part of India.
Uh always like you know aspire to be a tech uh technology related like in a person like mainly they were like growing up
there were only two careers that i always like you know aspire to be in either it's a doctor or an engineer uh did
you aspire that or did your parents say that's what you're doing like you know my mom's gonna like watch this i can say
like you know okay i love it i love it
[02:37]->[03:11]
So I like, you know, if it was to me, like, I wanted to become a chess player, I was really, yeah, I was,
I was pretty serious.
I thought that I was gonna make a career out of it.
Right.
And then I got sponsored for a state.
And then my parents like now, like, you know, you're not gonna be successful.
And they had their doubts.
And looking back, and maybe like, you know, it was a good decision.
I don't know.
But yeah, then I got into the engineering space.
And I always wanted to be part of technology, right?
And then I moved to the U.S.
In 2004, did my master's here in industrial management.
[03:11]->[03:44]
And after that, I worked for Accenture, Deloitte, and the journey began in the HR space.
And I'll talk a bit more about how I got into HR tech as well.
But my most current role for the past three years, I've been with Schneider, leading HR digital operations.
Tools, technology, strategy.
And most recently, I took on governance as well for HR applications.
AI is a big part of it as well, as with any other company.
But yeah, we are in forefront of some cutting edge transformation that is actually happening alongside with the complexity that exists,
[03:44]->[03:54]
which is unheard of.
In my 20 plus years of career, I've never seen a complex organization such as Schneider
But the culture is what like, you know, pulls all of this together.
[03:54]->[04:26]
Yeah.
And, you know, I have a long standing history of your colleagues going back many years.
And Schneider has always been on the forefront of innovation and ahead,
which is why I've always interviewed many of your colleagues over the years.
And you're right that at the center of all of that is a very strong foundation, which is your culture.
And you're one of a few organizations that truly actually live it, right?
It's not just something on a poster somewhere.
It's really aligned into the business, the processes, even the compensation, right?
[04:27]->[05:00]
Like is it as well.
So super, super exciting.
By the way, the chess thing just completely threw me off and I'm like so excited to talk to you about that separately because
like I've recently decided washing chess randomly.
And I watched the, what's that TV series?
Is it Queen's Gambit?
Have you seen it?
Yeah, it was such a good series.
And then I got like obsessed with watching it, but I still, I don't know how to play.
So maybe you have to teach me sometime as well, but like absolutely fascinating space.
[05:01]->[05:31]
My son, who's 12, recently won like a tournament here.
He got like, he won a cash prize for the first time.
Nice.
Significant like you know for his age like you know six hundred dollars of course and he was so excited about that and uh
he actually came second in uh texas state he started playing when he was five wow so he's uh yeah he's very excited and motivated
about chess as well so yeah maybe when he's older and he and he becomes like a grandmaster he seems like dad see this
[05:31]->[05:50]
could have been you
Is he, is he, um, is he, has he beaten you now?
Like, is he already like at the level where he's comfortably beat you and you've not let him win?
In the past 20 games that I played with him, like I won once.
[05:50]->[06:05]
No way.
That's what it is right now.
So I tried my best not to play him.
He, he tries his max to play me because you know, he,
He likes it.
I always cut down the video games for him and he likes to beat me in chess.
That's a good balance.
[06:06]->[06:23]
That's a fair deal.
So tell everyone a little bit more about the current role that you have and some of the focus because it's quite an interesting
role.
VP, HR technology, digital platforms, AI innovation.
And now you mentioned someone around the compliance side.
So a lot of stuff going on.
[06:24]->[06:58]
A lot of stuff.
Yeah.
So when I joined Schneider, right, like a little bit of history, it's like I was an individual contributor.
I was brought in with the understanding that this role was actually created,
a newly created role to bridge the gap between the COE that was defining the strategy.
They were doing some of the digital work as well on their side.
And then there is the Schneider Digital, which is the IT side of things, right?
So what was missing is there was a lot of like regional influence in terms of like driving tech transformation.
So there was a duplication of technology solutions that were being implemented,
[06:58]->[07:28]
very fragmented approach in general from how the systems would speak to each other.
Overall, forget about a global manager, but even from a regional standpoint, there was a lot of duplications and customizations.
So my role when it was created, the first few months was to talk about
The importance of governance, how do we enforce governance and ensure that people are not throwing tech at a problem,
but they understand the bigger picture of why we need technology to accelerate.
[07:29]->[07:59]
If there is bad data and you put some technology on top of it,
It's just going to amplify that.
It's just going to spit out all even garbage information.
That was my initial role and continuously my role expanded from governance to actually getting into the overall global digital lead.
Now, all the regional silos are broken.
We don't operate at a regional level anymore.
We support the regions with the regions in the forefront,
[08:00]->[08:14]
But there is a global team that actually does that, which helps us like, you know, tremendously, right?
Like if you ask me to quantify it, something that I'm very, very proud of is when we started this journey three years ago,
we had 545 HR applications.
[08:15]->[08:17]
Oh my God.
[08:17]->[08:17]
545.
[08:17]->[08:48]
Yes.
You name it, we had it, right?
So any technology.
And today, Like, you know, two and a half years, three years, almost three years later, we are sitting at 303.
Right.
So we were able to sunset a lot of a lot of like applications and address the tech debt.
But quite honestly, the journey has just begun.
I see it as like a lot more that can be done.
So my my role is to ensure that we're doing the things right way.
We're not like, you know, just getting the best, best of breed solutions.
But why are we doing it?
[08:48]->[09:18]
How do we measure it?
And then at the same time, in the aspiration of fixing the foundation,
we don't want to be left out from a tech evolution perspective either.
We are a technology-first company.
So we are adapting to new ways of working with AI.
We are probably one of the top three companies that have implemented a chatbot globally for all employees.
In-built, in-house, right?
Like we do leverage in AI, we have like open AI and all of that, but like everything's been built in-house.
The adoption's pretty good.
[09:19]->[09:33]
The accuracy is pretty good.
We continue to build it.
Now we are getting into the agentic space as well.
So when I compare myself with like some of the competencies out there and then also other companies, my team is like, you know,
doing some like cutting edge transformation there.
[09:33]->[09:55]
Yeah.
There's, I mean, there's so much to unpack there, but one,
I suppose the unique advantages like you have on like other companies is that you get,
you have the skills and capability to build this in-house.
How, how, how do you work with the in-house teams?
Cause it's a very unique situation that you can work with your in-house development team to build rather than how do you decide when
to build versus buy?
[09:55]->[10:26]
Yeah, no, that's always the key question, right?
Like, you know, because build has its pros and cons and buy has its pros and cons.
We evaluate case by case, right?
The first AI that we actually implemented was this chatbot that was actually in-house.
We do have an AI hub team that actually focuses on like, you know,
getting the top talent to actually build these tools for us.
The cons of that, there's a lot of pros because then we can actually define from ground up,
[10:26]->[10:57]
we build everything ground up and then there is so much that can be done from a requirement standpoint.
There is flexibility on how we do it.
But again, the downside of that is that the amount of time it's going to take and then the cost is tremendous.
So what, what we do is that some of these, like, you know,
where we have like a lot of confidential information and then we know that like, you know,
the technology out there is not there fully.
Uh, we do like, you know, take that, uh, in house and, uh,
But wherever we can actually buy.
[10:58]->[11:21]
And we know that we're just not addressing like one small problem, right?
Like, you know, it has to fit into the broader ecosystem.
In the past, like we had Glote, we actually sunset Glote very recently, but nothing wrong with Glote.
Glote was a great product for us that actually like did some really good stuff.
And for people listening, that's the talent marketplace solution, right?
[11:21]->[11:23]
That you use for a while, for quite a while.
[11:23]->[11:50]
Yeah.
Yeah, OTM, Open Hadron Marketplace.
That's done very well.
However, from our ecosystem, the technology wasn't speaking to Gloat, right?
So then the benefits of using Gloat wasn't really available for employees.
So it all comes down to how you implement it.
You could have the best technology, but if it doesn't fit into your current ecosystem,
It's just under the system.
Oh, man, I wish we could talk a whole podcast just about this.
[11:52]->[12:15]
You're right, because there's so many amazing products that are out there like Glow and others.
But unless it can bring in the other data sources,
you're missing all of the context and all of the other data that you can bring in.
And it almost just sits like standalone.
And it's a great product, right?
But you just can't connect it to the wider ecosystem.
Yeah.
[12:17]->[12:48]
One thing that like resonates with me very well.
And I feel like, you know, when you talk to like people, right, employees, they're not looking for like the best system.
They're looking for fewer systems.
Yeah.
So you could have the best system, but like, you know, what good does it do?
Like, you know, I always try to like give an example of Tesla.
And by the way, like, you know, my, I reported to Gagan, he's not a fan of Tesla.
Like whenever I give this example, he's like,
I said, you could have the Tesla.
I'm a Tesla guy.
But if you don't have the charger, what are you going to do with the Tesla?
[12:49]->[12:59]
So it has to fit in.
So that's where I focus on for employees as well.
It has to fit into the ecosystem.
It's not about the best system because there are just so many of them.
[13:00]->[13:31]
That's a good example, right?
Because what makes Tesla different to all the other automotives is that they own the ecosystem and the network.
So now every other system, now you can charge any car on the Tesla network.
So they understood the value of building an incredible car,
but also owning the infrastructure so that every car manufacturer now connects to their system seamlessly.
So, I mean, I'm sure in the beginning we knew that that wasn't the plan, right?
[13:31]->[13:58]
It was like only Tesla's only, but I think there was that broader vision of like now we become...
The network that all cars can plug into.
Obviously, a big question that, of course, keeps coming up.
Last year, we saw a lot of companies first starting to bring in these tools into the organization and into HR.
I would be interested from your perspective, what are the tools or where is AI actually delivering value in HR today?
[13:58]->[14:31]
Yeah, I think AI, for me, quite honestly, it speaks volumes.
It's not replacing HR.
I don't see that as AI replacing HR.
It's making the responses faster.
So the data is available much faster.
The service is available much faster.
It's helping us from SLA standpoint as well.
And quite honestly, things that
Uh, I, it would take me like hours to actually get an answer to, like, I get it in like minutes, sometimes even seconds.
[14:32]->[15:09]
Uh, a lot of that depends, uh, goes back to the integrations that you built and then the knowledge articles, right?
Like we cannot discount the fact that like, we really need to like educate the AI, but, uh,
Not only the knowledge articles are feeding to AI, but like AI is also creating the knowledge articles.
So it's like, you know, it's, it's going in circle, like, you know, pulling all of this information together.
So I see a lot of value there.
For us, like, you know, especially we have seen a significant, significant reduction in our cases, the employee cases that actually do come through,
whether it's like simple time reporting or like asking for like time off or like a simple question around like, you know, maternity, paternity,
[15:09]->[15:40]
like whatever that is, right?
So whatever the need is, we have seen like a reduction of 20% tickets.
And for a company our size, 170,000 employees in 130 countries.
We are talking like, you know, 50 to 80,000, 100,000 tickets per year of reductions only, right?
So that speaks volume.
And the second aspect of it is like now we're getting into the employee experience, right?
So when we talk about experience in the past, like what we were considering is that, oh, we need to build a layer,
[15:40]->[16:01]
an employee experience layer on top of everything.
But now we're saying, can AI actually do that, like agentic AI?
So gone are the days where AI gets you the information.
Now it's more about AI can also process information, trigger workflows, and all of that.
So we are experimenting quite extensively in that area.
And that's what all 2026 is going to be about for us.
[16:01]->[16:18]
Would the goal still to be that you would still have your agent that you've built,
but then connect that to ServiceNow to pull documents, resources, tickets, but still keep the layer that you have?
[16:18]->[16:29]
Exactly.
That's exactly right.
Like, you know, we did a branding.
We call our internal chatbot Joe.
So Joe is going to be the face for all of our employees, like managers, HR.
[16:29]->[16:38]
But where do they access Joe?
Is it inside of, like, what does that look like?
Is that inside of Copilot as a plugin?
Or, like, where does that exist?
[16:39]->[16:50]
So it exists in a couple of spots.
Like one, our intranet portal, which is, like, you know, SpiceBliss.
So you can go there, you can access it from there.
And the second is on Teams.
Yeah, I knew it.
[16:50]->[16:55]
Yeah, Teams.
So you have a Teams plugin and it's just embedded directly there.
[16:55]->[17:02]
Cool.
Yeah, exactly.
And you know what my ambition is?
I think, why do you even need an intranet?
[17:03]->[17:30]
Yeah, but dude, quite frankly, I mean that, yeah.
The fact that the intranet even exists still shocks me, but it's because of how big companies are.
It takes time to, you know, and because I think also you can't feed that into an agent because it's full of garbage.
But to your point earlier, like most intranets in companies are just full of like outdated documents and just like just so much trash
that if you were to feed that into an agent, it would be a disaster.
[17:31]->[18:01]
Right, right.
Yeah.
Eventually, we're going to get there.
Eventually, it's going to be one point of entry.
If I need something or I need to know about some communications and anything related, it should be available through the agent.
If I want to do my compensation planning, which is happening as we speak, this is the season for it,
I should be able to do that through the agent as well.
So I think a lot of that we're experimenting.
We also launched our performance reviews very recently.
We're just wrapping it up.
But Oracle brought up the AI Assist
[18:02]->[18:23]
Game changer, unsolicited feedback, like things that would take me days are like, you know, just taking minutes for me to like, you know,
provide feedback and complete the performance review documents.
I use it myself.
Like it's a game changer.
Like, you know, you just have to address like some bullet points.
It frames the entire, like, you know, the feedback in such a constructive way, better than human.
[18:23]->[18:24]
Wow.
[18:24]->[18:26]
Right.
So a lot of positive stuff.
[18:27]->[18:47]
So you use an Oracle for that as well.
How are you then, like just on that performance review one, because I think it's fascinating.
Are you sharing any of that data with your leaders and managers in real time?
Or are you connecting it to another platform to then give them that feedback?
How does that work?
Just out of curiosity.
[18:47]->[19:01]
It's actually...
Real time.
So, as and when you actually see this and submit it, your managers would have access to it.
And then we put it in the data lake.
And from there, you can actually report out using the people insights.
[19:01]->[19:34]
Wow.
Wow.
Yeah, that's, I mean, you're one of the first persons that I know of that capability, obviously,
but you're one of the first people that have actually brought it up, that are using it.
I mean, there's a lot of leaders right now, as you can imagine, they're pretty overwhelmed.
Like, I know most, I know the companies where they don't even know they have access to these tools.
That they're paying for, they're not even using.
What's been the biggest, I mean, we're talking like this is all really easy and everything's amazing,
but what's been the biggest challenge and the biggest hurdles that you and the team have had to overcome?
[19:35]->[20:09]
Yeah, there are quite a few.
The first, trust.
Having that trust in the AI to actually get things done.
Building that trust doesn't happen overnight.
So we have to like, you know, struggle through like a fair share of challenges to ensure that the data is clean.
We still go through that, right?
Like not everybody trusts AI in general.
And then I do realize why, like, you know, if you don't get the right answer, would you go back?
I think like it affects adoption, but I think like setting that expectations upfront is going to be very key.
[20:10]->[20:40]
Even for the AI assist in performance reviews, it wasn't easy because we didn't want to take any chances.
We didn't want to insert any bias in any of these discussions, but making it very clear upfront that this is AI assist,
this is a beta version.
This is going to do stuff that you want it to do, but it's still on you to make sure that everything's accurate.
And so far, zero issues reported on it.
That's been live for almost two months.
We are in the last leg of our performance cycle.
[20:40]->[20:57]
So trust, I would say, is one.
The amount of time it actually takes, right?
And then the education that is actually needed for the stakeholders and the broader,
because every conference that we go to today these days is about AI.
So there is a massive tool being released every week.
[20:58]->[20:58]
Yeah, yeah, yeah.
[20:59]->[21:31]
It's always about like, hey, like, you know, they're doing this.
Like, what about the other company doing this, right?
And everyone's like so excited about signing a contract, but
I think not everybody understands how that particular tool is going to get you the necessary ROI and the value around it.
So that's been a challenge as well, saying that, hey, we have a roadmap and it's not going to happen overnight.
We will have to take one step at a time, educating them on it,
and then ensuring that the foundations are being set along the same lines, saying, okay, clean up, standardize, simplify where you can.
[21:32]->[21:38]
Otherwise, you can have a tool, but it's not going to perform like the next generation one.
These two are the top ones.
[21:39]->[22:09]
Yeah.
I mean, I love the fact that you were transparent and I think that goes to building the trust of saying,
this isn't going to be perfect, right?
We're not claiming this is going to be perfect and you still need to check it.
And so it's like bringing them on the journey with you as opposed to being like, here's a tool and putting it, you know,
throwing at them.
As well.
I think that's super important.
And then secondly, to your point, being very intentional about why you're using the tool and why you're, you know,
[22:10]->[22:42]
like what problem are we solving for as opposed to let's just go and buy loads of new tools.
And we've seen the disaster.
I think a lot of companies did that last year and they're paying the price this year.
Uh for that um they're like oh all of these amazing productivity gains that we thought we were going to get where are they
um you know and uh and even us with atlas and i mean i don't mind saying this with our adaptive learning platform so a lot
of my conversations when i'm chatting to companies i have to slow them down which is counterproductive because i would make more money
[22:43]->[23:16]
But it's like no no what what is specifically the problem we're solving for and getting super concrete on that as opposed to yes
we can upskill your leadership team and do sales enablement and onboarding but no no let's just take take a step back like what
are we what is the problem
That we're solving for and then work from there.
One of our recent examples actually is performance reviews.
So building off the back of the performance reviews,
feeding that straight into Atlas to build learning pathways based on the data from the performance reviews, right?
[23:17]->[23:49]
That originally wasn't even in the scope with that company.
But then when we really delve down to what are the biggest challenges you're facing is our managers need to be able to practice
having these conversations and they're struggling.
So now they can practice having that conversation with Atlas and our AI voice coach in a safe environment, then go into their meeting,
right?
And build that.
So it's really interesting.
Everyone's kind of got this fear of missing out as well.
As you scale and consolidate,
[23:50]->[24:09]
What are the questions that you're asking to really narrow down that list and ensure that you have the right partners?
What are the must-haves, the non-negotiables for you and the team to be like,
because I think that's really interesting for both the HR leaders listening, but also maybe any vendors that are listening right now.
[24:10]->[24:18]
Yeah.
The first thing that comes to mind, like, you know, when we start to look at like the problem statement and then like,
you know, how do we address it is the scalability aspect of it.
[24:18]->[24:19]
Okay.
[24:19]->[24:50]
Are we able to scale?
Are we able to scale without trying hard to influence the product roadmap?
Or are we able to scale by customizing?
If the answer is we are going to be customizing things to scale, then that's a big red flag for me.
We don't want to bastardize the tool.
We don't want to sign a contract on a cloud platform and then end up just customizing, deviating, defeating the purpose,
and not taking advantage of a cloud implementation.
[24:50]->[25:22]
So for me, that's one of the key factors.
And how do you actually integrate with several other technologies?
The chances that we are going to have one global payroll system, very minimal.
One global time and attendance system,
Probably not.
We have 57.
We are consolidating to six or seven.
The same thing goes for talent.
We use Cornerstones today.
We are implementing Eightfold.
And then there is going to be an iSense implementation.
How do we all speak to each other?
Do we need all of them, five years from now?
[25:23]->[25:53]
The contracts that we are signing today, do we clearly understand where the product's actually headed and what's the scope of work?
Is there any duplication?
What is the data entry?
Where does the data reside?
All of these are the questions.
A lot of times, you'd be surprised, we had a big Oracle shop, and when we had to sign this contract with Eightfold,
knowing that we will have to go through some HR transformation in the future, like a big transformation to consolidate,
We went to each one of these partners, the top three, right?
[25:53]->[26:08]
Like SAP SuccessFactors, World Day, as well as Oracle, and said, like, what is your partnership debate for?
Tell us a bit more about, like, how do you integrate with them?
Is there a duplication?
Despite the fact that, like, you know, that's probably, like, three, four years away, we still, like, do that.
Yeah.
We're picking the right vendor.
[26:08]->[26:44]
Yeah it's so important i think one of the challenges now is like the pace of change is is exponential like there was a there
was a a point in time where you you would be with the same technology partners for a very long time and not much
would shift and change but with ai
It's like you can't even you can't talk about five years three years maybe even one year because like you know the products are
changing so fast right so that makes adds another level of complexity into these decisions um and companies also are promising the dream
[26:46]->[27:16]
In many cases as well.
So you also got to be careful of that, right?
Because like, you know, even when we met or at the last Unleash or HR Tech,
like there was a lot of vendors there claiming to do certain things and having certain, you know, new products that quite frankly were,
you know, just marketing.
Right.
So how do you ensure that you do the right due diligence when you look at that roadmap?
[27:17]->[27:47]
Yeah, for me, like, you know, the critical thing is like before I buy or like actually even build, like, you know,
I would like to experiment that in a lower environment.
That's my first.
Yeah, that's my first task.
Right.
I don't want to be like, you know, relying like the whole thing decision making process based on a demo.
Let alone slides.
I don't even go there.
It's not sales anymore.
I want to get into the demo, right?
And then from there, implement this in a lower environment for a subset of a population.
[27:47]->[28:20]
Let us play around with it, too.
And then we start talking about the ease of implementation.
A lot of times, you don't even have to build the integration.
No.
Not for the pilot.
Yeah.
You do that.
And that gives you like such a good view of like how complicated the program or like the tool is.
And then where you need to like invest.
Majority of the times, like, you know, it goes the other way around where people are very excited because they have a budget or they
have a problem and they want to like sign a contract today.
[28:20]->[28:54]
And then we start like, you know, putting the solution together, the requirements together.
And then we realize, oh no, that's a huge gap.
And then comes the change request.
And then like, you know, all of a sudden it's all technology issue, which is my team's issue.
Let's hit a reset.
Let's go back a step and then let's experiment.
Let's actually try to get to the bottom of what we're trying to solve and how are you going to reap the benefits and value
out of it?
Finance is coming in very smartly these days saying, if you are going to tell me that the ROI is
300K, I'm going to reduce your budget by 300K next year.
[28:55]->[29:07]
Yeah, yeah, yeah.
So you better be making the right decision.
We better be making the right decision and we better be not painting a rosy picture saying that, oh, the benefits like...
[29:08]->[29:13]
Well, you see that with the talent marketplaces, right?
[29:13]->[29:46]
Because they talk about this many hours of unlocked, this many unlocked hours, and then each hour is worth this much,
which means this amount in the millions, right?
And it's like, oh, really?
Okay.
You can't be telling finance that because then they're going to take away that budget.
Yeah.
From you as well.
You mentioned earlier about obviously the more focus and more mood this year around agentic.
Like for the casual maybe that's listening, we talk about AI and then we talk about agentic AI.
[29:47]->[30:00]
Where do you see that having the biggest impact?
Give me some examples of particular areas of HR where you feel like the agentic capabilities are really gonna help create a whole new
experience.
Yeah.
[30:02]->[30:33]
A couple of high-volume examples.
A majority of the Americas, especially in that time, and Mexico, if I take Mexico into account,
the request for time off or just understanding PTO balance.
There were days where you had to go to an application, there is a hyperlink, you have to click on it,
go find out what your PTO is.
Then you request a time off by inserting some complex steps, going through some complex steps, or pulling up an article.
[30:34]->[31:06]
AI came in, helped through that process.
AI is able to pull that information, and then it is going to tell you what your balance is.
So based on the integrations, it already started speeding up the process.
But you still have to go click somewhere with the time off request.
With the agentic stuff, we're eliminating that, right?
Like we're saying the AI, agentic AI, the agent's actually going to create that entry for you.
That's one of many, many examples, creating a position, just like promoting someone on your team.
[31:07]->[31:33]
All of this can actually be a workflow and an agent can actually write that for you.
It ensures that you don't have to pick a cost center.
It ensures that you don't have to pick the position ID, job ID, and all of that.
It resides behind the scenes and Eightfold's playing a role there as well from the beginning.
So those are some very, very basic stuff, but it's highly impactful because of the model.
At scale, yeah.
[31:34]->[32:06]
I think what I'm excited about is now moving to more predictive and prescriptive
We've spoke about this for a long time in people analytics.
I remember talking about this like eight years ago when it was HR analytics.
But now with AI, we can actually start to do some of this stuff that we dreamed of.
So you're not waiting for an employee to go and reach out.
We're actually nudging them in the moments that matter with what they need at the time that they need it.
[32:07]->[32:37]
And embedding AI into work itself
And embedding learning into work itself, right?
So as opposed to it sitting separately over here somewhere.
Like learning is a perfect example, actually.
It doesn't sit within, it doesn't sit in work.
It's separate.
You have to go over to make time to learn and land in a sea of LinkedIn videos that now I'm in LinkedIn learning
and I've got a thousand videos, right?
[32:37]->[33:08]
Like how do you make sure that that shows up
Just before that meeting when you have a difficult conversation and you want to make sure you've got some training or if it's something
technical you know whatever it may be it needs to come up and show up and I think like whether that's a notification in teams
or like you know embedding it but at the moment a lot of these systems are like you described are fragmented
The companies have like a coach an ai coach over here they have an lms over here they have content libraries over here they
[33:08]->[33:24]
have a talent marketplace with learning modules over here and none of them speak to each other and there's no there's no consistent employee
layer experience layer does that make sense this sits on top it does like you know and uh i can give you like another
[33:24]->[33:51]
example like where we still uh have like a ways to go right like i talked about ai assist
Let's say that you are going to have a conversation about a developing impact.
You're just saying that someone didn't perform the way it's supposed to and they're part of your team.
When I actually select that or add comments, wouldn't it be amazing if the AI coach just pops up saying,
I see that you're disagreeing.
Let's have a chat.
How can I help?
[33:51]->[33:54]
Exactly.
That's a great example.
That's a perfect example.
[33:55]->[34:13]
Yeah.
That would help so much because now,
Instead of me being reactive and being proactive about the conversation, I'm going in like, you know, well prepared.
And you're creating the framework so I don't have to reinvent the wheel, nor I have to reach out to HR, right?
I'll keep them informed.
But all of these conversations, I think are going to be like, you know, the game changers.
[34:13]->[34:36]
Yeah.
And that agent or coach that pops up, it knows the context.
It knows who you're having a meeting with.
He knows their role.
It maybe has access to their employee record.
All of the information that you have.
So it's not just giving you random generic feedback.
It's context aware.
And I think that's where it gets really exciting.
[34:37]->[35:08]
I think that could be very helpful.
And we just went through a rebranding ourselves.
Last week it was announced broadly that
We used to call ourselves HR Services and Transformation, and my team was HR Digital Services.
Now we call ourselves people operations and people technology.
So we are catering to people.
And where I see that difference is clearly visible now is that people tech used to document the past.
In the past, that's how it was perceived.
[35:08]->[35:16]
Now it's all about shaping the future.
It's readily available and that's where the predictive analytics and all of that comes in.
[35:16]->[35:27]
Listen, before I let you go, I could talk to you forever.
What are you most excited about?
As we look ahead, new year ahead of us, what are you most excited about?
[35:28]->[35:44]
I am very excited about creating a seamless experience for employees so that they don't even have to think about it.
The best experience that you can give to an employee is that when they don't worry about how to do it.
They just know how to do it.
Or they don't even know they're doing it, right?
[35:44]->[35:50]
Like you don't have training because you don't need training because the experience is so good you don't need a training for it.
[35:52]->[36:25]
And then I think what I'm also excited about is the education that's happening.
In general, people are upskilling and now they're seeing tasks as journeys.
We are starting to experience that as a journey instead of, hey, there's a traditional way to do it.
These are the number of clicks or system hopping and all of that.
It's more about a journey for an employee, for a manager, for HR, and we're just putting all of that together.
And I do feel that the tech that's relevant today is probably not relevant in the past one year or two.
[36:26]->[36:41]
So you need to forecast that.
And that's where you have to take calculated risks.
You cannot be 100% safe all the time.
You need to know where you risk it and then where you actually have to scale back and create a foundation.
So I think that gets me excited the most.
[36:41]->[36:47]
Yeah.
I mean, honestly, I feel like I've been doing this for 20 years now.
How long have you been doing it?
How long have you been in this space?
[36:48]->[36:51]
From like 2006.
So about 20 years.
Yeah, about the same.
[36:51]->[37:28]
I feel like there's never been a more exciting time.
Right.
Right.
I mean, there's a lot going on and it's hard to keep up.
Right.
But I feel like that's, that's why it's fun.
Like, cause it's constantly evolving.
There's never a boring day.
Um, it's a, it's a journey, not a destination to your point.
And, uh, we're seeing that with skills, like the half-life of skills is so short now.
Like we don't even know what the skills are going to be in the next couple of years.
There'll be new skills that we don't even know about.
Right.
Right now.
It's an amazing time and I appreciate you taking the time out to join us on the show.
[37:29]->[38:01]
Yeah.
No, no.
Thanks for having me, Chris.
And then I'll leave it with a note.
I think especially for folks who are watching from an HR standpoint,
I do believe one of the things I recently learned from our CEO, Olivia Bloom,
was that HR is continuing to become an intelligence layer for the enterprise.
And I truly believe that.
I do believe that now gone are the days where we were at the back office.
I think it's an intelligence layer.
For a tech transformation to actually take off, we really need HR to be in the forefront.
[38:01]->[38:07]
Yeah, I agree.
I appreciate you.
Enjoy the rest of your day and look forward to catching up soon, okay?
[38:08]->[38:09]
Yeah, likewise.
Thanks so much, Chris.
Arun Serikar, VP, HR Technology, Digital Platforms & AI Innovation, Corp Functions at Schneider Electric.