Spilling the Tea on HR Tech - Toning down the AI hype, Oracle’s big win, good news for the global payroll market, and how the tax code is related to tech layoffs.

[00:00:00] But listen, here's the point. Starting just around 2022 and into 2023, those started having an impact, right? If you're saying, okay, well, I'm only gonna get 20 or 30% of their salaries back, that's gonna cost me a ton on my tax bill. So I'm just gonna get rid of them because basically it's become a liability and it's not worth the gain versus the loss. So what do we see from that mass layoffs and people going to other countries?

[00:00:26] Welcome to the HR Huddle Podcast presented by Sapient Insights Group, the ultimate resource for all things HR. It's time to get in the huddle.

[00:00:45] Welcome everyone to Spilling the Tea on HR Tech, where we find the hottest HR tech news everyone needs to know to be in the know. We break down the news a week and help you make sense of what it means for our industry and how it can impact your organization. And we are recording today on July 3rd, just before Independence Day here in the United States, 2025. We're gonna bring you all the news you can use this week. I'm your host, Stacey Harris, Chief Research Officer and Managing Partner for Sapient Insights Group, a research and advisory firm.

[00:01:13] And joining me today as usual is my co-host, Cliff Stevenson, our director of research and our principal analyst. Cliff, what a hot summer day to be doing our thing, but we're both home, which is a exciting thing, right? That's right. You'll have a little bit of a recap because you did take a trip. I have been enjoying, I'll admit, I love going out there, meeting all you, but I love being at home too.

[00:01:38] If you're watching us on YouTube, you'll see that I'm already getting ready for the long weekend. Got more of the relaxed, Sapient Insight branded gear. It's up to do when you're on camera. But yeah, it's nice to be back. But you know, the reason I'm back and not traveling is because we have received all of the survey data from all of you wonderful listeners, viewers, and it's time to start figuring out what that all means. Stacey, we're gonna have our head in the books, so to speak.

[00:02:06] We are. I mean, we'll have final numbers on the next show, but it is pretty amazing right now to see that we have reached almost, we're probably gonna be there by the time we're done, 10,000 people who have opened and put something into the survey. Now, you all know, you're all service data people out there because you wouldn't be listening to us if we weren't data people. You know that there's a lot of cleaning and a lot of people who open and don't finish or three or four people in the same company.

[00:02:33] So we're gonna be crunching that data down. But still, compared to last year, we were closer to 6,000. The idea that we have 10,000 people who kind of said, yes, there's enough going on that I need to understand what's happening in the market right now. Just I think it goes to show that, Cliff, yes, people are interested. Yes, they're trying to figure it out. But I think they also want to share what they're doing, too. Like, that's the thing that I get out of it. You know, we see our, there's number one reason people take the survey is to get the survey, the actual report.

[00:03:02] The report is worth so much to people. But the second biggest reason generally is that they want to share their perspectives, their voice with the rest of the community. So I'm really excited to see what they have to say. I can't, the amount of write-ins, I stopped counting after, like, we were about halfway through. I was looking on the right and I stopped. I'm like, I, the amount of write-ins we're going to have to analyze. Let's hope our tools are up to this, this challenge this year, right? Yeah, our internal tools, our brains, as well as the technology that we're using.

[00:03:32] Yeah, and all, I'm excited to read all the comments that people put in. When we're at all of these events, you know, one of the things we love to do is just talk to users, right? You're at a small company, you know, there's four people that work there, five people work there. You're doing the HR stuff and you're like, I've used this tool and I just can't, I don't know, I feel like I can never get anyone a phone or I can't get it to get the report that I want. I can't, maybe they call it something different. These little things that, there you have a complaint,

[00:03:59] but they don't feel they're big enough. No one's going to listen. So this is a chance to say that. Now, there could be praise as well, but it's really wonderful when we see that and then we see those companies, okay, let's look at all these comments. Like, oh, yeah, we should have renamed that. And then that happens. That's what we love to see. You know, voice customer is a wonderful, catchy name, but it truly is what it is. It's your voice being elevated in this sense. And I just think it's really neat to watch that come full circle.

[00:04:26] Yeah. And, and I always, this, this week in particular, which is usually the last week, because the survey was closed last week from the dates that we're on. And then we, it's open for about another seven days while people are sort of finishing up and the system kind of closes out. And we still have people who are kind of frantically emailing us like, can I get these last two segments filled out? Can I get two more people to fill out that section of the survey? Okay. Just to thank you. Right. Like, I mean, I know how much work that takes. I mean, I know that

[00:04:52] the report is valuable, but I also know that it's a lot of work for people. And so just, just a big thank you to everyone out there. We really do appreciate it. And, and it, and it, you know, we've already started to look at the data and we're going to talk a little bit about some of the stuff here because I think it's leading into where the market's heading. I'm kind of looking forward to today's conversation cliff, because we get, we're going to have a chance because it's been a kind of a quiet week on the news front for HR to talk about some of the deeper things that the

[00:05:17] market is dealing with like data and the value of it and how we're thinking about monetizing this AI conversation and how we're thinking about reacting to some of the changes that are happening in other industries that are impacting AI, like regulations. And so we're going to have all that today. But as you said, one of the things that I did get to travel to last week, which was really, really nice. So I was in new Orleans at the bank conference, which is basically the women in

[00:05:44] business enterprise national council. And it was really, not only did I get a chance to do this with my partners, which is Susan Richards and Terry zipper. The three of us came together in 2020 to create what was safe and insights group, but Susan and Terry had already had a business for many people who know this called steel bridge, where she was doing advisory services. Right. And it, anybody who does kind of a merger acquisition, kind of a model knows it takes a little while to kind of

[00:06:11] rethink what an organization is when you bring two groups together who are doing two different things. We had all the research, all the data, all the people who are working on that. They had every working on their advisory services. I think this is the first year and this event really was it, it was so nice that we were kind of cohesively talking about where we're at as an organization, helping organizations through big decisions that they're making with the research, with the data, with the advisory services. So it was, it was a really nice event for us, I think,

[00:06:39] to culminate that, you know, we've been at in this business for over five years where we're a women led business. It was, it was a great place to be, to both be speaking and to, and to sort of connect up with other organizations who are similar to ourselves. The event, if you haven't had an opportunity, I did a big LinkedIn post on, I would really recommend going out and taking a look at it. It really is a great community of small business and entrepreneurial women who are really making a difference in the market. The numbers we have from one of the researchers who does a big research

[00:07:09] on the women in business was, you know, we're looking at, you know, $2 trillion worth of, of revenue just from, you know, the, the, that small amount at that event, those businesses, right. Hiring over 10 million employees in the market, right. Just, just really big data and numbers and stuff. And so I, it always makes me smile when I think about what an impact it is when you help elevate different roles inside of the organizations and inside of the market. And what was really nice is,

[00:07:34] I think, you know, leadership can be a really lonely place, especially when we're going through a lot of changes like we are right now with the, with the changes in regulatory processes, with the changes in the economy, with the global unrest. It was a good place for a lot of, of people to get together, to have those similar conversations and also talk about things that women particularly deal with in this work environment, which is being caregivers. A lot of times managing, you know, the challenges that we have with getting investments, you know, the challenges that we have with being taken serious,

[00:08:04] to be honest, in, in, in, in technology or in industries like construction or metalworks, you know, it was, you know, how we as a group of professionals are doing the work that we do every day that is so strong and so important, but also how we can help each other just to make sure that we know the value of the work that we're doing. Right. So it was really, really good event. We got a chance to, there's a couple of people of organizations there that we should call out, but I was really glad to see that ADP was there supporting the organization. We saw quite a few

[00:08:34] of the big consulting firms, almost all the large, like Deloitte, PwC, KPMG, E&Y were all there. We also, I got a chance to speak with quite a few people from some of the large tech firms. Salesforce was there. Apple was there. Amazon was there. We talked to all of them while we were there. We also got a chance to talk to some of the large manufacturing organizations like Boeing and Cisco and networking companies. Right. So it was a wide mix of organizations, large banking

[00:09:02] environments that many people would know. And then there was also a lot of really small businesses. Again, if you go to my LinkedIn site, you'll see like one was a really great small business that is doing these amazing stickers. Nice stickers may not seem all that exciting, but I know my Gen Z kids love stickers. They're putting them all over stuff. Right. And these had, again, depending on your, your view of, of what's, what's funny or not, but they were just really great commentary about, you know, just being a female and sort of punching through things. And so, and then we met a wonderful

[00:09:31] woman who does events out there. There was a great young business and he's called Naxio. It might've been, but it's something in those range, but she was an MIT student who was there with her small company. She was 22 years old and she was doing a new technology, new bio engineering material to replace Kevlar. Her material was stronger than that. Right. And so it was really, really nice to go and just see the amount of ingenuity, the mind of innovation that we're seeing in that market.

[00:10:01] And it was one of the first events I've been at in a long time, Cliff, where there was maybe three booths that had the word AI, only three. The rest were a lot of other really good stuff. And the AI booths weren't packed. I, you know, again, good or bad. I didn't quite know what to quite to make of that. We were at obviously all the AI booths, but the center of this was not around AI's technology. A lot of people knew AI, but it was much more about manufacturing products,

[00:10:28] services, and how AI was part of those conversations, which I think is, that feels good too, right? It's not at the center of every conversation. So, so it was a big event. Yeah. And that's interesting because I think we have been surprised by, you know, being data people, you know, we started to really think about that last year about, okay, less companies are using AI than maybe we thought. And it's because when we're doing what we do, we hear AI all the time.

[00:10:56] And it's something that we are cognizant of and we try and think about for this show. Not everyone is all that interested. They may work at a manufacturing plant and they're saying, I need to know more about some supply chain stuff, you know, or some other things. And, you know, even in our conversations in the last month or so, we're hearing more and more organizations say, what we're trying to put forth is idea that, yeah, we have AI underpinning some of these processes, some of this back office stuff. We're going to even talk about that infrastructure,

[00:11:26] but we are focusing, we're hearing it loud and clear. The market wants to know, how are you solving the problem that I've got? Which is very rarely something that's specific. Oh, I need AI. It's something more like, I need some trucks at this location, right? How is this? I need people. I need, you know, trucks. I need something like that. How do I get people certified for this forklift? You know? And it's like, okay, you don't come and say, AI will do that. It's like, what?

[00:11:51] What? Yeah. Construction was huge at this event. Like I, I was a lot, because there was a whole retail contingent there for retail stuff. And every one of them said, if you're a local construction company, come talk to us, we're refurbishing our businesses. There's no AI that's going to come in and help you figure, I mean, it might help you to figure out the drywall, but it's not going to lift the drywall for you right now. Right. That's right. That's right. Oh, I, I don't know if that's a, that's probably the worst possible segue into our first story.

[00:12:19] We did that in the pay scale, but we can go there. Let's try and figure it out. No, it is why we are going to, we, however, are going to talk about AI because it's very important in the world of HR tech and some of the big expansions and quarterly results that we're going to be talking about are very AI centric. So the first story is that pay scale is expanding globally into Romania. They put a technology hub in Bucharest in the capital.

[00:12:47] If I remember my geography well enough. So, and that will largely be focusing on, on AI building technologies through AI. They have really looked at the talent that's available and the sort of friendliness to business. We're going to talk a little bit of fact about later on, here's a little teaser, stay in about why this may be happening. Why we might be seeing a shift away

[00:13:16] from people deciding to do this in the U S and instead going overseas. And, and a little bit of a spoiler has something to do with taxes. I know that's really got people excited and they're going to stick around when they get to hear that. But yeah, so pay scale expanding into Bucharest in terms of physical location, but this also means, you know, global growth for them, but also means that they're expanding more and more into the technology and R and D side with a lot of focus

[00:13:44] on AI underpinning of what they're doing at pay scale. Yeah. And this, I, first of all, we've seen pay scale really take off. You know, they did a lot of acquisitions over the last couple of years. I think they're now solidifying sort of what they're offering. And for those who don't know, pay scale is a compensation application point solution to a point. Cause it's more of a platform of compensation. So, but it's got, you know, the, the surveys, the data, the management levels of compensations, the, the insights that I always tell people,

[00:14:13] oftentimes they would be surprised by how much skills data and certification data is inside of these compensation platforms. What I, you know, Chris Hayes, who's their CEO was very clear that of Chris offered kind of, as you had said, engineering, you know, exceptional engineering talent, business-friendly EU time zones and a mature innovation ecosystem for, for what they want to do going forward, including the global expansion of their work. It is tough to get compensation systems to sort of think globally, work globally because of the differences in regulations

[00:14:42] around compensation, the differences in just the actual money and funds and those kinds of things. So, so I think this is a good move for them. I do think what we're going to see, and we'll talk more about it, as you said, when we get to the tax conversation, but we are seeing more and more this outsourcing of the services and the technical work. Now this is not new in the tech space. Like, I mean, we've been outsourcing much of our customer care. We've been outsourcing

[00:15:07] much of our programming and development, a lot of it to other regions, including, and other countries, including India and China, as well as Eastern Europe. What I think I'm seeing here, that's a little bit different in the market in general, right? Is that, is that services is one place where tariff conversations don't have as big of an impact, right? And so that on top of the fact

[00:15:33] that the environment here in the U S is a little bit less friendly for right now, anyways, for immigration, for visas, for some of the things that, that sort of have up to this point, been a value proposition to sort of maybe having your leadership of those, of those sort of entities in the United States where they can sort of be with the other leaders in, in sort of a U S based organization or the senior positions in those roles be in the United States. What I'm starting to see is that, yes, we're continuing to do outsourcing. We're probably going to do outsourcing a little bit

[00:16:03] more. Our, our, our numbers are already starting to look up and outsourcing and our data sets this year across kind of the IT technology, all that stuff. But we are also starting to see the leadership of those outsourced functions now also being sort of hired within those countries where they're at. And that I think is a unique kind of a conversation that we haven't had in the U S previously. Previously, the whole goal was as much as possible to get as many people into the U S

[00:16:29] environment at the cost of point that makes sense. And then have a lot of the, the work being done in the more cost-effective areas from a regional perspective. I think that's shifting just a little bit and we'll see how this plays out as some of the things happen in sort of our own regulatory environment, but it's something to watch and be very aware of and be very, I think, under understand sort of how that's going to impact some of the decisions we make at the tech side and how it's going to impact some of the decisions we make from a hiring and a workforce planning perspective too. Right.

[00:16:57] Yeah. It's a, it's a very good point. And as we kind of keep talking about this expansion worldwide and how that's playing out, EPI, USC, EPI use, depending on how you want to say it, is expanding their partnership with data scale HR. Now they already had that partnership. And by the way, EPI, USC are a implementer and more for SAP, right? Amongst a number of other people in what

[00:17:23] they call the elephant group. They do a lot of the sort of inter services for these organizations and data scale HR is now going to be their worldwide reseller. So AI native payroll, made of middleware, I guess, is I think the term they like to use. So really thinking of ways to, again, expand out the, the one thing that I think you pointed out that I thought was pretty interesting

[00:17:50] was the, the CEO, I think it was of data scale HR or was this, no, this was from API. It was data scale HR. Yeah. So data scale HR, I think it's, it's very worth starting to watch. What I would say is the integration platforms and the, the systems that are figuring out how to, and again,

[00:18:13] not just API integration, but are figuring out how to use AI best capabilities to kind of aggregate and combine and basically be sort of like the hub of data at going in and out of your various systems, but becoming more of a centralized model. And that's what data scale HR is particularly for payroll, global payroll users. Right. And what I really thought was, was interesting is when you, when you look at data scales,

[00:18:40] CEO, which to make sure I'm going to get his name correct. Of course we don't have it on the link here, Cliff. Oh, I, Jerome Gouvernell. I, I had it and replaced it at the last second. Yeah. Yeah. Yes. Jerome Gouvernell. I was so, I was trying to figure out the pronunciation because I feel like every episode there's a part where we have to apologize. I'm like, let me make sure I'm getting

[00:19:07] this name right. But yeah, the background is amazing. You know, ADP as a general manager for 16 years, he was, and through the VP, he was also at the pay group with by deal. Right. And then came in to be experienced as, as data scale HR. So with that kind of a deep background, an understanding of the global payroll, so the need to have that reconciling sort of software, right. That's in the

[00:19:33] middle of everything that maps all the data plays. This is the integrator on steroids to some extent that we've been talking about for quite some time. And so again, I don't know enough about data scale HR. I think probably our friend Pete Dallas would probably know more and could be able to fill in more roles in this, but I do see more of those kinds of solutions. And a lot of the other traditional integrators were picked up by organizations like ADP were picked up by organizations who other software

[00:20:01] players in the space. So we're, we're needing more and more of these kinds of neutral vendors in the middle of these spaces. And I think that's what we're seeing. So I think it's just a place to watch. I know integration doesn't sound nearly as exciting. APIs don't sound nearly as exciting, but I actually think in the world of AI, there was a whole conversation about workflow that we're going to get into a little bit later. Whoever owns some of that connective tissue in the processes

[00:20:26] is really going to make out on where the AI future is, right? That's exactly it. Yeah. I sort of, we sort of teased at the beginning, right? This whole idea of the integrations, the connections, the whole infrastructure, I think is where things are headed because I think that that's where there's going to be a lot of strength long-term, right? You know, I think people are reacting very much to

[00:20:50] this idea of what is going to last through this sort of, maybe not boom or bust. I think I've said expansion and deflation period of AI and where is going to have the most long-term staying power. And I think people are starting to shift money and thoughts towards that as more and more sort of specific use cases get sort of snapped up. Yeah. So this next one is pretty interesting. I think

[00:21:17] this is going to get to our data nerds. We shouted out earlier, so you'll get a kick out of this, but also there's a little something here for my recruiting people. One model has released their newest update and there's some new product features. A few things caught our eye. I think you and I both really liked having some ideas for some visualizations. I really liked the scatterplot

[00:21:41] is very cool. The reason why is I think it helps people understand correlations and connections better than just a number, right? If you go, oh, this is, you know, 0.65 correlation, you're like, okay. But when you see it's like, okay, over time, this goes up and you see that's a dot and that's a dot. And then you say, oh, I see. So there's definitely a connection, you know, and that's what underpins the math.

[00:22:08] So seeing those sort of scatterplots to figure out the connection between two data, you know, variables, I think is really cool. And then I really like to see some funnel chart enhancements. If you work, this is very big for recruiters, right? It's basically, but sales as well. Basically, I'm talking with my hands, which is very useless for anyone who's doing this podcast.

[00:22:33] But basically, imagine a funnel, right? You might see anywhere. At the very top, it's very wide. That's where you have most things coming in, most candidates, let's say. And there are different parts as it slims down. And you can see when it's visualized, as much as you see where you have sort of choke points or why are more people falling out here is it's our interview process. Oh, I see. Or, you know, we're taking too long for our first reach out and all of a sudden everyone's dropping out.

[00:23:00] When you can see it, it means a lot more than just saying after 2.6 weeks, we see a 4% reduction. People are going, again, I don't know about that. I need to know specifically. Then it's very obvious where the problems are. So those sort of visualizations, it might seem on its surface, if you don't work with data, like, okay, that's, you know, that's weak, but that's what people rely on to make decisions. They don't have time to do a million things. They need to be able to see something. It makes sense to them,

[00:23:28] but it's also accurate, right? Anyway, that's my plug for visualizations as a concept, I guess. I think it's a great plug. And definitely we, it's important to us. One model for those who might not know is a analytics and planning solution in the market, right? Distributor of the survey. So thank you as well as as many of the people are that we work with. What I really think is interesting to your point, Cliff, is that they've really kind of taken on two roles in there as sort of a big thing for their solution, which is one is they like to be an integrator of multiple

[00:23:58] data sets. So that's really a value prop for them that they kind of, they've made it easy to get data in and out of their system, right? The other thing is, I think they're really emphasizing their visualization, which we do see some tools do really well in visualization. Some do really well in data cleaning. Some do, right? Every analytics platform kind of has their thing. We're definitely seeing one model really focus on that visualization part. And I would agree. I mean, the funnel is always an interesting one for me. One of my favorites, because I mean, we look at it on the research side,

[00:24:26] right? We, we, we tend to look at the data as like, here's all these people who come at 10,000 people hit the survey. At what point are they falling out? Which question caused them to go, my head's about to explode. I've seen too much. I need it. I need to pull out of the survey. At what point does it become too difficult to, to do what people are asking? That's along the way. Recruiting is really good. Oftentimes they'll find there's one question and one thing that basically, you know, kills the pipeline and you don't get the kind of diversity or the kind of group of people

[00:24:54] that you want down at the, at the final reviews. Those are why funnels are such good technologies and good tools. Scatterplots, not, I'm not as excited about those, but that's just because I'm, scatterplots are, are really hard to read sometimes, but I get the value proposition of them. If you have a 0.6 correlation, you're doing really well by the way. By the way. Yeah. So, but yeah, no, it's, it's great to see these tools. I think, yeah, they have an AI assistant. They've done some updates too, which I think, which is good,

[00:25:23] you know, some, some better messaging and stuff, but it's good to, to, to remember that, you know, data, even when it's not assisted by AI is valuable in and of itself, right? Like it has real value when we, when we, when we do a better job of storytelling, right? Yeah. And I think that's it that I'd mentioned about storytelling because ultimately the data is only useful if it's being used for something, right? It's being used to make decisions. And in order to do that,

[00:25:47] you have to think about what may, what tells that story, right? But if it, maybe it is a number, if you're going to IT or something like that, and that's what they would see, but you have to think about your audience and how to best use any piece of information in a way that will become apparent to them, but also doesn't mislead. So, you know, visualization is very important. And also one model we should say, we keep saying it kind of all one word because they used to always sort of stylize themselves that

[00:26:14] way. It is now one space model. So in case you knew them before and you're looking for them online and you're like, anyway, if you notice that change, same company. I don't know about you, but I don't know very many people that are hopeful about the world of work. And I'd like to change that. My name is Marcus Mossberger and I started the Hope at Work podcast where you'll find two things. Number one, really interesting guests. And number two, innovative ideas about the future of work. Check it out.

[00:26:43] Wonderful people there. So, so some other expansions going on. This one, I should say, really beyond expansions with just some new stuff coming out. Rejig has launched their work architecture platform. This is, I think, really big. This is one of those ones that I think that this show, not to now blow our own horn, that we do well, is finding these things that may not have flow, might not have caught your eye. If you're, you know, you're busy, you've got a full day,

[00:27:12] you don't have this opportunity to go through all this and you might just say, okay, yep, one more story. But this is kind of big because I think it really shows something we've talked about well over a year now is this idea of thinking about skills, you know, over jobs and, you know, how technology is going to affect that, you know, how do you have beyond skills inventory and taxonomies, but, you know, how do we really start thinking about

[00:27:36] how organizations structure themselves around skills, right? So this is one of the first times I think we've seen an entire sort of recapitulation of this whole concept of an org chart to be instead focused on where skills are, what tasks and goals need to be done. And so, yeah, that's from Rejig. I know we've got, we know, you know some of the people there too as well. You've worked with them

[00:28:02] for a long time. Yeah, Siobhan, we've done quite a few briefings with Siobhan and she was on one of, Rejig was on one of our, I think last year or the year before, she was on one of our emerging technologies to watch list that we put out at the end of our HR tech conference event. We're going to be doing a little more of that this year as an FYI in the actual paper this year. And she's proven out that her approach to skills is different and unique from what we've seen in the rest of the market, right? And I was, I, even when we were having conversations with her,

[00:28:30] it was always a challenge for us sometimes in our research is because we do the survey where we have to get enough responses before people can sort of show up in the data. Sometimes it's a little hard for smaller and emerging technologies. We do that in a couple of different ways. A lot of it is through briefings and stuff that Cliff and I do and making sure that we're just up and aware on those relevant items, but we are going to try and start to get a little bit more of that in the report. But I will say this year, we do have a skills and talent, intelligent category that we will be tracking.

[00:28:58] And I think I was looking today, I think we got enough data to at least do an aggregate view. I don't know if we'll be able to break it out by size. We're going to see if we're going to have enough to make a break it out by size. It's the first time that we've done it this way. It will be really interesting. There are a lot of ERPs in there. There are a lot of suites, and then there are a lot of point solutions in there. We'll see which ones sort of come out on top and the user experience and vendor sat. But I do think in this particular space, what Shaivon's done and what they've done with Rejig is like you said, a unique way of flipping the

[00:29:25] conversation about the work, just the org chart conversation. What I do think we have to have conversations about is sort of as organizations are working through these technologies is how, how do we reset up our business models, our workforce planning, all the things that we have done for years and years, our recruiting models to fit these new ways of looking at the work.

[00:29:53] We're going to talk a little bit more about that with job architecting, right? And with the idea of, is it jobs really anymore or is it tasks? And how does that look in this new world, right? One of the people advising that's on the advisory board for Rejig and Shaivon is Amy Wilson, longtime friend, has come out of working for, was an industry analyst for many years, worked with Workday for many years, worked with SAP SuccessFactors for many years. So you can see the influence, I think, of people who have been in this space for a while and how

[00:30:22] they're rethinking this market. As we get into this space, I think the conversation will come down to what is a job versus what is a role versus what is a skill and a task and how do we start to manage those differently, right? Yeah, absolutely. I know I should be mentioning the Shaivon, she's referencing Shaivon Savage or possibly Sauvage. I'm probably overpronouncing it this time, but yeah, that's the CEO and founder

[00:30:49] of Rejig. So you mentioned sort of the up-and-coming companies that people might not know so well. This does not fall into one of those categories. This is a well-known company. This is Oracle. Now, Oracle had been interesting not because of their sort of hyper growth, but it seems like they had been sort of stagnating for a little bit. I think they themselves would say that as well.

[00:31:13] But we have seen something pretty interesting, some pretty big Q4 fiscal year 2025 Q4 numbers, but also just one big contract that was just announced. I think at the time of recording, this might've just been yesterday or even today, 30 billion annual cloud contract. A little bigger than the contracts we get here at Sapient Insights Group, but if you're listening, we're available.

[00:31:39] But this whole thing about them able to secure this contract, we don't know who it is yet. There's plenty of speculation online. Feel free to go through there and all we're doing here. But when AWS and Amazon Web Services and Azure launch and even GCP, those were all very early on, AWS in 06, you know, those 210, Oracle's sort of competitor to that, to that sort of infrastructure as a service.

[00:32:08] Infrastructure as a service is the term that everybody uses these days, right? There we go. That's it. That didn't really come around until almost five to almost 10 years later, in some cases, to the competitors. And in that time, it seemed like they were playing catch up. But what was pretty interesting is in the new sort of Gen 2 build of OCI, they have gone sort of a complete rebuild, really put AI at the forefront of what is going on in the back end, right? It's not

[00:32:36] that sort of cool, fun story-making AI where it's doing the generative stuff. It's instead doing a lot of the fast compute that needs to be done and that can learn from what's going on back there. And since then, yeah, we've seen Oracle get this huge contract. And along with that, had just an absolutely stunning Q4, fiscal year 25 Q4. I should keep mentioning that in case people are listening,

[00:33:01] what year does he think this is? So an 11% revenue growth in that period, that's for a company of that side, that is not common. That's incredible. So an 8% rise in total sales overall for the entire year. So really finding that doubling down on this sort of line of business has been where they feel their strength is. I know we're going to be there. So we'll get to hear more about this.

[00:33:29] We'll get to hear some more at Oracle World, right? But I think the bigger conversation I've seen in this one is, I think when they got into this space, there was a lot of like, why? Why would you get into the hyperscaler space? Why are you going to try and compete? But what they were ahead of, and whether Larry saw this coming down the pipeline or how they plan this, right, was the need for the amount of space and just sheer power that AI is requiring, right? So what really, this is a reaction. The expectation

[00:33:55] is that this big deal has to do with some large AI firm is that AI requires so much more server space. Like if you guys ever, if anybody was back in the internet days, like you had your own little server, your own little, every little town had their own little server environment. And then it all kind of aggregated up to cloud hyperscalers, right? And then there was this idea of, are we going to go hybrid on-premise or not? But this is truly sheerly a conversation about amount of servers and space that you have and how much compression you could have inside of these environments.

[00:34:24] And Oracle made a big play on this. And I don't know that, so there is this conversation, but what is going to be more valuable down the road? Is it going to be the space or the energy or the server environment to run AI? Will it be the software, the applications, the environments, right? Or will it be the data inside of all of it? And we don't know the answer to that, right? No. But someone who is doing some good work on figuring this sort of stuff out is Albert Pang.

[00:34:52] I wanted to give him a special shout out because he did compile a lot of these numbers. I'd advise how close the race was for sort of number three in this infrastructure as a service data scaling world, hyper scaling world, that there's a good chance that they could take over Google Cloud for that number three spot falling behind AWS Azure. So pretty interesting stuff and really neat. It's interesting because, you know, sort of we focus a lot on the up and comers, but it's pretty

[00:35:21] cool when you can see a legacy organization of that size still manage to, you know, bring that sense of, you know, agility that you sometimes have to lose when you're a big company, right? It's more maintaining. People love to tell the story of IBM switching from hardware to services. This could be one of those things that we end up talking about years down the road where we say, okay, Oracle was,

[00:35:47] you know, on the brink and made a comeback because of how they shifted their business model. So very, I think that's very interesting and we'll keep an eye on that. Like I said, we'll be at Oracle Cloud World in October, November. We'll talk about all of our events in just a bit. But, and speaking of events, we do have some new positions. Jerry Ting over at Workday is going to

[00:36:12] be the VP head of agentic AI, has to be one of the first people with that title. You know, all these, whenever there's a new tech, it's so funny to say, okay, I guess we need to have a position for that. Not just AI anymore. Now it's head of agentic, right? Yeah. Yeah. That's right. That's right. We saw probably only a few years ago, we saw our first CAIO, almost a chow. And now we have a head of agentic AI and Evisort, which is where he'd come from. He was the founder and CEO of Evisort. I still, yeah.

[00:36:40] It's worth noting that Jerry, that Evisort was the AI solution for reading basically contracts. So it's on their supply chain management side, contract reviews, and basically taking that OCI technology, which has been around for ages and translating that through an AI model. I, the most interesting things I've seen happening in AI recently have been very much with this kind of eye, especially for

[00:37:06] agentic, because it is this idea of the amount of paperwork, amount of PDFs we all work in and having tools that will read that effectively. So Jerry's got that background and he's got some other things as well on there, but I think that's definitely where that's. Yeah. Yeah. I love kind of seeing some of the backgrounds, you know, we talked about Jerome earlier. He still teaches at Harvard, Jerry Ting does, and had worked at Credit Suisse and also Yelp and BCG, which will give you a giveaway, Boston Consulting Group, about where he's living. So,

[00:37:37] you know, as someone who used to live in Boston, you know, represent, well done. So because we do have, you know, a little bit of time or do we love to talk a little bit about some of this stuff. We mentioned taxes. That's what you've all been waiting for. Here we go. So why do we bring this up? Because it starts to shed some light on something we have talked a lot about on this show. And we just talked about earlier in this one, which is what is fueling all this layoffs

[00:38:03] and what is the impact on these bills that, you know, you get buried and it's like, oh, there's just some tax stuff in there that doesn't matter, but it does. There was a section 174 of the tax code, which was been around since the fifties, right? It had been around and then had been expanded upon, which basically said, if you have someone in an R&D role, if you have someone basically that is working to create new technologies to innovate in the technology space,

[00:38:32] they, you get a hundred percent of their salary. You get that back to your taxes, right? So when you're a business, basically you're more or less getting to hire someone for free, if you're using someone for that. And that fueled a big boom in tech people. Now in 2017, that was revised under the Trump administration where they said, no, we're going to take that away. It's slowly going farther and farther down. And we are now seeing the impact of that because basically the way they do,

[00:39:01] they stagger these cuts to these programs. So it doesn't all hit at once congressional budget office, US politics. If you're listening from outside the country, you're halfway asleep. If you're in the country, even all the way there, but listen, here's the point. Starting just around 2022 and into 2023, those started having an impact, right? If you're saying, okay, well, I'm only going to get 20 or 30 percent of their salaries back. That's going to cost me a ton on my tax bill. So I'm just going to get

[00:39:27] rid of them because basically it's become a liability and it's not worth the gain versus the loss. So what do we see from that mass layoffs and people going to other countries as a result? So pay attention, I guess, is what I'm saying when these bills are going through the taxes. It is. Yeah. And this was called out. I want to, I want to do a shout out to Frank Scavo, who is an independent analyst who we know from the enterprise space. And he was the one who kind of

[00:39:51] brought this to my, my attention. And, but I, but I also think it is, it, when you're starting to watch sort of how some of the decisions are being made, I think there's a, there's a real thing of like, oh, it's just AI that's causing this, right? There are other factors that play into that. Now, granted, just because you don't get a tax break, doesn't mean you're not going to do research and development, right? Like that's a, that's, that's, you know, you got to still do research and development. Any good company does research and development. Even we do research and development,

[00:40:19] put aside some measure of our work for that. What it just means is that it's not as lucrative and it means it makes more sense to me to do some of that research and development offshore versus here in the United States from a tax perspective for the, the salaries and the people and the work that you would be doing. And that I think, and again, not a tax person. So, so check all that with your person, but I think it does get down to this conversation about where is the innovation, where are we driving the innovation being done versus where are we driving the work or the,

[00:40:49] or, or the piecing of things together or those kinds of stuff. I'm, you know, there's a lot of that dynamic that's changing right now. And that's the piece that I'm trying to watch because it's showing up in our data. We're definitely seeing this sort of drive for, for the, the revenue at all costs, performance at all costs and reducing costs at all costs, right? Like those things of

[00:41:13] growth and, and reductions in, in, in spending are coming down to higher levels of, of per revenue, per employee expectations across every company that we're talking to and real questions about how you're doing workforce planning in a way that looks more globally versus maybe more, more individual, more individual country-wise, which you think is different than some of the intended outcomes of some of the decisions that we've made here. Right. So, so we'll see how this plays out.

[00:41:40] Yeah, that, that's a good point. It's the sort of intent versus the reality, right? And so we got a, another sort of example of that. This is from Cloudflare. Cloudflare is basically, we talk about infrastructure. There's your internet right there. Cloudflare controls almost all of the internet traffic. 20% is the number that was given, but start thinking about how much that really is and how much everything's touched. If you remember, I think it was two years ago, there was the cloud

[00:42:09] strike incident, not related, but is sort of related in that they're not the same company, but that did all of the sort of checks, the security checks for information passing through Cloudflare servers and that sort of thing. And you remember when that went down and basically just crippled the U S for a day until that got sorted out. So how important are they? Very important. And while these sort of regulations are going through, what you end up seeing is regulations sort of

[00:42:33] by default through a, for a totally different reason. Basically Cloudflare used to say, okay, the AI bots control, they can scrape through the internet and go through all these different sites, go ahead. Now they're restricting their use. And in fact, it's set on by default to restrict their use. They're going to now do a paper crawl program. Crawling is what they call it when the AI bots are going through and finding the info so that they can charge, you know, off for that. So yeah,

[00:43:02] they're doing it not for, you know, we were worried about regulation, but for, you know, monetary reasons. But what does that do? It ends up creating a setting forth a regulation in effect that's more potent than anything that could be passed down by any governmental legislation. You know, if they said, Oh, I can't do this. And it's like, well, they really can't do this. Well, and I, what really caught me on this one, and I said this for a while, right? When,

[00:43:29] when Google first hit the market, the big conversation was if they were, if when Google just pulled forward, any internet audience, what you were doing, that was great. Basically, that was like getting a storefront that, that someone was able to see. Right. But when Google started pulling information and not letting you go to the site, but so flights is a really good example of this. I'm going to pull all of my flights that takes out of the market, that aggregator,

[00:43:53] maybe kayak or, or Expedia, where you would have gone to get that aggregate view because it's scraped that information in its own way. And then now we have this happen with some of our big recruiting platforms, monster back in the day, that a lot of their traffic was hindered by these tools that were scraping and aggregating the data. Right. And so I think this, what this is doing is it is,

[00:44:18] it is, again, it early on saw what we saw through the early internet days that, Ooh, I can make some additional money by not allowing you to automatically scrape. And the company who is putting that website up on the cloud fair environment through, through the cloud fair tech, right? Has the right now to say, my data is valuable. I'm not going to let you scrape it. Even if you pay, there's that thing that's

[00:44:44] going on there too. Right. So this then gets down to how valuable is my data. We have this conversation all the time about what you put out there for free versus what we put behind the firewall. Not all the time, because we don't want people who might look at it and see it to have access, but because we don't want these technologies to scrape it and use it inappropriately, which is very different dialogue. So, cause we've changed the dynamics about why people would put anything out for free. That was the whole process of the internet. Now there's something else that's going on behind this that I think

[00:45:11] everyone should be watching for, which is what we're calling subnet environments. So subnet environments oftentimes modeled around the blockchain conversation and this idea of blockchain, which for a long time has been kind of pushed off to the side. Well, it's coming back because the idea now through those subnet environments, I just had a conversation with someone about this yesterday, who's starting up kind of a, it's not crypto, but it's on the same blockchain and technology model that

[00:45:39] we saw crypto modeled after they're starting networks where you can actually start to see the value of the data that someone wants and basically charging per data set instead of letting them just come and take it because, and it's cleaner data because it's on a subnet. It's not the wide internet. And the idea around that is that you are also rethinking this model of the value of the question that you're asking

[00:46:05] through an AI data grab, right? So that the AI is more tailored to the data that you're getting and you're not out there because the biggest issue we've got with current AI environment is it sees everything and it takes everything into consideration, even when you tell it not to, which is why we get a lot of the hallucinations because it's trying desperately to answer your question with all the information that it's been taught over time. So how you train your AI becomes a really critical

[00:46:32] and what data set you're training it on. And you want to manage that. And you also want to see the energy cost of that because us running a thank you to chat GPT is a massive energy pool where us running on a subset is a much less energy pool. And we might want to be able to look at it that way, a little more green approach doing AI. All of those are things that play into this conversation. And every technical business leader has to have some understanding of where this sits, no matter where you are

[00:47:02] at, you have to understand how it plays out in your website. You have to understand how it plays out if you're a vendor doing technology, how it plays out and how you're going to be able to access AI and what AI can do for you. And you have to understand where you might want to invest your own finances if you're investing in these kinds of technologies. Because if a door closes, does that value proposition of that software, which is all about being able to scrape, become less valuable? So big questions,

[00:47:28] right? Yeah. And you're going to need to be able to explain that to others in a way that makes sense, possibly using storytelling and visualization. That's how I wrap it up. Bring it back to the top. But we also mentioned we are going to be, we're sort of scaling down, but that doesn't mean the whole company's going to be doing some travel, right? Coming up before HR tech? Yeah. So before HR tech, Susan, our founder will be up in New York actually next week, doing a walkthrough with an organization,

[00:47:58] an HRMS organization, which we haven't been given approval to say their name yet. So, but once we are, I'm sure we'll get some updates around that. So if you're in New York next week and want to touch base with Susan Richards, she's our founder, she'll be up there. I'll be an ADP at the innovation summit, September 3rd in New York city, lots of New York coming up. And then Cliff, we're going to be at the HR tech conference in Las Vegas, September 15th through the 18th. Make sure you get the day right. Right. Our, we've got several sessions. We're going to be at the, both myself and, and Terry

[00:48:27] zipper. We'll have our session at the women in HR tech on Tuesday. We're going to have our company friends and family dinner on Monday night, right? So that's, that's the Monday, my session on the annual HR system survey that you'll be supporting. And then you'll be doing the ask the expert with me on, we'll be on Thursday morning at eight. Thursday. Yes. So stick around, make sure you check your travel dates. You want to be there, you know, obviously leaving later on Thursday afternoon,

[00:48:55] that's when we'll be doing our big debut. And like I said, I know it's early, but do try to get there even earlier in that. I always am so sad when people are like standing outside the door, you know, for this event one day, they'll give us the full giant ballroom, but yeah, you and I will, we're not sure who will be going, but someone will be at the day force discovery, October 7th and 8th. You're going to be at the Oracle cloud world, correct? That's also in Las

[00:49:22] Vegas as well. That's right. By then it'll have cooled off. When I was in there a few weeks ago, it was 104. This will be much nicer temperature and I'll get an update on everything that's going on. It's sort of driving those great fiscal results that we've been talking about. And then we'll both be at the UKG Aspire event in Las Vegas. So we're very excited about that the week of November 14th. And then I'll also be doing the, the I solved connect regional event

[00:49:48] in November in Philadelphia and Scottsdale. One last item to know about. So if you are interested and if you're, if you're following us at all, a press release will come out next week about our relationship with the chief financial officer's council and the finance and technology expo, the national finance and technology expo in New York in the 14th and 15th of November. We are running special round tables for that. So if you're interested in participating in those,

[00:50:18] let us know. I think we've got a couple of announcements going out about that. That's going to be New York at the Javits Center. There's going to be 3000 or so finance officers there. So we're really excited about it. That is cool. Yeah. So, you know, the only other thing I'd like to say is that we are going to be putting all this list on our website. I think you go to news and views and we should have this obviously listening to the show probably the best way

[00:50:45] because we're, we're updating it, but you can also go there if you're trying to remember and not trying to fast forward through this. We'll have that up as well. And we were given some feedback to put our events in. So we do listen to you guys. We do understand there's a lot that we're covering. So we, we've wrapped them up at the end cliff, because we're wrapping up and we've got to get going as we wrap up today, a couple of other big pushes, although the survey is done and wrapped. You can't, we will start to have some specials. If you want to, if you did not get a chance to participate and didn't get a chance to do that

[00:51:13] starting next week, we'll have our by last year's get next year's special. So just be aware of that because I know people are always trying to get access to that data if they can early. So that's a good way to get some of the stuff as quickly as it's available. We are also, as Cliff said, if you want to know more about where we're going to be at, what we're doing and where, and what's going on, please sign up for our newsletter at our website that will give you access to where we'll be at and all the fun things that we'll be doing. Be sure to listen

[00:51:39] to our sister HR header podcast as well. HR, we have a problem hosted by our CEO, Terry zipper. And if you like, and appreciate these events and like to hear us talk more about the, what we're doing here on the podcast, please subscribe and leave a rating and review at our new work defined home to stay up to date with the immediate breaking HR tech news and get all behind the scenes content. You can follow us at sapien insights on LinkedIn and Instagram. And thanks again, Cliff, for always pulling this together at the last minute. I know there's, there's all, I send him stuff like an

[00:52:08] hour before sometimes I start eating off things. So he does a great job keeping up with it all. Also thanks to a brand method media group, Kelly Kelly. She does an amazing job getting this out to our marketing team, Summer Alano, Cole Harris, as well as the rest of the team who supports all of that hard work. Thanks to our listeners and community. We couldn't do this without you. And guys, I hope you all have an enjoyable couple of weeks here in the summer where maybe you get a little bit of downtime, but that's it for this episode of Spill in the T on HR tech. We hope it's been just

[00:52:35] the brew you needed to start the engines running this week. We'll be back in two more weeks with another pot of boiling hot HR tech updates and insight. Thanks everyone. Bye.