Ali Nawab: The obvious thing is that every company is an AI company. I think some of the other things that are gonna be less obvious are that a lot of companies are trying to be the one stop solution for all of your HR needs. And at least in my conversations with people, they're getting fairly confused about what that means, because nobody's like fully satisfied with what they have. So there's clearly gaps.
But if you look at the range of companies presenting every company's doing analytics, every company is doing HR Payroll, compliance, employee benefits, and I think we will see a clear separation of companies that are very focused on a specific area. And then there, you know, the general platform, SAP, Oracle, Workday type products, the companies that are, neither here nor there, and they're somewhat struggling to articulate their positioning.
And so what is Agentnoon, bringing to the table?
Ali Nawab: Agentnoon is a highly focused product that helps leadership teams make better decisions with their data at the fastest possible rates. So while everybody is selling a point solution to a specific problem, that is typically downstream of the HR leader, we are selling a very focused solution with very fast speed and ease of use, that is focused on the leadership suite, which the HR person is a critical member of.
But it's also the finance leader, the ops people, the CEO, that's where we're focused.
And I know that on the episode that I interviewed you and this is really about how Agentnoon brings together the language between the finance and HR functions, where you're marrying quantitative data with organizational design, and even perhaps other specific strategies that the Chief People Officer is looking to implement.
Ali Nawab: 100% So the promise of technology is that it's going to help us make better and faster decisions. I think a lot of products and companies are still focused on the automation, we'll just kind of have these things go very, very quickly. But I think if we make bad decisions, having them compound at a fast rate is probably not a good idea.
And I think from our perspective, because we meet everybody where they are we're like a translator in between. It builds a lot of alignment because we're not going to get a finance person to get out of their spreadsheet.
We're also not going to get an organizational design person to look out of their org chart. But they all need to work together in unison to be able to deliver outcomes. And that's where we want to speed things up.
And so what does the future hold for Agentnoon?
Ali Nawab (05:14): Great question, I think that we're seeing a lot of changes in the environment, I think those changes will continue to amplify and continue to be more frequent. From our perspective, we want to be the command center for leadership teams to make decisions around their number one, and effectively most expensive asset, which is people we want them to build to make great decisions about who they have, who they need, where to deploy people, there's a lot of conversation about skills based deployment. I think we're going to start to see separation around problem statements.
And I don't see a single CEO, no matter what product they're using, who's saying I get all the results I want, super fast. And then I can do a bunch of what if scenarios on those results to get where I want to go and be able to adjust my strategy in real time.
That's where I think we're going to shine or we're going to really separate ourselves. But I think that is a bit of a long journey. I'm excited to be part of it obviously.
If there was one thing I was eager to explore during the conference, it was the potential of AI to enhance productivity. That's when I discovered Beamible, a company led by a dynamic Australian female co-founding duo, X Google employee, Victoria Stuart, and Stephanie Reuss, who has spent 10 years at CEB.
Stephanie Reuss (06:32): Victoria and I started Beamible, because we could see that the current systems for organizing and distributing work were very broken, causing friction points for employees with burnout, and high workloads and high stress and friction points for organizations who are struggling to optimize their performance.
So we built Beamible, our work design platform that would help organizations get a view of their current state, a diagnosis of what their current work design is, and what the gaps and opportunities are. Provide them with some analysis to show them those hotspots, and then help them to improve their work design, through a really easy to use interface where they could optimize for the work that people love to do, and the work that their organization needs to get done.
And as I understand it, you are collecting data around employee activities. And so how do you collect this data? Where does it come from?
Victoria Stuart (07:38): Great question. So we essentially populate activities with using AI.
So that's a really great starting point for organizations. In addition to that, we allow organizations to pulse their people to understand are those activities actually the work that they're doing? Because often we have a disparity between what a job description says and what activities people are actually doing in their work.
We also invite them to add hours to their activities to recognize how much time they're spending against them. And then there's a series of questions that helps categorize the work so Steph mentioned before around what work is really energizing what they love. So they have an opportunity to select which activities that they really enjoy doing, we might ask them what work is aligned to the organizational goals.
And this is all customizable, but it really allows for organizations to understand the nature of the work that people are doing, and invite a bottom up response from their workforce as well.
Felicia Shakiba: And what I think is really interesting of what you guys are doing is that you're able to, from a very high level, if you're an executive beam down into someone's work, and really understand where they're putting their time, which I think is incredible, because from a high levels perspective, it's very hard to do that you really have to go to the manager of a specific team to really understand and even they may not fully understand what their team is doing.
So that is what I see that's incredible today with your product, what's the roadmap look like for you?
Victoria Stuart: We're really excited about what we have planned. We've been focusing on work within organizations, we're also going to flip that view to help organizations represent the skills as well and be able to see the gap not only between what the role needs but also what the individual has and isn't necessarily being tapped into as well.
We also know that a lot more opportunities for organizations to automate a lot of the activity captures as well.
So we'll be doing a lot more in that space to make it simple for organizations to really get a quick view into what is actually happening without too much investment from their team right now it's a really easy lift. But we're going to make that much more automated to ensure that it's a really accurate reflection of what organizations doing, using the systems that they currently have.
And so with all of this data and where you guys are going, how does that reflect the value the return on investment for the business?
Stephanie Reuss: One of the biggest ROI that we hear from our clients is the wasted effort that they're able to identify through Beamible.
And one of the quickest wins, for example, is simply just the misalignment in expectations from leaders, and what employees think is the most important work that they should be doing. So simply getting alignment is the quickest win in productivity.
But in addition to that, we see other efficiency or simplification opportunities identified such as process simplification, we see work duplication between people that can be eliminated, we see much more efficient ways of working innovated, because they've seen how much it costs and how much time it takes around things like internal meetings, cascading communications, and so on.
So we typically see organizations finding between 13 and 21%, productivity gains simply as a result of getting visibility into their workforce and making some changes.
Felicia Shakiba: One of the most coveted applicants tracking systems, commonly referred to as an ATS is Greenhouse. I was already aware of the quality of their product. However, it wasn't until I listened to the story of its inception that I gained a profound understanding of its significance.
John Stross, the visionary founder of Greenhouse.io, generously shared his remarkable journey with me.
Jon Stross: For me, like my previous job, you wouldn't have guessed, I would start a recruiting software company. I was Head of International General Business, a company called Baby Center is a website for new and expecting parents. And we were launching in 20 countries around the world.
So I was traveling the world building a baby website. And what we figured out was that the key thing for success wasn't about the content or the technology, it was just about the editor. If we could find the right local editor who could adapt the content, it would work.
And so we had to build this system to say, how do we hire a pregnancy editor in China, and India and Brazil and Russia in all these different countries? I don't know pregnancy editors in these countries.
And so we had to build a whole system for how would we find people. How do we interview them? How do we test their skills, their local language, and then eventually hired and onboarded them?
And it worked. We hired dozens and dozens of people, we built these wonderful websites to this day, years and years later, is still a very successful website, helping tons of people.
And so the learning from that was that if you can quickly predictably bring on the very best talent, you can solve most business problems. That's a huge weapon.
And so when I was working with my old friend, Dan, as a developer, who actually developed a lot of the same theories from his company he'd been doing. And we realized that when we talked to friends who were running companies, they would all say hiring is one of our biggest challenges and we'd say, so what are you doing about that?
And then they would say gibberish, and we're like, No, this is really important. You need to do the things that I did a baby son, or Dan did at Lab49, and we realized, oh, there's this huge amount of value to be created.
And helping companies become great at hiring. And so the founding question of the company was, if a company decided to commit itself to be great at hiring, what software would it need? What technology would help them? And so we didn't start from the perspective of Hey, mate, yes, I want to build better ATS.
We started from the perspective of as a CEO, well, what I want to help me become great? And so that was the genesis of the company.
It's an incredible story. What's on the horizon for Greenhouse?
Jon Stross: So the future well, you know, starts with our mission, our mission is to help everyone become great at hiring. And so there's a couple pieces of that. One is everyone. So that means there's lots of different types of companies that we don't serve today.
So there's a part of this geographically, we're now spreading out all over the world and we are building offices in Europe. And so there's a big geographic expansion that's happening. There's different types of companies. So historically, we sold to a lot of fast-growing tech companies in Silicon Valley now we've expanded to many different types of companies beyond that - many different types of hiring beyond.
And then the other big piece of it, we said become great at hiring is that not all hiring problems, or ATS problems like the bigger than that. And so what we're finding is that there's a lot of really critical hiring problems that are bigger than what you would do in your typical ATS.
And so a lot of our sourcing problems, how do I figure out what job ads to buy? How do I figure out what agencies to use? How do I figure out which sources to choose? There's DE&I problems of like, how do I become fairer who do I mitigate bias? Right? There's downstream problem.
How do I learn? Did the hires actually work out, and are we having great quality of hire? And so all of those are just me more problems within hiring that we think fits under the tent of our mission. And so that's kind of what guides us and what we'll keep doing.
And does AI play a role in the platform today, or in the future?
Jon Stross (15:11): Of course, yeah. So I think machine learning is something we've been working with for a while. And I think now what we're seeing is that things that seemed impossible, like four years ago that were like, oh, it'd be really hard to build have suddenly become like, really doable.
And so for us, it's less about saying, How can we use AI and it's more saying, Well, what problems can we solve that AI - that we couldn't before, right.
And so I think that there's a bunch of obvious use cases, right, the things like put an LLM inside of every textbox. So you can imagine writing job descriptions or writing interview questions. It's very helpful with that, that's great. Like, obviously, everyone's working on stuff like that.
There's also other use cases, they're a little bit less obvious things like it does really good categorization. So we're able to feed in all these different jobs from our customers and say, like, hey, actually, it turns out this job you're opening based on the job description, and the title, we think it's just like these other 1000 jobs at these other companies. And we'd have the underlying model, which we can say which jobs are similar to each other, which allows us to create really interesting benchmarks.
So it'll look like ChatGPT, but it'll actually give you some really profound insights from this corpus of data that we have. So automation things we can do, right where you, you can get to the end of the process and say, Oh, given this job description, and this person's resume and all the interview feedback we collected against them, here's a two paragraph summary of why we're going to make this hire. And then you send that around and you're off for approval.
You know, there's lots you can do. I think that also say there's another category of AI stuff around, can you use AI to decide who to hire and make decisions between person and person B, that I think a lot of people have a lot of nervousness about, as do we. \And so I think that's an area where we research but I don't know that we're ready to put a stake in the ground and say we're doing that quite yet.
And so I think that's an area where we research but I don't know that we're ready to put a stake in the ground and say we're doing that quite yet.
One product that I was unfamiliar with before the conference was Veritone. The parent company of PandoLogic Veritone, was founded by CEO Ryan Steelberg, a notable figure in the field of ad tech. Ryan did something interesting. He seamlessly transferred his extensive expertise in programmatic ad tech strategies to a realm of job advertising, and now is accelerating Veritone's footprint into the HR tech arena at lightning speed.
Ryan Steelberg: I decided to start Veritone from a background in advertising tech, being one of the first entrepreneurs to start the digital ad technology business back in 1994. We became very good at building technologies and businesses that were very effective serving the right ad to the right person at the right time and have built several businesses sold a previous business to Google where I worked there for several years heading up a lot of their advertising efforts.
But the key was everything that we historically have been working on was serving more or less display or a call interruptive based advertising. So whether as a pre roll, or search result ad, or an interstitial video or commercial, like we say, like the call them. But when the mobile phone kind of took over and started dominating the advertising landscape, more so than legacy desktop, we needed to evaluate other forms of advertising a category, which some people are familiar with, we've all had exposure to it.
But product placement or native based advertising, this is when you see the Apple logo appear in a movie or when a sports broadcaster during the game does a live read and talks about State Farm or Geico.
These embedded forms of advertising, which can be very, very effective in terms of consumer engagement are very challenging to track and identify. So it's kind of like how do I bring insight or data structure around a logo that's embedded in a movie, for example. So Veritone, which the name comes from the root, very truth and tone signal is truth in the signal. So we set out to build technologies leveraging AI, and this goes back to about 2012. Could we start to analyze content and audio video assets at high volume and scale, and be able to organically and programmatically identify when these organic product placements and ad mentions are happening inside the content?
We started the business specifically focused on those use cases and those problem sets and the business kind of took off, then it kind of expanded from there where we had government agencies reach out to us, you know, could we start to apply this AI based technology to helping the Department of Justice and the DoD analyze audio and video, whether it's satellite imagery, or body camera and dash-cam video leading up ultimately to the HR opportunity.
Frankly, it's such a large industry, the investment into human labor mean if you look at just from a corporate expense, on average 75% or more of a typical company's corporate expense goes into compensation.
Could we start to bring a lot of our expertise and technologies to bear to frankly help automate and bring a lot more efficiency and scale to the talent acquisition and recruiting marketplace.
And so that's ultimately what we did. We didn't start from ground zero on this one, we already have, obviously, the AI and technology stack, which we own at Veritone. But we initially made an acquisition of one of the market leaders in programmatic job-based advertising and that company was called PandoLogic. And we acquired them about two years ago. And then just about 100 days ago, we acquired Broadbean, who really have a dominant position in manual job posting and distribution.
So we're accelerating our entry into this ecosystem through a couple of acquisitions. But now you can kind of understand how we're going to be infusing our expertise of program automation and AI into the space to really bring major material change.
In high volume hiring scenarios, the primary objective is to expedite the recruitment process, while maintaining efficiency.
Felicia Shakiba: Many organizations such as restaurants, retail stores, and those with seasonal staffing demands frequently onboard numerous individuals annually. How can this process be streamlined effectively, to handle the high volume of recruits? Insights from experts like Hope Weatherford, the Head of People at Fountain could offer valuable guidance in this context.
Hope, what is Fountain?
Hope Weatherford (21:26): Fountain enables high volume hiring, allowing organizations to reduce their time to hire from months to days and in some case, even hours. Organizations like Sweet Green, Bojangles, healthcare companies has seen tremendous success using Fountain. With automation and AI, both teams and candidates have a great experience. Also ensuring that you're able to fill your roles with the right employees and meet your staffing goals.
And can you tell me, what kind of candidate is an ideal type of candidate? Or what type of business can hire this many, this fast? What is Fountain great for?
Hope Weatherford: Thank you. Fantastic question. So we really focus on frontline workers, hourly workers, they could fit in a number of different industries, from retail to food service, to hotels to any type of hospitality, we're also manufacturing.
We work with a lot of gig companies as well. So super excited about the types of people that we're able to bring in the types of candidates that we typically work with are candidates that are in that frontline worker perspective, they may be teenagers that are going for their first or second or third job to help them get through school.
And then it could also be people that you know, really just enjoy that type of work.
So the types of candidates that we look for typically aren't ones that are going to have a big, long, large resumes or even a resume.
And so our tool allows our candidates to apply without a resume, which makes it a very frictionless process for them, which is great.
What does the product offer customers in the near future?
Hope Weatherford (23:04): What we've got going on in the future is really exciting. We really have been focusing on making sure we get the right candidates through a hiring pipeline in in your, you know, starting on their first day very quickly.
What we're going to be focusing on the future in the next few months, is really making sure that once they're in, we have the opportunity to help them grow and stay engaged, and really manage and help with that employee lifecycle from the time that not only from stopping when they're hired, but all the way through their lifecycle until off-boarding, and then potentially rehiring as well.
That's so exciting. And I want to take a step back and really understand what does the candidate experience really look like from using Fountain? What is their experience from start to end? Where do they end up? Because I know that you also have a feature where candidates can book their video interview very quickly, and it's easy to apply. So talk to me just a little bit about that.
Hope Weatherford: Yes. So again, a very frictionless interview candidate experience. So candidate finds a role a lot of times they are going on Indeed, and Indeed is a very good place for people in the US to apply for hourly work or frontline worker type roles. Typically, somebody applies for about 28 to 35 roles in one sitting.
So speed is really the name of the game. As soon as you can get back to that candidate that is typically the company that's going to end up hiring that candidate. So we make it very easy- is a very short process. You can do it on any device. You don't have to have a laptop, you don't have to have even a sign on.
So that makes it a really easy process. Also, once you get through that piece, you'll answer a few questions. You'll understand if you're going to be a right fit for the role when you're available, things like that.
And then if you're chosen to move into the interview process, it is so easy.
Our tool connects in with calendars from the recruiters that candidate can pick when they are free. Again, all of this is done on their phone or on their tablet, super simple start to finish to somebody pick completing an application is likely less than five minutes. Once they have their interview, then they may move into the into the offer stage.
We do have some customers that move into the offer stage before they do a final interview to ensure that those candidates stay engaged.
On the cover of this month's Harvard Business Review, my eyes were drawn to the title, Reskilling in the Age of AI. Was it a mere coincidence, or perhaps fate when I reached for the magazine on my way to the conference. I was actively searching for companies that could offer precisely this kind of service. And to my surprise, I discovered not one but two. The first one is Skillable, a platform designed to foster an environment for honing hard skills like coding, and custom software usage. Chief Marketing Officers Sarah Danzel tells us more about the challenges this platform solves.
Sarah Danzl (26:11): When we think about scalable, scalable is a hands-on learning and skill development platform that focuses on applying skills. So if we zoom out a little bit from that, and how we think about skills are validated today.
You know, the room at HR Technology was full of all these incredible technology and tools, some even legacy that handle really important parts of the skill ecosystem. And yet, we still hear things like we're experiencing skills shortages.
And our people still report that they don't have the mastery needed.
And it is because all of these incredible skills only give a portion of what a person is capable of - the only true way to understand what someone is capable of and if they are job ready is through validation of performance of behavior. And that's what Skillable is trying to tackle is this ability to apply and validate skills through performance.
And as I take a demo of the tool today, I see that there are opportunities that are something that you call a lab, can you talk to me about what a lab is?
Sarah Danzl: A lab is a virtual environment, a virtual scenario-based environment to apply these skills to work through these challenges.
The brilliant thing I think about our virtual labs in our hands on skill challenges is that when we think about what has shaped the last 20 years, and learning, it was this room, it was the explosion of all of the content and the lab providers. What I believe the future will be is high touch at scale, some organizations have had to lose that personalization to scale.
And sometimes that happens when you think about learning, right? It can be a little bit generic, it's not as personalized, because we had to hit a lot of people quickly to scale up as learning and skills grow.
But labs are the opposite labs take a high touch, scalable approach to this hands-on learning. So inside a lab environment, you go through a real life scenario that you would experience on the job. And at the end of the lab, they are automatically scored. So you get a score that says this is where you're good. This is where you're weak.
This is what we think you need to improve on from a skill perspective so that you get real time evidence and skill signals on what you're capable of.
And the individual taking the lab can actually work in this practice environment. And Skillable will actually tell the individual if they got those answers right or wrong or give them feedback?
Sarah Danzl (28:47): Correct. So when you think about the way we think of assessments right now, there's probably a lot of guessing I can admit to it myself, there's probably a lot of guessing involved.
Sometimes you just pick D all the way through, sometimes now thanks to things like AI, you can get your own answer in that way. But AI and the assessments are answers, they're not outcomes.
And so that's the difference in Skillable is that we are looking at the actual behavior needed to perform the job, the task, whatever it might be. And then you get the feedback from that and you as the individual understand where you're good.
It's also a great signal for leadership and for managers where they can help guide the process along as that coach and as that mentor for areas that might need to be worked upon, or even areas that are great to give them that feedback that this person is really succeeding.
And where I see a lot of productivity increase for a company using Skillable is that sometimes when people are learning a new skill, they walk over to their peers or their manager and they take time away from their colleagues to learn something new, whereas Skillable is actually a scalable behavioral solution that allows someone to practice hands on learning and get immediate feedback on how they're doing without having to disrupt the work of others.
Sarah Danzl: Agree. So I think peer to peer is a very important aspect of learning the same as content, the same as you know curators and designers, they are all doing still very important work of today.
What we just tend to believe is that that's still not enough information to know about how a person is doing. Skills today are very much inferred, or they're being told from an outdated skill system and a lot of places. So that might be for example, if you're using your resume, or if, for me, that's been 20 years. And on LinkedIn, I don't update it that much.
And if you think about you upload your resume when you apply for a job into the applicant tracking system, and perhaps that's what data is being pulled to see if you're ready for another job that you don't even know you're being considered for.
So at Skillable, we like to consider a lot of use cases we'd like to consider, of course, exactly as you're saying that ability to apply the skill, and then get the validation to know you have it but also pre and post assessment. Also talent mobility, are you looking for a new job? And are you confident in the skills that you have or not so that you know, if you're prepared or ready?
There tends to be the kind of entire employee ecosystem, if you will, holistic view of skill building through Skillable, we really want everyone to be able to apply those skills to build confidence in this way, so that they can go into that next job or the one that they're in now or prove that they have skill mastery in the role that they're in or the future one. That's what we're after. We're really wanting to help people apply those skills in these real-world scenarios, so that they get the skill validation they need.
While validating hard skills remains crucial as one ascends the organizational hierarchy, the significance of soft skills becomes even more pronounced. Nag Chandrashekar, Chief Product and Platform Officer at Degreed not only offers a solution for verifying soft skills, but also possesses additional insights and strategies to facilitate continuous learning and development, particularly from a managerial standpoint.
Nag Chandrashekar: Degreed is a skills first learning platform, it's a modern learning platform and it started off by being learner first, as the name indicates. So it's all about putting the learner in charge of their learning, development and upskilling shifts.
Basically, a number of our organizations, our customers come to looking to us because they are getting content now from various sources. In the last 10 years, there's been amazing number of content sources, right.
They're all hosted independently, they catered for different types of content, from hard skills to soft skills to basically everything from simple courses to full blown programs and categories. So in a sense, they are drowning in an ocean of content.
And that confusion also translates to learners within an organization. So Degreed comes in to say we've provided a curation layer, in addition to the content aggregation that essentially allows the company subject matter experts to provide a layer of curation.
And that in turn allows the learners to choose what are the things that they would like to do to take better charge of their career?
It could be because they want to apply for a different position, it could be they want to apply for a promotion, it could be because they want to start a new initiative, or an opportunity that's happened.
And talk to me about skills signals, what is that?
Nag Chandrashekar (33:39): Skill signals is a very interesting and a nuanced concept to handle the variety and quality of things that determine a skill, right? So at its very basic, people almost tend to distill skills into a label, a description, and then essentially said, this is what you need to have, maybe for your role, or maybe for what you would like to do, right.
But one of the things that we noticed was, for example, let's pick a skill that we're talking about, let's say product strategy, right?
We think to having a proficiency in the skill, or understanding how much you know about the skill or how much you acquire about the skill comprises of getting signals from different sources.
It could be a straight up rating, right? It could be rating that you've done yourself. It could be a manager rating, it could be a peer rating, but it could be the experiences to when taken, maybe you're spoken to a leader or a mentor about it, you've spoken to a coach, maybe you've basically connected and worked on a project in this area. Right. So that's that. What about achievements?
Maybe you've taken some certification program outside, right? You maybe have participated in some workshops. So we believe that it's the skill signals is a combination of ratings, experiences, achievements and learnings that you had in together, those signals contribute to proficiency level proficiency score.
So it creates a nuanced, but a real-life approach to how you actually understand the skills that you might have.
And it helps people within the business understand how their peers might be verified in that skill or beginner or a master of that skill. And to be fair, soft skills are really hard to measure whether or not you have them or not - interesting that you have this concept in the product, because it solves for the ability to really understand whether or not someone has that skill and at what level we could have an educated guess about.
Nag Chandrashekar (35:36): That's exactly right. Essentially, it's the color behind the logo, right. And as you correctly said, it's extremely hard to basically have an objective view of it, especially for soft skills. And so these make that a little bit more real, and a little bit more understanding.
And what is your manager dashboard? Can you tell me more about that?
Nag Chandrashekar: Yeah, the manager dashboard is again, kind of the same. We call it a skill coach, essentially, its goal is to manage and support your team's growth, right?
So traditionally, manager dashboards and learning management systems tend to be more like very tactical, it's basically like, Oh, tell me how many completions you've done, make sure you've done all the compliance, right? Are you on track? That kind of stuff.
This is more about making sure you as a manager can support your team's skill growth, because you kind of know, what do they need. What does each person need for the role in your team? And so how do you ensure that you have you give them the right support for their skill development?
And in the process, you allow the person, the manager to contact the team members, and discuss their plans, discuss their skill needs and progress in a meaningful central way. So that's kind of what the dashboard provides. It really kind of has three kinds of main areas.
One is gives you a skills view, to say, what are all the skills across my team? What's the rating? What are the focus skills? How many of them are kind of you said, you've kind of chosen to put on your profile, right?
And then the other one is basically learning insights, what's the learning that's happening within a team? And that kind of gives a round number of how many completions, how many points, but it also gives a little sense of who's active, what are the skills they're looking to complete? And kind of where are they in the journey.
So that's that. And finally, the skill Insights is kind of a way to graphically show where everybody is on in that skill radar. And you can pick a few skills, right? So for example, you might want to say I have a few focus skills I'd like to kind of help the company grow. One of them could be communication, kind of them could be leadership, one of them could be empathy, so you can kind of track the progress of the skills in a team-based view.
Felicia Shakiba: That's a wrap for part one of our HR Tech Conference journey. Stay tuned for part two next week. If you're navigating the complex world of HR technology and need guidance, visit CPOPLAYBOOK.com. for a free consultation. In part two, we'll explore AI's impact on giants like Workday, and IBM and introduce new HR Information Systems (HRIS) making waves in the market. See you next week.
