AI-powered algorithms are a powerful tool for analyzing large volumes of workforce data and making precise predictions and recommendations for optimizing workforce management. Far beyond simple automation, AI helps leaders make wiser and more informed decisions.
Tune in to this panel to hear business leaders discuss the latest technologies and strategies for leveraging real-time analytics and data-driven decision-making in talent management.
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Note: This content originally appeared during AI Decision Maker Summit: Revolutionizing Business Strategy with AI on June 6, 2024.
Speakers discussed leveraging AI to enhance workforce optimization, focusing on matching employee skills with organizational needs, optimizing workforce initiatives, and addressing privacy and security concerns. They emphasized the importance of setting the right direction, implementing AI, and addressing data privacy and ethical concerns. The conversation highlighted the potential of AI to improve workforce management, but also raised concerns about the challenges of implementing AI and ensuring transparency and empowerment for employees.
Vicki Lynn Brunskill 0:09
Hello and welcome back to the Argyle AI Decision Makers Summit revolutionizing business strategy with AI. My name is Vicki Lynn Brunskill. It’s great having everyone join us today. A couple of notes before we meet our esteemed panelists for this session. Just a quick reminder to stop by our sponsors virtual booths at any time during today’s event, and for the following week. Our partners are committed to providing you with valuable content and a great overall experience today. At any time during the event, you can visit their virtual booths from the main agenda page, and those do include complimentary materials, information, and meet and greet opportunities. To ask questions throughout this session and all sessions, simply type into the Q&A chat, and we will address your questions at the end of the session. And now, without further delay, I’d love to dive into this wonderful conversation. We are so excited to have our panelists for a panel discussion titled Talent on Tap AI for Workplace Optimization, a very popular and important topic today. I’m going to start out with let’s start with some brief introductions. I’m gonna go with Tiffany first Tiffany Please introduce yourself.
Tiffany Ingram 1:16
Well, hello everyone. I am Tiffany Ingram, the global human resource director of continuous improvement at Wahl Clipper Corporation. I’m also the CEO of Let’s Link Business Solutions. It is a service-based business dedicated to enabling businesses to identify and create synergies between AI and human resources. Again, I am thrilled to be here. I’m speaking with this esteemed panel, and just sharing my insight on how AI is truly revolutionizing the workplace, our workforce optimization and discussing the significance that we’ve all seen in talent management and beyond. So thank you.
Vicki Lynn Brunskill 1:56
Thanks for being here. Tiffany. We’re glad you’re with us. How about you jump in? Who would you like to do a brief intro to?
Jabin Geevarghese George 2:02
Oh, thank you. Thank you, Vicki. Good afternoon, everyone. Excited to be part of this panel. I’m Jabin Geevarghese George. I work for TCS Tata Consultancy Services. I work as a global FinTech transformation leader. What we do is that provides service delivery and transformation for our major financial capital markets clients, and particularly you. I do have more than a decade of experience working with retail financial services clients and we are working on AI solutions FinTech and implementing in agile ways. So I’m really glad to be a part of this panel with Tiffany and Andrea and also to execute your agile for and what we have today. And definitely it’s the need of the hour to talk about AI for workforce optimization, because definitely it is going to play a vital role personally and professionally in our lives. So more discussion, looking forward to talking to everyone. Thank you.
Vicki Lynn Brunskill 2:53
Thank you. Thank you so much, Ben. And Andrea, a brief intro. Yeah, great.
Andrea Shiah 2:59
Hi, everyone. My name is Andrea Shiah. I’m the head of talent strategy and transformation at Eightfold. I joined Eightfold, which is an AI talent platform, about three years ago. Prior to that I had a 25 year career at American Express, where I worked mostly in the business but I was tapped on the shoulder to join HR and lead a lot of transformation HR. While there, I implemented a fold and a lot of other transformations were low wild by what I saw and saw that AI was a big deal for HR. So I decided to join HR Eightfold and now spend my time talking to talent leaders about AI and how it makes a difference in their talent priorities. Excited to be here today.
Vicki Lynn Brunskill 3:44
Thank you so much, Andrea, for joining us. And I want to go into some of those experiences that you’ve had. I’ll start with you on the first topic that we’re going to talk about today, which is what are the top ways you’ve seen AI improve workforce optimization? You said you’ve seen a few? Yeah.
Andrea Shiah 4:02
So I thought maybe it would be helpful for the audiences, maybe for me to share a little bit about AI and, and what exactly it means, you know, when you talk about talent, because the impact is so large. So, starting with a quick one-on-one about this, you know, what AI brings or what April brings to our customers is we have a huge depth of knowledge about skills and skills that exist in different roles that people hold. And so what we’re able to help our customers do is understand the skills that their employees have, and also the skills that candidates have. Right. So that’s one very important outcome of having AI. We also help you define, like, what are the critical skills you need when you’re looking to drive business results for all your different roles that you have in your organization? So when you can match the kind of your critical skill needs with the skills that your employees and your candidates have in unlocking everything like All of a sudden, you’re no longer limited by a job, and therefore that job can move to these jobs. Now, you’re actually looking at the talent in your organization that really unlocks everything for every stakeholder. So HR can all of a sudden answer the question, what skills do I have in the organization? Leaders can understand what skills do I need to drive business results? And then they can also understand across your workforce? How do I build those skills in my organization? Or do I need to go out and acquire those skills through talent acquisition? So some really powerful things that come about when you know the skills your employees and your candidates have, and you can match that with the skills that you need? So that’s a quick primer on kind of AI and how it really optimizes for your workforce.
Vicki Lynn Brunskill 5:43
Thank you, Andrea. And Tiffany, did you want to add to that, or I’ll kind of go one at a time so that there’s not too much overspeed?
Tiffany Ingram 5:52
Definitely. So I really enjoy what Andre said about, again, just how AI is playing a part in talent development. I’ve seen it personally in performance management. So again, when you’re looking at the skills that you have within an organization, and matching that up with the talent that you have, you also want to create a process by which you can give employees that immediate real time feedback, and also be able to provide development opportunities. So AI has, has shown up on the scene, as we say, and made a significant boost in these two areas. And again, I’ve seen that and how it correlates to employee performance and productivity. So again, if you’re able to give that employee immediate feedback and supply them with the opportunities to either upskill and rescale. It’s been phenomenally shown to increase productivity within organizations too, as well.
Vicki Lynn Brunskill 6:50
Wonderful, wonderful. And then to Ben, what do you think? What are the top ways you’ve seen AI improve workplace workforce optimization?
Jabin Geevarghese George 6:57
So going back to pretty much what Andrea and Tiffany have said, we are definitely seeing a big wave of AI in terms of the workforce or talent optimization. So what I see is that it is a multi tree view, for example, from an intra enterprise point of view, how we are looking at our employees and assessing internally, to elevate the experience, have a better collaboration within the tools to work to to foster productivity and all those things. But as an employee working for an enterprise, I will also be looking at what it means to me from an AI perspective. So for example, as an employee working for an enterprise, can I have personalized, tailored learning? Can I get a cube support, for example, how AI is playing a very beautiful, beautiful role as in HR bots, it is helping us cute little, like, as an employee, give us like, instantly answer the queries that we are looking for implementing Gen AI search, it can skim tons of data and just give me what you’re actually looking for, instead of going over multiple emails and tons of emails. That is a beautiful aspect. Second thing recently, like what Microsoft and we are, we are I mean, in the conference, what recently has been spoken off. It’s a it’s a multi level of agent deployment where all the enterprises Okay, so one is like how the how, as a co pilot, like, actually, like if he or someone sitting with me and helping me put my code, or helping me hire the right candidate, exactly what Andrea do, like have a skill match, basically what we’re looking for and increase our right to higher frequency, for example, all of these things are getting optimized just on your fingertips or just a magical AI being implemented in enterprises. And that’s where the tailored solutions like what eightfold AI or what Tiffany or we are doing, they’re trying to bring in for our customers of the services. So just to touch base, like I don’t want to take all the time, but it’s a lot of topics. But again, we have to touch upon how we implement the data governance part of it keeping security and ethical concerns in place by the enterprise. So
Vicki Lynn Brunskill 9:05
That is very good. Very good work, you know, building on that drive, I’d love to stay with you. What are the most significant ways you’ve seen organizations apply AI to innovate like employee engagement and other workforce initiatives?
Jabin Geevarghese George 9:21
Okay, so as of now, as in every enterprise we are trying to fix our enterprise within our intel internally like, are we ready for the general DVI or AI implementation? So first thing is that to have a strategic direction, set up the AI board within your council or AI committee within your enterprises. And what we have seen is that we can start with very low end initiatives, for example, low low to moderate risk kind of initiatives like having your service bots implemented, and answering a simple query where the key employees or the key or key associates can focus on strategic work, where they can focus more on the strat Add and rather than on the routine VA works. So what we have seen is that service agents or agent deployments look like agent bots, that is pretty much common across all different industries and small mediums, and that is what we’re doing for clients. And it is pretty much giving a lot of bandwidth or and reducing our call rates to the operation center also, for example, I am not I’m having a login issue, or I’m not able to log into a banking application, I do have a virtual assistant, I just give the details, it says that, okay, you might have to reboot, or you have to do this, this this, that makes our life easy. And from an employee perspective, we are able to focus more on the key important work. So that’s really one thing. Second thing is that how enterprises are using it is like integrating the products together. For example, I’m not, I’m not sure but all large scale enterprises what we are seeing, definitely they have Microsoft products in place. So what they do is that they try to integrate product strategy, bringing the products and platforms, bringing in office 365, copilot teams and SharePoint together. And how it helps me as a as a based on my persona, it brings in everything together for me and can summarize the notes for me summarize my meetings, summarize my records, having a personalized dashboard, that is what elevating the employee experience, that is what something we are trying to step up for our clients and and bringing that flavor. So that is how they are, I mean, there is definitely a lot of talk that needs to be done. And before we all do all these things, definitely data has to be there, the foundation, the foundation has to be there. And that’s where, like Andrea and Tiffany, we all see that AI can bring in a lot of optimization for us. But before that, we need to set the right direction. And we have to start implementing it. And from a talented workforce. Like I think Andrea can touch upon more about it. But HR integration would definitely be something really good, like the onboarding experience, how we can replay something or play a critical role with assistance. assist us. Yeah.
Vicki Lynn Brunskill 11:57
Thank you for adding something on employee engagement and other workforce initiatives? And how do you see companies innovate with AI? Yeah,
Andrea Shiah 12:06
Well, I think you know, it’s such an exciting time, from what I can see out there, I think what, like up to the CEO, there’s a realization that your workforce is your most important asset. Right, we just went through some really crazy times during COVID. And coming out of COVID, even crazier from the standpoint of talent. And so all of a sudden, all the way up to the CEO, they realize that the workforce is the most important asset they have, they have to keep an eye on. And so the great news is that HR has now got this great seat and really kind of being pushed to drive innovation. And so I’m seeing a lot of engagement. Now, in terms of employee engagement, how do you get employees engaged, how and a lot of what our customers are looking for? is enabling mobility, right? That’s what employees are interested in, I want to constantly develop, I want to make myself more valuable, you know, to the workforce in general. And so there’s a lot of effort around that. And when you think about AI, what’s really great about that is we introduce transparency. So if I’m an employee I can now look at or you know, roles across the entire organization? And what roles can I potentially move to? Where do I have a huge overlap of skills, and not only the typical pathway, like I could just potentially move up now I can look across the entire organization? What am I interested in? And what do I need to learn? Right? If I understand what skills required, what do I need to learn to be able to move that role successfully. So all of a sudden, that transparency empowers your employees to really drive their mobility, and movement, we’re seeing huge results because of that, right? Because employees are, the uptick in terms of internal hiring, and mobility is really high. And what I really love in that, too, is diversity, the increase in diversity for movements and even application for roles internally, we’re seeing gigantic increases, right? Because I think it just opens up the opportunity for them and gives them kind of the courage to apply when they’re seeing that they can match to these roles. And it’s really exciting to see those types of results.
Unknown Speaker 14:14
Tiffany, did you have anything to add there?
Tiffany Ingram 14:16
So I just really wanted to hone in just a little bit more on the sentiment analysis. So Andrew talked about the employee engagement piece. And you know, not waiting till once a year, when you have that engagement survey. It’s really AI tools are helping us analyze employee communications, and the feedback that we’re getting either through pulse surveys, the annual survey, of course, when you maybe conduct state interviews, maybe you when people unfortunately leave your organization, you’re conducting excellent interviews, so you’re able to identify the trends in morale. So again, if there are things or touch points that need your attention, you’re able to address them timely, and again, help reduce your turnover rates within your organization. So creating those natural touchpoints with your employees, so you can always check their pulse is one way that I’ve seen AI just, again, truly impact employee engagement.
Vicki Lynn Brunskill 15:18
Thank you, Tiffany. Thank you all for that. That was a very good answer for that one. So, I wanted Tiffany to let me move on a little bit, and change it up a little bit and talk more about the challenges. So what are some of the challenges you’re seeing related to applying AI in a workforce environment? And most importantly, how can everyone listening overcome those challenges?
Tiffany Ingram 15:39
Holy moly, where do I start? Of course, everyone’s concerned about privacy, privacy and security. Right, that’s at the forefront is my information, my employee data, my company data, is it protected? So again, protecting that sensitive employee data is crucial there, there are AI solutions out there programs or platforms out there that help you provide robust cybersecurity measures that, again, safeguard this information. Another one is, well, I think they’re run kind of hand in hand. But the change management piece, right, you have, you may have employees within your organization that are really resistant to taking on or even adapting AI because they’re thinking, what we’re all thinking, right, maybe in some shape, form or fashion that will one day replace us. So we have to be clear on the communication, provide comprehensive training for those training programs, and involve employees in the change process, take them on the journey, and invite them on the bus with you. And this can help ease the transition. Again, if you make them a member, allow them to be a part of the transition. And then lastly, biases in the AI algorithm. So understanding where that data is coming from is a significant concern. Because again, we don’t want to adopt a solution that has built in biases within it. So you want to ensure that you’re having those regular audits, you’re understanding where again, the origin of the information is coming from making sure their diverse data sets are in there. And the algorithm is inclusive by design, so that it ensures that there’s fairness and equity within the application.
Vicki Lynn Brunskill 17:27
All right, very good. Good points to Ben, did you want to add to that?
Jabin Geevarghese George 17:32
Oh, absolutely. Whatever Tiffany, like just using the same thing, the challenges definitely, it’s like a holy holy thing, like definitely a lot of things to be centered around the VIPs because definitely, it’s it’s going to be resistance from the employee side of it, but not only employee side, but there are data Foundation Data privacy and ethical concerns. Also, for example, we do have an AI system that we have just deployed in our environment, but how are we training our AI model, okay, is it going to be giving us a non biased output, irrespective of anything, so those things have to be given. So that’s where the AI governance piece comes in. And we need to really really, it could be something very stringent for every organization to put some focus over the AI governance but then only your all these things can play because it’s it’s directly involved with the reputation of the company, for example, if it is giving some and if a small security related concern or data leak happens, it damages the entire enterprises reputation, so there is something the person of the companies lost. So we have to be very careful in embracing technology. But definitely, it is not going to hurt us in any way. We have to beautifully love AI and how it can help us in our journey. And that’s where the human aspect is not going to be lost in any way. I’m not trying to divert from the topic. So what we can do is to help the enterprise’s and employees elevate their productivity using AI tools, but the critical thinking mindset, those kinds of culture, can we still be in the mean organization, so that we can be focused on what our customers want? And we can bring in that piece for our customers and deliver the right fit of products and services to the customer. Now, there is something I think Andy was touching upon about predictive analytics and Tiffany touched about the sentimental analysis. So as of now, we are also exploring how to like as a firm, how to like a lot of firms are also explained, exploring by implementing the camera sensors they can read, if I’m looking dulled today, or what is my energy level. So that is where we are trying to embrace it so that we can give them knowledge of what our employees are going through. Okay, so we can help them giving some holiday coupons, some beach coupons, some off time those things like save, if they look and they’re not able to share anything so so a lot of factor has been on Mental health of the employees also because sometimes as as an HR factor or a people engagement perspective, I may be opening up or I may not be opening up, I may be going through a lot of things I may be overloaded. So how the technology can be like how the enterprise can read those data having an analytics on or sentimental analysis on your employees, and they can tailor this for the benefit of their employees. That is how, what I see is that AI is going to be a big game changer in terms of helping everyone like a win win for everyone. Yeah,
Andrea Shiah 20:35
Vicki, man, if I could just build on a couple of things. Tiffany, you brought up a couple points in Jimmy and I think you also brought these points up, but two things, one on the change management. You know, making things easier for people is hard. That’s kind of what I’ve seen. Because ultimately, that’s what you’re trying to do with AI, you’re trying to make something easier for employees, your recruiters, HR, whoever it is. But the thing that’s interesting is it’s a change. And so change can be hard, I think the recommendation I would give is two key things, I think there’s two components to successful change. One is you have to have the inspiration, right. So all the utilization, you know, for all the users of your new tool, they have to be inspired, there has to be a reason for them to participate, there’s no reason, you’re not going to get engagement. So you have to be very clear on the inspiration and inspire them to use the tool. And for the purposes of talent, you know, it can be around mobility, it can be around, you know, transparency, it can be around upskilling, all those things are really inspiring things for employees. And then the second thing for change management, I think is making the action easy, helping them understand exactly what steps they need to take when I think is really important. So those two things combined really helped change. And then on the front of bias, I think the one thing I would say, I feel like, there’s four points I think you should look for, you know, when you’re working with any vendor, so that’s great, you know, if they’re claiming that they don’t have bias in their AI, but the one thing you always want to make sure is number one, that there’s no data use, that can create bias, that’s number one. Number two is that they are auditing themselves, right? Because you never know when bias can creep in. But you need, you need someone to be auditing themselves on a regular basis. Number three, not only are they auditing themselves, but they have a third party audit. Right, so somebody independent of them that they are commissioning to also audit them. And number four, if you’re used to using the AI, you should also audit yourself, do reviews to make sure because I think the worst thing in the world is to operationalize bias into your decisions. And so I think it’s really important that you’re doing regular checks on that. And audits are a really important way to do that.
Vicki Lynn Brunskill 22:59
Thank you. Excellent points. And so let’s build a little on that. We talked about engagement. And we talked about bias. But, Andrea, I want to go to you first on this. Can you share any examples of innovation in terms of applying AI for career development, talent acquisition, onboarding, all of those good? Points? Yeah.
Andrea Shiah 23:21
I mean, I think we talked a little bit about kind of mobility and learning, you know, when you give employees the transparency to see the roles that they can move to beyond what they’re aware of, I think that’s really important. Because all of a sudden, they’re able to look for opportunities based on what they know, not who they know. Unfortunately, today, when you’re thinking about your next job, you usually reach out to somebody that you know, to ask them about that job, and how it works. But not everybody has that network. So suddenly, you know, the great thing about AI is just full transparency. And that’s what makes everything so much more inclusive, and therefore better quality of talent results. So I’ve talked a little bit about employee engagement, maybe I can talk a little bit about recruiting, because I think that’s another very big priority for a lot of organizations, and there’s lots of competition for the same type of talent. A lot of organizations are building digital talent, you know, analytical talent, we’re all fighting for the same skills. And then if you look at these verticals, they’re all fighting for other skills like renewable energy and oil and gas. hourly workers are very competitive right now. You know, biotech is really important in the pharma industry. So each industry not only has their digital skills challenge, but they have their own vertical challenge. So recruiting can be very competitive. And I think the great thing that you get when you have AI, if you can know, you know, your candidates in the skills they have, you can actually find more candidates. That’s number one, so your sourcing becomes much stronger. I think the one thing that’s really powerful that a fold will do is that All your former applicants, their profiles come to life. And you can actually source from all your former applicants, which I think is very powerful, because those are warm leads, they’ve gone through the process of applying for roles at your company that’s really powerful to be able to source from that population. But then being able to really focus on those individuals that really have the skills that match to what you’re looking for. You know, the other thing AI does, too, is if you get a lot of applicants for a role, your recruiter can screen hundreds of resumes in minutes. Right, which is like, if you think about the idea that a recruiter still has to open and read every resume, it’s like, astounding, it’s really astounding. That’s a lot of work, it takes a lot of time. And I found when I lead the global talent acquisition organization and American Express, oftentimes, recruiters are so busy with so many requisitions, what they were doing was choosing the first five or 10 applicants that fit the bill, and then leaving some better talent on the table. Right, because they’re so busy, they find the talent, and then they move on. And you’ve got some, we saw in our analysis that we had some really strong talent, we just didn’t get too in terms of there reviewing the resumes. So being able to screen resumes comprehensively is really powerful. And then I think I talked about this regularly. But I think that diversity, having more diversity in your talent is really important, right? Being able to be more inclusive as you’re looking at talent, because you’re considering the skills and inviting more people to imply because they’re a match based on their skills is what comes about with AI, right candidates are able to go to your career site and basically leverage the matching to see what are the roles that match to my skills, you’ll get a lot more diverse applicants in that way, is what we’re seeing in our results. So that diversity brings a better quality of talent into your pipeline. So really important capabilities that you get when you have AI. I just, you know, I talked about, you know, mobility and employee engagement, and I just want to put a lens on talent acquisition to
Vicki Lynn Brunskill 27:13
Thank you for that. Anything to add on AI hiring and onboarding and career development?
Tiffany Ingram 27:20
Well, you took the words right out of my mouth onboarding. So you spend all this time getting the ideal talent, you identify that star candidate, and their first interaction with your organization, again, is the review or not the review of the interview process, but bringing them on as now a part of your organization’s family. And, you know, with AI, now you’re able to because onboarding behind the scenes without AI is a very, very labor intensive task for HR professionals. So with AI powered power systems, we’re able to develop those customized training programs, get those forms out to the candidates, before they even walk in on the first day they’ve done 90% Or if not 100%, almost, of the administrative work. So now you know you, when they finally reach your, your organization for the first day, then they’re ready to jump in and really learn what the company is about not being bogged down with those administrative forms and things that are such that may happen on the first day, you may also be able to provide them with virtual tools with these AI platforms, which again, now they’re learning the landscape before they even arrive. So they’re able to immerse themselves a little bit quicker. Overall, I’ve seen it enhance the initial experience that your new hires have. And it reduces their time to productivity, because it’s helping them feel valued from day one, versus coming in feeling overwhelmed by seeing everything for the first time. So again, implementing AI in your onboarding, I think is just as critical, again, as it is with recruiting too, as well, because you want them to have that energy that they had during the interview on their first day and not feeling overwhelmed by all of the things that normally happened. So it truly helps that I’ve seen it firsthand.
Vicki Lynn Brunskill 29:24
AI is a very powerful tool here. And then did you have anything to add on the talent acquisition, onboarding career development aspects?
Jabin Geevarghese George 29:32
I don’t mean just to add. I mean, pretty much Andrea Tiffany has covered everything but it is so exciting that someone takes my operation work you know, I just say that okay, can I make my day be easy? So as Andrea was saying that tons of resumes it is not an easy easy task to do like Tiffany was saying you fill up the applications, rank them etc. So that’s where I think AI document analysis engines can do a really good, good, like it could be a life saving thing for because, you know, a lot of it can take a lot of operations things from us, like summarizing the profiles ranking the profiles and, and also, which like, I think we could work on something enterprises are working on the whiteboard. Now, that opening is also coming and playing beautifully, what we say, trying to create it, we spit out AI something they have already given it, but they are trying to incorporate more translation power to it. So once that comes in as an HR, if I say scheduler, scheduler intuitively, and automatically, it’s automates the task, pulling up all the data brings them in the product owner, product owner, the free scheduler interview, I just say in few seconds, and AI does it for me. So just imagine I’m going to spend 10 minutes, and now this is going to be just 30 seconds or one minute. So definitely that saves a lot of things. So the two aspects, AI can help us elevate our operational tasks. And we can focus more on the strategy aspect of it. And, and it can, it can be really one of the key elements in talent division, definitely, because it’s the way we do not realize how much of the backend work is going on. And if this AI driven analytics and tools can optimize it, then it’s time to start using and embracing this technology. So
Vicki Lynn Brunskill 31:22
Thank you. Thank you. Excellent. So I’m gonna follow up with you on the final thing, and then you’re gonna have to, you know, predict the whole future. What’s next in AI for workforce optimization? Are there any tech trends you see as game changers? What’s coming to Ben?
Jabin Geevarghese George 31:40
Okay, so we keep That’s, that’s a very amazing question. Like what Andrea has told it is pretty much I’m aligned to what if new, also saying that these technologies are really good, but we need the ecosystem in place. So if every, every domain, or every business is having their own set of challenges, if you talk about healthcare industry, or retail, or renewable energy every so the focus should be on the low energy based solutions, because AI, it is very good. But imagine the power it takes to compute whatever the power consumption or the energy consumption using these AI systems, it’s not going to be easy. Now, the next challenge would be how we’re going to optimize and have low energy solutions to use AI into play, or bring AI into power. So that’s where edge computing is something we might have to be prepared for how to, like, I think Nvidia is doing a great job therefore for accelerating the AI network infrastructure, and using edge computing. So that is something we might have to see from a technology perspective, because then we have to live on this planet and Korea and, and have a better or non damaged situation on our own planet, right? So if we consume energy, like anything, because AI systems are going to consume energy, like anything, that’s where edge computing is going to be like, which is I think not as often of the lot of enterprises that might be just starting with it. But that is where we are moving towards. If you ask me, in the future, edge computing is something we might have to start looking at as an enterprise today. How to bring in that so that our AI systems can consume less energy, and we are not going to create another set of problems. That is one thing. And the second thing is definitely like us. The second future would be like, let’s say we do have a base operational set of AI. It is now how we create an AI ecosystem that is not easy, like blood connecting all these dots. We have touched upon Hr integration system, talent acquisition, and talent onboarding. But when we talk about bringing all the functions of an enterprise together, we have to talk about it as within enterprises, we can start to think of creating a marketplace, having our own agents making life easy for every employee and their operations. So those are the two aspects that I would say one is the low energy solution, start embracing edge computing. And the second is creating an AI ecosystem within your company, like having your own agent marketplace for your employees, employee base personnel. So that takes a lot of operational things and we can really add value for our customers, what we really can put in our critical mindset or the real solutions for them. Thank
Vicki Lynn Brunskill 34:31
you for the very, very important. And um, I see we’re getting some really good questions from the audience. But I want to make sure that Tiffany and Andrea have a chance to answer that question. What’s next, you know, put on your predictive hat and let me know. Tiffany, did you want to go next and let us know what you think there’s
Tiffany Ingram 34:50
one thing that well, just really, really quick and there’s one focus as we look at the well being of employees as a whole right I really foresee there being more AI driven employee wellness program platforms. I’ve kind of heard of this a little bit, there are a couple platforms that I’ve looked into. But again, just as we look at an understanding that our employees are our most precious resource, right, and again, like Andrea stated in the very beginning, you know, HR has a very, very interesting role to play, as it pertains to, again, bringing AI or showing the benefits of having AI within the organization. So, you know, with this AI could monitor and promote employee wellbeing, personalized health recommendations, just like we’re seeing personalized learning plans, they can also help identify mental support outlets, or possible solutions, and do help employees and organizations deal with stress. Right? Again, with everything happening, we expected to do more with less because of the talent shortage in the market. There’s an immense amount of stress, through the sentiment analysis that we’re seeing in these employee engagement surveys, employees are saying, Hey, I’m stressed out, right, I need some sort of assistance. So I really do foresee more of these AI driven employee wellness programs, along with some other things. But again, just looking at the employee as a whole. I predict that we’ll see more of that.
Vicki Lynn Brunskill 36:36
Thank you. So we’re gonna see AI for wellness increase. And Andrea, what do you think put on your predictive thinking cap? And let me know what you think’s coming next in AI for our work? Optimization,
Andrea Shiah 36:47
I’m in total alignment, I think, believe it or not, AI is still young. Right. And its applications are growing on a regular basis. And I think, even within a full, you know, we’re expanding, you know, the use cases for AI as it applies to talent. And I know, there’s a lot that’s happening now, as we talked to leaders around looking at their job architecture, looking at workforce planning. And then helping make it easier, as I said, you know, copilot is a common tool. Now that it’s available, it’s easy to expand and, and I think that code that plays a change management role to actually where you can help employees and prompt them on how to use these new tools, that’s going to be very much needed. I joined a session, actually with Microsoft. I heard them talking about their co-pilot, helping to co-pilot all the other co-pilots, because everybody’s needing help and kind of navigating all the new tools that are becoming available. So I just think, a lot of things, the application is going to continue to expand. And it’s going to ultimately help and make a lot of things easier. But then, you know, employees are going to need help, you know, navigating all these new tools. So there’ll be new tools to help employees navigate so those are kind of some of the trends that we’re seeing. Thank
Vicki Lynn Brunskill 38:08
you for that. Excellent. So I do see some great questions from the audience. And I’m going to start digging into them and feel free to jump in. To answer them. The first question that came in is how do you ensure the accuracy and reliability of AI predictions and workforce planning? And what can we do to validate these predictions? It’s a big question.
Andrea Shiah 38:36
I think predictions are really scary. I feel like we’ve seen in our data, like, skills are changing very quickly. You know, chat GPT is an example of something that just appeared overnight, and all of a sudden, everybody’s talking about it, and it becomes an important skill. And so your ability to predict what’s coming up? I don’t think that’s 100% reliable, a lot of what we look at is what are the trends, what’s rising really quickly as it relates to skills, and that’s a great indicator, I’d use that as an indicator, versus a predictor. It’s really hard to predict someone’s going to predict skills in five years, I don’t think I would believe them. But I think looking at the indicators of trends, whether it’s in your organization, in your industry, or in the world, I think is the best way to know kind of what’s coming up and be ready for what’s coming up. That’s definitely an insight, though a lot of our customers are using it.
Unknown Speaker 39:35
Anyone else want to add anything to that?
Jabin Geevarghese George 39:39
So I think, what pretty much what Andrea said we might have to look to cover data and analyze it, how we go, how it is like there is no success, or something that we can predict 100% of everything right? It’s about how we historically analyze our data and see how our forecast Screen comes up, based on actuals. And that’s where the strategic minds like the HR who have been playing that role, or the key partners, know how the trend has been. And then we need to realign our models. And there should be some technology, we might have to fix it, because the accuracy has to come based on how we also learn our ai ai model and also have to learn through the data. So to to, to say that there is no one size fits all answer for it. It’s about how your AI is learning and predicting it, basically. And we as in human minds, or HR players, or the strategy team, or the leaders have to see that. Okay, that’s how it resonates with actuals. And you just recalibrated. I think that is what the option we have. As of now. I think that is my take.
Vicki Lynn Brunskill 40:59
Thank you so much. Tiffany, did you want anything? We have swiping?
Tiffany Ingram 41:03
I know, we have so many questions. But I think Adrienne Devin really did a good job explaining this one. When I looked at the question, I was like, well, that’s a good one. And the only thing that I would just add really, really quickly, is again, you know, maybe conducting the scenario analysis. I know, Andre said, you know, taking in all of the data Javin talked about looking at looking at historical data. And just using all of the data points that you have to, again, validate those predictions, but maybe creating a scenario. And again, conducting that to see if that prediction actually would work. And maybe you can do it in a small pilot area or something like that. But again, they covered it, they provided great, great answers. I just thought of that immediately when I saw the question come in.
Vicki Lynn Brunskill 41:56
Thank you so much, Tiffany. So I’m just gonna think we have time for one more. And it’s hard to choose
Unknown Speaker 42:02
because they’re all I know, they’re all
Vicki Lynn Brunskill 42:06
I guess this one about existing workforce structures is good to kind of touch on as a key challenge as well. Can you discuss the challenges and best practices for integrating AI into existing workforce structures without disrupting current operations? That’s another big question. When want to weigh in,
Jabin Geevarghese George 42:31
integrating just to bring in what Tiffany and Andres point of view, we should have a good change adoption framework, not creating resistance. And probably we might have to create AI champions or HR champions, who have to educate our own employees, how this has to sit and coexist with you without disrupting your day to day jobs. And if sometimes, you know, we try to do certain good things for our users, and they do not like it, for example, some pop ups. And it gets annoying, and I’m trying to be cold or something. It says who is messaging notifications, etc. So we might have to take instant feedback also, from the employees, how they’re embracing it on those instant feedback, and the awareness from HR champions to AI champions who have to let other employees or the internal stakeholders and external stakeholders know that. But the change has to be there. But it is not creating a problem for anyone. So pretty much the change adoption strategy has to be on the high focus whenever we are introducing such new technology or those things. And I think there is another aspect of its workforce structure. So I’m not sure if Andrea can touch on it. But workforce structure, pretty much I think we are talking about the team sizing or something. I’m not sure. But from what I could interpret from the question was that how we make these types of new changes, we introduce it without the disruption of our normal Bau work or operation. So I think the feedback awareness could help.
Andrea Shiah 44:10
I think that, like the bulk of the work is the technical work, right, where you integrate AI into your platform. And then actually, that’s kind of the technical work. And then when you introduce it to the stakeholders, you don’t want to disrupt their work. Right, you actually want to be additive in terms of the value you’re delivering to them. And so you don’t even need to talk about being face to face, you just can employees, you can talk to them about hey, check out your profile completely. Take a look at new roles that you’re interested in, take a look at learning you want to build, take a look at career paths and development goals that you want to establish if it’s not meant to be disrupted. So you need to do everything differently now. It’s really meant to be additive or for your recruiters like, hey, you know, look at what you can do now with your candidates, it’s less about, hey, leverage the AI, I think it’s more about kind of the actions that you can take. So that’s kind of how I think about it.
Vicki Lynn Brunskill 45:16
Thank you. Thank you so much. Unfortunately, we’re out of time. All these good questions we leave in there. But thank you to the audience. And thank you so much to Tiffany to Ben and Andrea for being a wonderful panel and this great, insightful discussion. I want to thank everyone for joining us for this session. And this session, along with all of today’s content, will be available on demand following the event. And our next session will begin at 250 to five o’clock Eastern Time. And that will be a presentation titled developing secure LLM applications using private data. Please click on the join button that will appear on your screen to be redirected to that session and we look forward to seeing you there. Thank you again for a wonderful panel.
