Name: the AI spectrum: balancing automation and human connection across the talent life cycle
Uploaded: 2026-10-08T15:32:59.392Z
Duration: 58 min 24 s
Description: the AI spectrum: balancing automation and human connection across the talent life cycle

Transcript for "the AI spectrum: balancing automation and human connection across the talent life cycle": Welcome, everyone, to today's webinar, the AI spectrum, balancing automation and human connection across the talent life cycle. Good to have you all with us today, whether it's morning, afternoon, or probably evening, wherever you are. Just a quick house rules for today's webinar. We will have a interesting panel discussion, but we will also have some time for Q and A. So if you have any questions for our panel, please pop them in the chat or submit them here at the Q and A section, and and we will get around to answering them at the end of this webinar. This recording will be available on demand, so you will be able to share it with your colleagues if you're interested. And if we don't get around to answering all the questions, we will reach out to you afterwards. Most of all, have fun, and we'll have it over to our moderator for today, Glenn Cathey. Glenn, over to you. Alright. Thank you very much, Nina. So I wanna first thank everyone for joining us today or watching this as a recording after the fact. I think it's good for me to kinda set the stage for today's webinar, what we're gonna be covering. We have noticed, as you probably have as well, that organizations as they're moving past the theoretical phase of AI, there's kind of a fascinating friction that's emerging, where on one side, you have people using AI to help them in their job search, their application, and through assessment. And on the other side, you have employers that are leveraging sophisticated AI to attract, engage, evaluate, and onboard talents. And what we've done for you today, which is my pleasure, is to bring together some very forward thinking leaders to explore the current reality and the future opportunities of AI across the entire talent life cycle. I personally think you're in for a treat as we're gonna dive deep into how global organizations are practically deploying agentic workflows, navigating applicant AI usage, and managing the delicate balance between high-tech automation and high touch experiences. Now for those who may not know me, I'm Glenn Cathey. I'm SVP talent advisory with Randstad Enterprise. I focus heavily on helping companies with AI fluency and strategy and the AI transformation of work. I am truly honored to be joined by three esteemed panelists today. By the way, their LinkedIn profiles can be accessed via the speaker section on the top of the screen. Now we greatly appreciate you joining us today to share your perspectives on balancing high-tech with high touch across the talent lifecycle. Blair, Julian, and Sailesh, would you please take a moment to introduce yourselves in that order, if you don't mind? Glenn, my my, streaming went a little bit off, so I'm just gonna go ahead and jump in. I'm Blair Bennett, Perfect. and I'm a global talent acquisition for PepsiCo. PepsiCo is a 90 billion plus dollar company in the foods and beverages business, and, we, as a talent acquisition team, do recruitment for frontline all the way through top of house executive across many, many different, roles and skills. And so it's truly a pleasure to have been with PepsiCo for seven years leading this awesome team. The other thing within, my portfolio is all of our employer brand, our strategy, all of our program design, portfolio management, and the new capability that we're building called talent foresight, which we'll talk a little bit more about today. Prior Nice. to, PepsiCo, I was with Walmart. And prior to that Korn Ferry executive search where I got my start in recruiting over twenty years ago. So it's wonderful to be here with you. Thanks for being here. Appreciate it. Jillian? Hi. Hi, everyone. Jillian Snavely. I am, Accenture's global head of recruiting and onboarding. I have been with Accenture for twelve years and have been in recruiting my whole life. And so I have a passion for, our trade and excited for what we are about to experience or are already experiencing in, so much impact and change for recruiting in our industry. Before being at Accenture, I was at PNC Bank, and, my real true passion when I started recruiting, is learning how to source back in the day when there wasn't actually sourcing. So Glenn and I spent a lot of time together over the years, trying to figure out how we go out and get passive candidates in the most unique way. So so much has evolved, and I'm excited for what the future holds. and, thrilled to be with all of you today. Sailesh. Sailesh here. I'm a vice president at Everest Group. I lead our, sort of research and advisory offerings in the HR and talent space. So I have been an industry analyst for six and a half years now, tracking everything to do with talent acquisition, right, talent acquisition tech, talent acquisition services, operating models, future casting, what the sort of next functions, strategy, and functional structure looks like. Right? So, and then also a lot of the future of work surveys and research. Right? So I've worked with a lot of service providers, a lot of global enterprises on tackling a lot of current as well as forward looking statements these days, and this topic of AI is something that, you know, we've we've been coming up against a lot. So looking forward to today's discussion. Yeah. Well, thanks for joining us. I think, hopefully, everyone is now suitably excited given who we have here and the perspectives you're gonna be able to bring. I wanna first, throw it over to you, Sailesh. I know that you and your team have been conducting extensive research into the future of talent acquisition with regard to AI's impact. And as you're preparing to release your upcoming report, which I appreciate you sharing me a kind of an advanced copy, it's actually very thought provoking. Can you help set the scene for us in terms of a quick overview of what you're seeing out there across companies? Absolutely. So this year, we we have run three to four different studies, which have sort of evaluated various aspects of what's happening with you. Right? So we have looked at, let's say, maturity and adoption and transformation within sort of the broad talent acquisition ecosystem, like the people process, technology platforms, and the partnership, right, the outsourcing models, the vendor relationships, etcetera. We have done, we we spoke to a lot of enterprises about the impact that AI was having at the beginning of the year on their people and their processes as well. So, you know, went very narrow trying to understand how exactly on a day to day basis is AI creating, like, a positive or in some cases, you know, a challenging experience. And, obviously, what we are doing right now, which you you you had the preview for, is that we're actively trying to create a hypothesis on what the future of talent acquisition as a function looks like. Right? So for this particular one, we have spoken to, I think, roughly 100 to 120 organizations, and we have gotten a lot of inputs on how people are actually envisioning the next iteration of their talent operating model and especially their talent acquisition organization. Right? The bottom line that we have gotten across all of these studies and, you know, what's interesting to see the commonality or the common thread among all the organizations we are speaking to. I think most talent acquisition and HR leaders are very convinced of the fact that there's absolutely, you know, a future which no one really is sure of right now. Right? That's a... So no one really has an answer on what the operating state and the model and the the sort of intricacies of the workforce are going to look like. Everybody is sort of on their own journey. Right? So AI has been a massive disruption, not because of the technology itself, but because of the promise it presents. Right? So it... That's the the way you use AI can significantly impact your workflows, your experience, and that journey is looking very unique from organization to organization, from team to team. Right? So, there's a lot of, I would say, alignment across the global sort of thousand companies that, they need to actively reevaluate how they have been doing things for the last few decades. Right? And that is what I think everybody is working towards. And in the process of working towards that, there's a lot of reimagination and reinvention happening on the people front, on the sort of process front, the platforms front, as well as the partnerships front. Right? And it is becoming a much larger as well as, I would say, a more wider mandate than just being about recruitment. Right? And, obviously, we we have all of you who have spent decades in this industry. But I think finally, I I would say that we are in a situation where we are starting to move away from talent to workforce to work as a concept. Right? And there's a there's a there's a big amount of change and transformation needed to make that happen. And I think that's what, hopefully, we'll we'll hear more of, today from, you know, Blair and and Julian as well. Excellent. Thank you very much for that. I I always appreciate the broad perspective of being able to engage hundreds of companies and aggregate the information from what you're seeing. I think that everyone, by the way, who is attending this and registered is gonna get over... The report when it's actually released. And, again, it's quite thought provoking in terms of the future models of TA. So I'm gonna move forward. So thank you for setting the stage there. I'm gonna move into the... A question for you, Blair. You know, I know your role involves helping PepsiCo prepare, you know, for its talent needs over the next three to five years, you know, not just the immediate, roles that you have now. What can you tell us about what you're doing today to prepare for the future? And and what do you what do you think about the relation between humans and AI will look like over that Yeah. Thanks. And, Sailesh, what a great opening. Can't wait? to read the full report. The, so first, I actually do believe that our future is one where humans and AI are working very closely together and that the organizations that will thrive are the ones who are continually helping their people learn, adapt, and develop new capabilities as technology evolves. And, you know, I think that human creativity and judgment, empathy, trust building, and leadership are gonna become even more important. And that's why we are actually working on this new capability within our HR function called Talent Foresights. And we really picked the window of, like, three to five years, intentionally. We call... That's what we call horizon two. And I think part of this was, like, you know, the next twelve or eighteen months are already somewhat determined in investments, etcetera. And it feels like seven years as fast as things are going is probably too far out. So we think, like, three to five years is a sweet spot where you can still influence the business to make choices and shape their long term strategies. And what we're doing is we're trying to build really a next generation, workforce planning capability, what we're calling Talent Foresights. And this is really what we're trying to focus on, like, what skills and capabilities does our future workforce need, and how do we start to prepare that workforce today? And even though it's sitting within HR, we're really trying to design this capability that can be benefit to the entire enterprise because we wanna look at the intersection of business strategy, technology evolution, workforce trends, and external market insights to really understand how work is likely to change. And so in this, we're using scenario planning to explore multiple possible futures and really to start to look at signals, which tell us how the future may be emerging. And when we start to look at what the future might look like, that helps us start to build backwards into, you know, what roles exist today, what skills, what tasks, what tasks are gonna be most human centered, and how do those tasks and skills and roles start to evolve or reconfigure. And then we can put build buy borrow strategies against that where we can start to look at what skills do we need to be building our workforce today, what external capabilities might we have to infuse to be able to, you know, acquire skills that may not exist in our current workforce, Then where might we want to use external partners to enhance capabilities? Usually, you're not working with one lever, you have to look across all three. So this is really what we're trying to do to make sure that we're one of those companies who's helping our people learn, adapt, and develop new capabilities to, to move us into the future. So that's that's some of the work that we're doing and super excited to be leading it and where it's taking us. Yeah. I love that. I'm sure that many other companies are also looking into the future, but I... I've also seen you talk about this topic, in other forums, and I think that you're probably on the leading edge of of looking at it as as thoughtfully and as sophisticated as you can possibly be. So appreciate you sharing that. Jillian, let me move over to you for a moment. I know that you manage a global team responsible for processing almost 10 million applications and filling nearly 200 thousand positions last year. How do you balance the need for current and future skills gaps when you're hiring at that kind of scale? Yeah. Well, it's it's it's interesting. I was relating a lot to what Blair was saying. I do think the connection between your workforce planning and designing of what the future looks like is only, gonna benefit those that are actually then putting the... Going out and getting that talent and or upskilling that talent. Because I think it it... We don't know what the talent is. How can we build and nurture those pipelines and ensure that we have them readily available when the business makes that shift or doesn't make that shift? I will also say that there are ways in which... And in my personal opinion, if I can't fill at least 70, 80% of my demand with the 10 million applications I have, I probably should be fired. And I think the big focus is is that how do we take that really niche 20% and ensure that we're getting the best of the best. And so those... That 20% could be unique to very different by market. I mean, we operate in 52 different countries. So what we do in Japan is very different than what we do in India, so than what we do in The UK. And so it's really... It... It's looking at the market specific, looking at what the talent needs in that particular skill. We are kicking off a project right now where we're looking to hire 15,000 data and AI professionals. That's a... Some of that is a different skill than we're used to recruiting for, so we have to think a little bit differently. Always start with market intelligence, where the market has the most of that talent, how do we compete, what is our competitive advantage, some of the stuff that you think is recruiting one zero one that we should be thinking about, before we go into the market, and making sure our value proposition is strong for those people as well as how is our process fast enough to compete in the market. Right? And that's where we spend a lot of time thinking about how can we get candidates through the process even faster than we already are today. Again, another another thing we always think about as TA leaders is what is our our process and time. But I think making sure that we are prepared in advance because some of this takes time to nurture and and bring candidates in. Thanks for sharing that. So I'm gonna ask, Sailesh now. So, you know, in hearing what Blair and Jillian had said in response to my questions, how do you how would you say that compares to what you're seeing in the larger market across all the different companies that you're doing, taking a look at during your research? What do you what do you think the relation between humans and AI will be? Yeah. That's that's a loaded question for sure, Glenn. Right? And then I... People might hate me here, but I'll actually introduce another term. Right? So I think both Jillian and and Blair talked about skills. I think the future is actually sort of distilling more into tasks. And and why it tasks because I think there is unanimous view that, yes, there is a world where humans and AI will coexist together. But at a... organization level, I think leaders like Julian and Blair, they'll... And then, you know, the CHROs and the CEOs, all of them. They'll have to take a conscious decision on what tasks do they want AI to take up and which part of the tasks do they want the humans to go control and own. Right? And that is where I think we we are seeing sort of the greater sort of, you know, thought process moving towards. And I believe that, you know, hey. Today, we are in an environment where people report to people. People work with people. But in a, you know, task based environment, it will... You know, we'll have lot of agents sitting, running, and sort of working beside the human workforce. Right? And everybody's right now thinking more in terms of, okay, how do I bring in productivity? How can I spend, let's say, $50,000 and showcase cost savings worth 500,000? But the greater challenge actually is sort of breaking down this entire org model and sort of rethinking every single role, every single JD, every single comm structure to actually reflect a new reality of, you know, hey. What my what my company will look like with 5,000 employees and maybe, like, 5,000 agents. Right? And I think that is something that we are sort of in the early stages of. Right? We are we are seeing a lot of chatter emerging now around work redesign, Mhmm. around task intelligence. And I think that is sort of the inevitable future that all of us will have to move towards, especially if all of us are bullish on AI. Right? As an organization, I respect if a CHRO stands up and says that, you know, hey. I'm not going to... We're not going to have any AI in our ecosystem. Great. Then we can continue to have, you know, the total talent model that we have seen for years where you're using multiple channels of talent to bring people in. But most of the most of the people who are sort of, you know, on the other side of the fence, who are in favor of using technology in a greater and a bigger and a better fashion, I think they'll have to align to this view of, you know, people, tasks, agents, and then, you know, the workforce of the future. Yeah. I Can I just add to that? So. Absolutely. at home for us. Right? As we were bringing in AI to TA, we had to have strong principles. And so we did. We looked at every task that every player plays in the in the team and realized, okay, what falls into those three or four principles of using AI within recruiting and in onboarding and in background checks, and what do we want the agents or the AI to contribute to the signals of decisions versus making the decisions, and then how does the recruiter then or the background check reviewer or the sourcer make the final decision and or direct the signals up higher to where we want it to go. And so I think it's really, really important as I've learned along probably the last two years is what are your principles? Start with that. Like, what are your clear principles of using AI in your process? And then go down to the task and say, based on this role, all the... And it's brutal. Right? Because we all know in recruiting, we have thousands of tasks, but it is worth the investment to go into those tasks and outline what in the principles does it make sense for the AI to do the work versus the human. So, Yeah. like, Yep. bottom and for me. Yeah. And and, just... If I can add a interesting data point that came out of the recent study that we're working on, right, for the for the report that's about to come out. So forty three percent of our respondents, Jillian, right, they actually, want to create a enterprise office, which is responsible for all of this. Like, for workforce strategy, for. talent channels, Yeah. for technology, for data, and for AI governance. Yeah. Right? Because it's the... It's a... My earlier comment about talent acquisition going beyond its limit, that is absolutely, I think, of future that a lot of folks are thinking of and envisioning right now. Yeah. Yeah. And you have to have that. We have a couple of different. We have a responsible AI team that runs in HR, then we have a responsible AI team within recruiting. And, Yeah. really, because you have to make sure... I mean, obviously, from a compliance perspective, legal perspective, which is a hot topic right now, you know, you have to make sure you're... But if you're... If you always link back to your principles, what are your principles at the very onset and they're clear and you've gotten those approved, you should have no problem continuing to impact, continue to invest, continue to add if you just ground to the principles. Yeah. Nice. Yep. So thanks for the dialogue. I appreciate that. And we'll stick with you for a moment, Jillian, because I know when we were preparing for this, you would talk to me about a frictionless recruiting process, for technology roles specifically, you know, designed to move candidates through the funnel a lot faster. Is there anything you can briefly tell us about how you used AI to stream that process end. to end? Well, just as I was just saying, I think, obviously, grounding to our principles. The other thing that I I don't know if I formally have declared this at Accenture, but I've I've said it multiple times. I think our... We're just now into our new fiscal year, so we're into 2027. And I think 2027 is gonna be the year of assessments, because I think if you continue to add parts of your process where you want the automation to help move candidates along, you still have to have someone confirm that they have the skills that they say they have. And this answers a lot of questions. It answers the legal questions. It answers, do they actually have the capabilities to do the job? So for us, we have piloted this. We have about 15,000 jobs globally right now that are in this frictionless process. Candidate applies. We have a compliance agent that confirms or denies whether the candidate meets the minimum qualifications of a role at Accenture. That is for everyone. That role applies. It is a rule, right, not a decision. It's just we we know we can't hire this type of talent in these different parts of, our countries. And then they go immediately to, do they match the job description? If they do, then they go to an assessment. And that assessment is a sixty minute truly invested assessment to confirm or deny that the candidate actually can show us that they have the skills. And if they do, then they go immediately to a hiring manager. So the recruiter, by the way, is watching this activity happening to ensure there's no issues. Right? And they have processes or alerts that they get if they're, you know, so many questions that they're cheating on the assessment, it alerts the recruiter. But the recruiter's not doing the assessment. Right? We need the tech to do it for us because remember, 10 million applications, 200,000 hires, I don't have the capacity to do assessments like that. Right? So having a tech assessment be able to do that for me has not only decreased the time, it's changed the way the recruiter's working, and they're spending more time in the moments that matter. And I'm getting more quality of candidates because we're actually confirming without a human confirming or confirming by their actions doing this in an assessment so we know that they have have the skills that we need. Nice. I have a question next for Blair. But before that, I want to go ahead and pop up. There's a question in the chat that I think is very relevant to what you just shared, Julian. Do you see any kind of fallout at the assessment stage? We do. And it it... When you look back at it, it's because they don't have the skills. So they pass certain parts of the assessment, so they might. be a really good, like, software engineer, but they're not an AI software engineer because they don't know how to build an agent. So, okay, that's not what we're looking for in that particular role. But what I like about it then it alerts the recruiter. Right? And the recruiter says, wait. We do have roles that this person could be really good at, so let's repurpose them for another role versus saying, okay, they just fail. But, yes, we have dropout based... Because it's based by skill. Again, going back to what Blair talked about, it's all by the skill and the job family so that we ensure we're getting the right role and the right person for that skill. But what we've always stunk at in recruiting, which I I have no denying that we... I have really stuck at this my whole life, is how do you repurpose people? Because you get in your little funnel and you're like, oh, they're really good for this. And we've always talked about, like, how do we repurpose them and move them around? Like, now we actually can spend the time doing that because we're not spending our time prescreening, assessing talent that probably isn't a fit anyway. Because you go through... I mean, what? One out of 77 we have to assess? Like, a human having to do that takes the bulk of their day. Now I can have. them going out and matching people to other roles, which there's a tech for that too, but confirming that they can fit those other roles instead of them spending time doing the assessment. Yeah. We're getting some other questions here. We do have a Q and A at the end and we'll address some of these then. But I do want to move on and give Blair an opportunity to talk about in this particular section because I know that you've been doing quite a bit of work over the past few years in terms of literally transforming recruitment within your organization. I just wanted to have you share with the audience, how is PepsiCo using it to enhance the experience for all the people involved, the candidates, the recruiters, and the hiring managers? Yeah. Awesome. And and, Jillian, I think, you know, this idea of frictionless, and you also mentioned a point that I I feel very good about is I keep saying, like, in my twenty years of being in this industry, there are some things that we have always talked about and we haven't necessarily been able to solve. And one of the things that excites me about AI is I actually think we have now such powerful technology that can help us solve some of these things. And one of them that I always talk about is, like, talent pools and talent communities. Like, I think we can really do this now. So, Glenn, to your question around experience, like, first of all, we don't start with tech ever. Right? Like, we try to start with what is the problem that we're trying to solve. And when I think about candidate experience, hiring manager experience, recruiter experience, this is a space that we really want to be able to provide elevated and differentiate... experiences across all three of these elements of the recruiting process. And I think for candidates, you know, our goal is that we want candidates to be able to have easier access of information. We want them to feel supported. We want them to have a clear understanding of our opportunities. And the confidence and excitement about what's next and what can what can be achieved, at PepsiCo. And so in frontline hiring as an example, this is, we did a piece of work to totally, redo our frontline hiring our frontline hiring processes. We selected a new frontline hiring technology. We have a RPO partner who's new. So we really, like, broke it all down to build it back up. And part of what we have now is a tool that, you know, our candidates have a virtual assistant. They can apply with ease. They can answer, you know, questions about the role. They can do an assessment that helps them to understand and helps us to understand, like, are they gonna be a good fit for the role? And they're getting constantly updated along the way. And you know what's funny is, like, it wasn't that long ago that people were, like, literally walking into a facility and, like, filling out paper, and now they have literally a virtual assistant who's helping guide them through a process. So I just love that. I also love that it can help direct talent into different talent communities, and that allows us to have a much better relationship and build trust with our candidate. You know, also with the hiring manager in the same process, that virtual assistant is also now helping them. You know, we... One of our goals is, like, let our business leaders spend as much time focusing on the business so that they don't have to do, you know, burdensome tasks or go into burdensome systems. And so now, you know, they can really have an assistant who helps them open a job, who helps them, you know, know what's happening through the flow of a process, and they... We can give them time back. Right? So that... That's one of our goals there. And then within our own function with our recruiters, we really have started to look at, like, what is the entire process, and where can we enable our recruiters to do the more, you know, human centered work that really helps to have them exercising judgment, advising leaders, and creating experiences. And, you know, one example is, you know, we have put in the hands of our recruiters an interview companion where at the very front of the process, it is helping them to be more engaged with candidates and to be able to have higher quality conversations because they're not spending their time note taking, or they're not spending their time, you know, writing up summaries for the hiring manager. They now can do this in a much more, efficient and elevated way. And the insights that come through that information also can help drive more productivity later because they're able to look at, like, you know, how much time am I spending talking in an interview versus how much time am I allowing the candidate to give me, you know, really fruitful questions? Or what am I gaining from the candidate in their motivations that I can start to personalize my conversations a bit more to what they wanna hear and to what they're concerned about. And so I think it's just creating much more opportunity for relationship building, for trust building, for talent advising, and all of these things that I think our recruiters genuinely want to do and the the quality of work that they wanna perform. Nice. I I really appreciate that kind of, like, three sixty view and how you're thoughtfully considering all of the stakeholders, the human stakeholders involved. So to close out this section, Sailesh, I'm gonna bounce over to you and see if you can. offer the attendees, some advice. So when it... When companies and people are thinking about capitalizing on their AI investments, what would you say are three things that they should do when adopting a new AI solution? And, you know, What can they do. during implementation to ensure that it actually sticks? Because it's one thing to buy it or build it, it's another to get people to use it and actually start getting those business benefits. Yeah. Yeah. So so, you know you know, Glenn, this is a very loaded question. Right? Because I I can have, like, a one man analyst show for three hours just talking about, you know, 30 things that we'll need to do about this. But I think the core issue or one of the most fundamental problems that, I would urge leaders to focus on is data. The thing about AI is not software. Right? AI is not a plug and play solution. You know, I was meeting a global insurance company today. We were talking to their global TA team, and, I gave them sort of an analogy that think of it as... Not as something on your desktop that you click and it runs, but more like a second brain or a third arm that you actually have to learn to use, like, a prosthetic. Right? And that whole learning is dependent on what data you provided. So whether that's data across multiple platforms, whether that's data that's unstructured, or whether that's data that is being captured in, files instead of, you know, instead of databases, clean your data, structure make sure that you have all the data available before you start thinking about AI and transformation. Because the AI performance will only be as good as the data it trains on. Right? And that's where the second piece becomes important. Right? And it ties back to what we were discussing earlier. It is very important to understand that this is not, again, a plug and play solution. It is a complete reimagination of what you're trying to do and how you're trying to do it. So in that sense, I think to both Jillian's and Blair's point, it is very important to have a level set in the beginning. Right? We need to take... Let's say, if you... If you're if you're talking about AI within, let's say, your TA function, you need to break down every single task that your team is doing. So if a sourcer is doing 15 different tasks in a day, if a employer branding expert is doing 20 different tasks in a day, you need to have that whole thing mapped out and really need to sit and think about where do we want AI to play a meaningful role and when do we want AI to play a meaningful role. Maybe there's a phase one where you do five things. There's a phase two where you do 15 things. Right? But without that planning, approaching AI as a software or a SaaS play becomes very dangerous because that's where the risk of ROI mismatch, the risk of not seeing value, that that all goes through the roof. Right? And I think that's where the change management or post implementation piece also becomes important. So if I can share a personal anecdote. Right? So even within a risk group, we we have access to chat GPT. We are also encouraged to, you know, improve our turnaround time on research, on data collection, etcetera, using AI as possible. Now if I look at how my chat GPT used to respond to some of my queries, some of the grunt work I used to hand over to it. Right? Eighteen months or maybe sixteen months back versus now, there is a significant difference. Why? Because over the last sort of sixteen months, it has, it now has access to all of this group data. It has access to, you know, all the resource that we have produced. And it it it has learned how to think like me because I have taught it to think like me. Right? That, hey. If this is the problem statement, this is how you react to it. If this is the if this is the email you need to draft, this is what my phone sounds like. This is how I write emails. Right? So after sixteen months of training it, now it is in a position where I have a executive assistant without having to pay for it, sort of. Right? So that is the journey that a lot of people miss out on. I saw some questions around, you know, hey. How do you really get teams to, you know, adapt it and sort of jump over it? There's a big mindset and leadership aspect to getting AI adoption through the roof. And that is sort of explaining people how to think of it as a change in their workflow rather than, you know, hey. Another platform that you have click into and, you know, make their life suffer. That... That's not it. Right? So the change management here becomes complex primarily because you have to teach people to rethink their roles a little, rethink their tasks, and rethink their general day to day workflow. Right? And that is the breakdown that I typically see missing in a lot of situations. Right? That's that's sort of the myopia I think that exists in a lot of conversations, which are usually early stage. Right? So organizations which are still sort of exploring and just starting off, I think that's where I see a lot of mismatch. Mhmm. But then there are sort of good case studies like, you know, what what Gillian is doing and what Blair is doing at at PepsiCo and Accenture. And that is sort of a good sort of future state to target. Right? Like, hey. This is the clarity we want to have when we are going out there, when we are putting our implementation plan in this. Okay. So if I can summarize it, right, data, task mapping, and then the whole, you know, change management piece and the mindset shift. Those are the three key things that I would put on everyone's plate because they may not have thought of these three things. But, otherwise, if anybody wants to talk more, I can spend a week talking. Yeah. I'm a. lot of... not... Yeah. I know I I. asked you a big question. It's not easy to to provide a super in-depth response super briefly, but I think you did your best. And I appreciate the three key takeaways. I hope that, the attendees are finding them valuable. Yeah. I'm gonna move forward to the next section. I'm actually gonna go back to you, Blair. So when it comes to... I mean, we've already been talking about the fact that AI can help streamline lots of the things that happen in the recruiting process, but I'd like to hear from you how you think about ensuring that that human element remains an essential part of the experience. Yeah. Absolutely. And, Sailesh, I love what you just said. I absolutely agree that, those three takeaways are important, and I don't know that we can talk about how important data is enough. It is something that, is gonna become integral to everybody's every day. On your question, Glenn, so I actually... My my view is that with our... With the way that we're using, you know, different advanced technologies, like, you actually get to be a little bit more human. And I think what we are looking at is, like, where those human touch points can be elevated and where they matter the most. And so, you know, I think about, and and first, let me say, like, at PepsiCo, we have a responsible AI committee and all of the principles, and we're grounded in responsible AI, and we have a global framework. And so how AI technologies are procured, developed, and used across the company is very governed and very tight, which I appreciate because it actually allows us to have, you know, build build this trust around these technologies that we're using them in very, you know, responsible ways. But if if I think about, like, what I was talking about with our frontline optimization, for the hiring processes, One of the things that, you know, I mentioned is, like, our hiring managers have sort of less burden through the process now, and that gives them an opportunity to, you know, go focus on the business and and grow our business. But the other thing that it actually allowed us to do is as we were socializing the new process is to start working with the hiring managers and say, this is where we really need you to spend your time with us. If you do the time upfront to help us understand the role, to help us understand, you know, the conditions, the routes, like, all the things that we need to be able to make sure our candidate can align to, that is time well spent. Spend your time there, then we can go have the process fit that. Or with our recruiters, you know, our recruiters are very much still making the judgment on the hire. They are still working through the candidate conversations about the offer, a critical conversation with a candidate. They are still, you know, looking at, you know, the the workflows and the processes to understand, you know, where... This is a good example too. We're actually redoing our entire TA measurement strategy. And the reason we're doing that is because we wanna have a more systems look at, like, how our how our metrics and how the things that we're measuring are actually allowing us to be more predictive and to have more leading signals about where outages might exist in a process where we don't have enough candidate flow or where we're not getting the right matches of candidates. And I think those those types of, changes in a more systematic way of thinking actually allow a recruiter to be able to go into a process where they're most needed, to be able to talk to a candidate when that candidate needs them the most, to be able to make a judgment or a decision where that judgment and decision is absolutely critical to the process. And so I think that, like, be... Just because there are some tasks or some work that might be being done different, it doesn't mean that you are removing people from the process. You're just sort of reconfiguring where they're going in the process so that the human touch can be that much more elevated, that much more concentrated in the places that matter the most to the hiring manager to the candidate. So I think, you know, and one sort of proof point of, like, how important we think people are in the process, when we did our frontline hiring optimization change, we actually hired a team of people. And so this is, you know, part of where we're where we're trying to go is just direct to be human. Yep. Alright. I appreciate that. And I love how deeply you're thinking around the human element, and that hopefully is encouraging to many people that are listening in and watching later that, not all companies are just using AI to figure out how do we replace people when everything becomes completely automated. So it's very refreshing. Jillian, I wanna bounce over to you, in the same vein around, you know, we're saying that we believe humans should always remain a part of the process. You know, you you really can't say humans without also thinking the fact that people bring bias. Right? So everyone was worried years ago about AI bias, and the the funny thing I used to say is like, well, hello. You know, who's actually more biased? Is it humans or AI? And Who knows? You might find out that AI is less biased than humans. But give us your perspective on how you're thinking about using AI to protect against bias. Yeah. Well... And by the way, I was... I pinged in our group chat on the side for those who are listening that I was saying amen to Blair and a 100% aligned all of things you said. It's like, yes. Yes. Yes. From a bias perspective. Right? So again... And I'll... I see a lot of pings in the questions in the chats around legal and doing this in the right way. And as Blair said, you know, we all have dynamic, responsible AI principles, policies, people looking over this. And it... There's a lot of anxiety in it and a lot of concern from a lot of legal and or compliance folks. And I think when we look at the data, which we've talked about a couple times, and we use that to tell the story, it is... It was very clear to me that as we watched and monitored some of the ways we were doing the matching or the ways that we were hiring and the ways that we were using the AI to help us inform those different signals in the process, that when we didn't have AI, there was more bias from the human. And listen, like, as much as we all wanna say, we're trained as recruiters, we're trained as HR professionals, We cannot a 100% deny that there are things that come into our experience that make us want to choose somebody else because you had a connection with them, influence the hiring manager to choose somebody else because you had a a connection with them. Like, those things happen, and it's okay. Right? It's okay because we are human. That's naturally how we're designed to be. But when you compare that to the tool, the tool doesn't have the heart. So it doesn't carry the heart and the mind that we do. It has a different type of heart and a different type of mind than a human does. And so we, in fact, when we watched the data and looked at it over a period of seven months, nine months, and we watched it, it was clear when you did a side by side comparison that, unfortunately, the human was actually inserting more bias than the tech. And I have examples of that. I mean, I can tell you we were hiring people that I didn't think were exactly the best match for the role. And do you know why? It was because they were referrals. Nice. So... Right? Like, we get a referral and we think, oh, we know that human. We know that person, so they're gonna be good. But do they actually have the skills when you compare them to someone else? Maybe not. And so I think, like, again, a human bias. It's okay. Yes. A referral is a good source. It's always been a strong source for us. But do they... Are they actually the best candidate? And, Yeah. unfortunately, we make decisions with our heart, and that can that can creep in to some bias. I really appreciate that twist. I think you've got me on that in our prep call. I didn't actually know. But it's true. And, obviously, referrals can be a fantastic source of hire, but as you pointed out, they can also be a, unfortunately, fantastic source of bias. Yeah. Yeah. Mhmm. Nice. Thanks for sharing that. Yeah. Looking looking at the time, I think I'm gonna ask one more question. I'll direct this to you, Sailesh, and that'll leave us, hopefully, about ten or so minutes for Q and A. We've got some questions that we've queued up that we'll be able to throw out there that are juicy, and I think I have one myself if I can slip it in. But, Sailesh, before we hit Q and A, let's talk to the talent leaders out there. If they're trying to create a future in which they can benefit from this next generation technology with AI and agents, while they're making sure that people are still included? What advice might you have? Yeah. I I think it boils down again to the to the sort of mapping and the planning piece that we that we have spoken about multiple times today. Right? I think what is important to understand, first of all, is that this is not really a sprint. What... Whatever we are talking about today, it's a multiyear transformation that, you know, everybody's on right now. Nobody knows the end stage. That's the beauty of it, I feel. You know, as as organizations almost always, you know, whether that's functional leaders, business leaders, we always have sort of a summit to work towards. We know what best in class looks like. Right? But because of the disruption happening right now, we don't really know what that looks like anymore. Right? So everybody is free to envision their own future. So for for HR leaders, for TA leaders, I think a few things that I would I would point out is... One is that, in the conversations we have. Right? So we see HR and TA as being some of the teams which are very notorious for pushing back a lot on big change. Right? And and it also comes from a lot, from a fatigue. Right? So there's so many tools and platforms that the average recruiter has to click through in a day. Right? There's a lot of resistance to, again, having to work with something new. Right? So I would genuinely urge, you know, leaders to sort of think about, you know, not just how to improve productivity, but also how to improve the entire experience. Right? So a lot of the sort of use cases that Jillian and Blair talked about today, for example, it has been a lot around managing the workload, improving the recruiter experience, improving the hiring manager experience overall. Right? We have been focused on candidate experience for a very long time. I see a lot of questions around candidate experience today, but very few are asking about recruiter experience or hiring manager experience. Do we do know how our teams are feeling about all these big ideas that we have? Right? So, you know, so that's sort of like a broad idea, but I would say that... I mean, yeah, I... You have to, you know, really think about... Again, coming back to tasks. Right? What do you really want your people to control? What do you want your teams to retain? And where do you see the biggest opportunity for AI to be? I I love the word you used, Glenn, in the chat. Right? Resource. It's it's... Think of it as a junior resource. Think of it as an intern you have access to. Right? So really think what you want to outsource to the intern, so to say. Right? So so I think that is the key question any HR or TLD doc has to answer before they start on this journey. Right? And some of the data points that are coming in from our research, right, there's a lot of thought around sort of evolution of roles. So, obviously, in a world where certain tasks are going to the intern, and your sources and your recruiters and your coordination, you know, managers and your employer brand experts, your advisers, right, your business partners. When their tasks start to evolve, we also have to think about how the roles will evolve. What might be the potential version of a sourcer two years down the line? What do you call a employer branding specialist three years down the line, right, when they are very well adapted AI? So I think that is also a big question to answer. And we are trying to do that hopefully through the research and, you know, when when people get access to the paper, they'll go through some of these ideas. But these are some of just the key questions or the key provocations I would like to leave the leaders with. Again, very few people have answers to these questions, which is why I'm reiterating again. This is not a sprint. This is a marathon. Right? There's. a lot to figure out. But, yeah, just just... These are the questions that I think everybody should mull over before they go back and, you know, talk to their teams about how AI is gonna change everything. Okay. Thanks. I can say one more thing. I know we're running out of time, but I really want to hear or allow, Blair and Jillian to maybe briefly answer this question. And we'll start with you, Blair, and then we'll go with Jillian. So if you were to... Since you've been on a journey, right, but if you can actually go back to your past self at the beginning and offer yourself some kind of advice at the start of your AI journey, that maybe that thing that would have saved you the most time or pain, what would that be? Oh, it's such a good question. I actually think that, it's probably more about, like, giving ourselves grace. Right? Like, I think at. the beginning of this, it was like, oh, I have to, like, keep up with all of this, and I have to learn every tool that's coming out, and I have... Like, it's impossible. So. I think it's, for me, a little bit of, like, just start somewhere. You know, you're starting by listening to this podcast. Great. But start somewhere, use things, practice things, put, you know, put put some, you know, day to day practices in, but but I think give yourself grace that it's really hard to keep up with everything right now. We don't have all the answers. And I think, like, these types of forums and conversations help us understand that we're all on the journey. Nice. Alright. Thanks, Jillian. Anything to add? love that. I was gonna say grace too, Blair you stole mine. But, I will say test. So it's it's good to test small. So, like, just try something small and then... And expand. At Accenture, we're always wanting to scale quick, and I I, we try to just start with little small petri dishes. So I would say test first. The other thing I would say too is that take time yourself to become an expert in the tools or in whatever you're gonna use AI for AI for. Right? Like, you can't be out there... I mean, Blair and I both as leaders, we can't be out there preaching all this change, and it's immense change if we don't do it ourselves. And so we were talking before we came on, there's a couple searches I still carry, to keep my my trade up. I use AI in those searches. So, like, teaching the team that I can do it, they can do it, how I do it, will show through examples. So I would say, don't be scared to just dive in it yourself and learn along the way. Nice. Nice. Thank you very much. I'm gonna pop over and I'm gonna do, a little bit of a catch all in the Q and Q because it seems like a a lot of the questions that came in were around candidate experience and some candidate frustration about when they apply to a job that they immediately get greeted by AI. And although you've all actually talked about how that can have some positive elements, how are you thinking around the fact that some people are resistant to that? That they're not really crazy about, like, what? I don't get to talk to a person. You know, I have to talk to AI first before I get to a person. Just share some thoughts with the the attendees around how you guys are approaching that. Taking any order you'd like. Yeah. So I'll just go real quick. I actually called the first candidate that went through our frictionless process where they didn't have a human talk to them. They started the process at 1AM their time because they had worked a third shift or a second shift or whatever they were off early. They didn't... They got to schedule an interview with the hiring manager within three hours of them applying. Had they have had the... Gone through the original process, they would have waited for maybe twenty four hours, maybe forty eight hours, then their excitement... You know, emotionally, they get excited about, oh, I applied to this job. I wanna see what happens. The candidate told me the most fascinating for that person was that they knew where they stood within three hours of applying to the role. And so sometimes I think we take for granted that our candidates sit back, and it's an anxiety moment when you're applying to a new job, whether you're happy in your job you are, whether you've lost your job. There's a lot of anxiety around that. And in our past processes, having done them myself, I would be like, thank goodness I got to the candidate within five or six days of their process. Like, that is so far from the truth now. Like, if we don't get them within hours, they're going somewhere else because they're anxious and they need something or they want something. And so I feel like the candidates are appreciating the fact that they don't have to wait to talk to somebody that they can continue to go. However, and Blair mentioned this, when they need a human, it's very easy to find one. Right? Like, they can go into our chatbot. They can say, I need to talk to somebody. They can send a text message. Like, there's lots of ways that they can interact if they need someone. Not everybody needs someone. So let let them go their... The path they want. Alright. That's fair. Yeah. I really appreciate you sharing the perspective. Blair, do you have any, additional was just... thoughts around? was gonna add one thing in that, you know, we actually are... And I'm sure, sure, Jillian, you guys are doing this too. But, like, we are constantly, like, monitoring how the sentiment around our digital assistant is. Right? And so I think there's... You know, there are probably some candidates who are less comfortable, and it's like any journey. Right? Some people are, like, fast adopters, and some people take longer time. So I never wanna deny that some people may be, like, a little bit more reticent, but I think that's what Julian's saying. Like, there are opportunities to have human interaction. For those who are comfortable and they're using it, we're also consistently going in and saying, how can we make this better? How can we make it feel more personal? Is the question... Are the answers we're giving, like, what we want to be giving? Are people stopping at any point in the process? So I think there's just all these areas where we are constantly looking at it. We're not just, like, setting it and forgetting it. We're working with it. We're improving it. We're iterating on it, and only to continue to make those experiences that much better. Nice. Yeah. Thanks for that. I can just. add if I can just. add one. data quick. point to. support both... Yeah. Yeah. So the 15, 20 companies we spoke to last year who were piloting a lot of these tools, What we noticed as data would... Which Boils down to candidate satisfaction is none of the CSAT scores had dropped after the pilot's run. Right? So I think that's great news that, you know, hey. If your CSAT scores are not reducing, people are not really hitting it. It's a different way of doing it. Obviously, people candidates will have their own preference. But that early cohort we spoke to, none of them have seen a dip in CSAT, which I think is a big testament that there are obviously candidates who don't mind this. So. That's great to be able to back that up with the data point, and you guys are doing great work in this area, all of you as from a company perspective. So I'm just gonna wrap this up as we have just under two minutes left. First, I have to say, Jillian, Blair, and Sailesh, I thank you very much for your time, agreeing to be here, sharing your perspectives and the insights that you have, and for the valuable discussion. I also want to thank everyone who took the time to join us today live or watching the recording later. As a reminder, anyone who registered, you're going to receive an email once that Everest report is is released in final form. Everyone will get that and, again, at your end for a treat because I've seen a early version of it. You'll also get a link to the recording, which can be helpful for maybe your teams that weren't able to attend. And if you're interested in learning more about AI fluency and work redesign, you can find me on LinkedIn and reach out. Happy to continue the conversation. But thanks very much. This has been fantastic. I learned a lot myself. I hope everybody else found it valuable, and I appreciate the discussion. Thanks for having us, Glenn. Thanks for. listening. Yeah. It's been great. a good have. a good a great, rest. of your day. Thanks.