Transcript for "Pole Position for Progress: How Humans and AI Power F1's Future Organisation": Hello, everyone. Thanks for joining us for this looking forward with Workday webinar. We're just gonna give it sixty seconds as I can see lots of people still joining, and then we will start our webinar. In fact, while we're doing that, let me move forward so you just so you can confirm you're in the right place. So poll position for progress. I hope you like, what I came up with there to play on words. How humans and AI power f one's future organization. Okay. Just waiting until it's one minute past ten, and then we will get cracking. To those now joining, we're just just waiting until one minute past ten, and then we will crack on with this webinar. There we are. One minute past ten. Let's go. Gentlemen, start your engines. So that's the last one I'll do with that. It's not very funny. Right. So okay. So we're, really, today, very excited to have Alastair from Formula One with us who we'll introduce properly in a moment to really talk about how humans and AI are working together to power f one's future organization. So but before we get into that, just a bit of housekeeping. So, if either of us make forward looking statements about functionality we're perhaps working on or road map functionality, please keep in mind that future plans can change, so only make purchasing decisions on currently available functionality. So, you'll you will receive a recording of this web webinar in about a day, in twenty four hours. So you can share share this with your colleagues if you think they would be interested. At the end of the webinar, we really want to, encourage you to ask us questions. You know, we want to have q and a. And we've got Alastair here from Customer F1 and myself, ready to answer questions. I'm one of my more technical colleagues, Michael, sitting in the background. And if you do have any questions, don't wait until the end. Yeah. As the question pops into your mind, enter them into the q and a, panel on the right hand side there rather than the chat. Yeah. So please, enter those questions in the q and a. And and for those of you, who aren't asking questions, but have a look at those questions and vote for the questions. Give a thumbs up for the questions you would like us to ask. And then what I'll do is those those questions with the most thumbs up, we will go to first. And right at the end, we will, ask to fill in a survey about the webinar because, you know, we want to hear your feedback that helps us shape the future sessions, that we have planned so that we're actually producing content and, information that is of interest to you. So we really do appreciate your your feedback. So, this is the sort of the the agenda. Now we're not actually gonna have any slides. This is just to give you an idea of the flow of the session. So we're gonna first talk about obviously, introduce Alastair, talk about Formula One, the organization or the business as as it may not be what you think. Then we're gonna talk about the challenge the challenges that Customer F1 was was facing and and the vision that they had future. Then we're gonna drill into really look at very interesting use case around the, AI in HR. And really, Alice is gonna share with us the impact, you know, the in terms of the results that using AI has had in HR and any lessons that they have learned. And then we'll we'll close off the conversation, with looking to the future, and then we'll open up for q and a. So we should definitely be, at q and a at the latest by half past the hour. We want to make sure we have plenty of time for q and a. Okay. So, just to introduce myself. So I'm Richard Doherty. I am a senior director here, at Workday. Been with Workday for over ten years, and my focus is on our HCM solutions. And I come sit at the intersection of product marketing and sales. And we are joined by Alastair. Sorry. Alastair, I've been banging on, haven't I? You haven't had the chance to to say anything. So let me That's quite alright. You keep talking. I don't mind. No. People don't wanna hear me. They don't wanna hear you. So let me stop sharing the slides. There we go. So now we're full screen so we can see each other. So, first of all, in case I forget, thank you so much for agreeing to be on this webinar and share your experience. It's really greatly appreciated by Workday. You are a fantastic customer, and we really appreciate it. No worries. So to kick things off, you know, tell us a little bit about yourself and your role at Customer F1. Yeah. Thanks, Richard. So, yeah, I'm I'm Alastair Goss. I'm the HR systems lead at, Formula One. You know, we we primarily use Workday for for much of our systems requirements. So, you know, in short, I look after Workday at f one. I've been here for around eight years. I actually began life in the HR team. I was a senior HR business partner, merrily minding my own business when the work implementation project came along, and, was asked to get involved. Initially, really didn't want to get involved, actually, but begrudgingly said yes, and then have not looked back since as I discovered that, systems are easier to manipulate than people. And I enjoyed that much more. So, I've been, yeah, in the HR systems world since, I I guess, you know, 2022, and and very much enjoying the, change of change of career that I've had. I think it's also probably worth introducing the company right because, you know, many people will know the sport. I think most people will know the sport, but I think fewer people will know what we as an organization do. So, Formula One, is the commercial rights holder for the sport. We're responsible for for three main things. So the sports, event organization, so where the Grand Prix are held, the sports broadcast. And whenever you watch a Formula one race, you'll be watching the footage that we have chosen to present to you, and it will be identical across the globe. Ultimately, though, we're responsible for revenue generation, both the teams, who receive that, cash as prize money at the end of the season, but also, of course, for our shareholders. So back to the question about what I do, well, I want our staff to be focused on those three main things, and I think that means having, a system that, increases efficiency is easy to use and, you know, not the other way around. Perfect. Brilliant. And, you know, I mean, that's all very good, but, you know, can you get me some free tickets for the British concrete? No. Just joking. Just joking. Just joking. I can, but it might cost you my job. I'm gonna say no on this occasion. Yeah. No. Say say no. We're being recorded. Yeah. So Formula One, you know, obviously, is a brand synonymous with innovation and high performance. Right? When you hear future of work, you know, what do you envision? Thinking a lot about this before the session, and, it's just reflecting the fact that at f one, we don't think the future of motorsport, nor motor vehicles more broadly is just electric engines, unsurprisingly. And, actually, we we believe it's in a it's in a combination of hybrid engines and sustainable fuels. And and I was reflecting on the fact that I think, that, you know, AI is to the workplace as batteries are to the engine. So I I in my in my mind, I I see AI providing the necessary productivity boost that's needed rather than being the answer in and of itself. Yeah. Nice. Thank you. Great answer. So shifting to sort of now maybe talk about challenge and the vision, that f one have within HR. So looking at things from a HR perspective, you know, what would you say are some of the unique challenges you face operating in this very dynamic global and high profile f one environment that you've you've touched on? Yeah. I mean, there there are many. I mean, we we like to think that we as an organization are entirely unique. Of course, that's not the case. Many organizations operate globally. But there are some very distinct challenges that I think we do have. For me, I think one of the main ones is the, mismatch between the size of our organization and the size of our brand. So, we have a current headcount of around 800, but yet yet the sport has over 800,000,000 fans worldwide. So there's massive mismatch between the size of brand and the size of our actual company. And I think the main challenge that creates and it's a really, really fantastic challenge to have, but we attract people from all over the world, for roles that we advertise. But we're, you know, primarily based in The UK, you know, face the same employment sponsored challenges that any UK employer faces. And I'll say I'm not, lamenting that challenge because I say it's a real privilege to be able to attract that many people to roles that we advertise. But I do think it creates a very distinctive challenge, that certainly, you know, over the years of working at F1, I have been searching for solutions to try and solve. And if we perhaps, look backwards before the current state, you know, with Workday and, our AI related solutions, you I guess you relied on, you know, legacy systems, manual processes. Can you share with our audience sort of, you know, the the sort of inefficiencies and frustrations this created for your HR team and and the hiring managers? Yeah. I mean, yeah. For sure. It it's when when I arrived at Customer F1, we, and, you know, in in the years that were before Workday, we had many disparate systems. So our and payroll system was different to our ATS, which was different to our performance management system, which was different again to our time and absence system. And none of those systems talk to one another. So, you know, relying on, for example, you know, communicating changes that need to be made in payroll when somebody was on maternity leave was all manual. And it just there was so much that was done manually, that needn't be done manually. And so we were really, we were really keen to move to a solution that could help us step forward from that from that position. And, just before we drill into an AI use case, just obviously, you you know, the the organization Customer F1, chose Workday. Can you can you share with with our audience, you know, why why why why the decision was to go to go with Workday? What was it about Workday that you felt would support? You know, remove those inefficiencies, drive the productivity, and so on. Yeah. I mean, it's not as many people assume a product of our broader or the the broader commercial relationship that that that we had. I think I think people do assume that because, well, there was a sponsor of Customer F1. It was the foregone conclusion that we would choose that system. But I can categorically confirm having been involved, in, you know, the process behind the scenes that that wasn't the case. You know, Workday was chosen for its own merits, and the two relationships, in a customer and commercial are entirely separate. And so, you know, really, we we chose Workday because, it allowed us to take all of our disparate systems processes, you know, not just those four systems that I mentioned, but all of the processes that kinda went in between and around and consolidate them into one holistic solution. And for us, when we were taking a decision, you know, Workday was the was the obvious answer. Perfect. Brilliant. Right. So that's sort of the the background, the challenges. So, you know, you you you touched on there. You were receiving a huge volume of applicants per open position, you know, very reflected by the size of your organization versus the the profile of the organization. A nice problem to have nicer quotes. Right? Because that's it's actually not very nice at all. Yeah. And you gotta protect your brand. Right? You know, you don't want you know, you need to be you need to be careful of how you manage those incoming applications. So and I know our audience from all and also this is generally for all the meetings that I I get involved in and the events. You know, everyone's talking about AI. Of course, you know, it's transforming work. It's transforming people's roles, and it's moving forward at such a fast pace. And I think our audience, you know, are really keen on sort of practical AI use cases. How our organization's really using AI, and you're a great example of that. So tell us, you know, how you're using sort of AI to move away from manual processes Yeah. And, specifically, let's look at recruiting because that that's where you had a massive challenge. So tell us a little bit about that. Yeah. Yeah. And I guess to kind of reiterate what I said about the start around AI, you know, providing the necessary boost. I I think it and what and what I've seen kinda confirms this. I think AI works best when you really point it at a very particular problem. When you give it focus, you give it parameters to work within. You say, here's what I need. You know, it's all about good prompting. Right? That's what we're all learning about in our kind of AI journey. And I think for me, as I say, for a long time, you know, both in HR and then as I stepped into the systems world, I had been thinking and wrestling with ways in which we could do something better in our in our, for our recruitment team. I mean, just to give a kind of bit of a picture of the of the context. So, in the previous twelve months before we took the decision to purchase Hyatt score, we'd had around 78,000 applications for 150 job requisitions. So it's an average of 520 applicants per role. Our talent acquisition team is only 3.7 FTE. Now I won't bore you with the math, but that's a lot of CVs to review in a short space of time. And and, indeed, they they don't have the time to do that. Right? But this is not the only thing screening CVs is not the only thing they're responsible for. You know, we want them to be proactive, to be strategic, to be spending the time with the hiring managers, doing the legwork at the start of the process to make sure we're drafting good job descriptions, all those good things. But, actually, because of that high level of, applications, I was pretty confident, that the team were having to to resort to some fairly blunt sifting methods certainly to get the, you know, number down to a manageable level to to review. And I was also fairly confident, therefore, that we were sifting out stellar candidates at stages too early in the process. And I think that point was really brought home to me when one of the TA team said to me once that they'd had a recruitment agency present back to them a candidate that they had sifted out who'd you know, they'd applied directly, and they'd sifted them out too early. And and they've been sifted out because the salary expectations were too high. But a quick conversation with that person, you know, able to check whether there's any flexibility on that point, you know, and the agency were quickly able to ascertain that, actually, this person should be in the mix, but the member of the TA team didn't have the time to do that. And so, you know, we heard when I heard that, I was more convinced than ever that we needed to do something to fix this fix this problem. And the choice then is very clear. Right? You know, you either hire more people to do that reviewing for you, or you find a smarter way, to solve the problem. And as I've kind of hinted, and this won't be a surprise to any of you on the call, you know, AI was the obvious answer. It was there. It could do the heavy lifting for us. And it's, yeah, I was very keen when I saw high score for the first time at Elevate twenty twenty four. Suddenly, that was, like, okay. This is this could really be a game changer for us, and I was very then excited to kind of pursue it and try and get it in at, Formula One. Perfect. And and just to just to clarify to our audiences, so HiredScore AI is a part of Workday's, talent acquisition suite. It's a company that we acquired about a year and a half ago. It's now integrated into the Workday solution. You know, it's a fantastic AI based solution. But and perhaps, Alastair, I mean, before we we sort of talk about the introduction of that and how people have responded to it, How how are you how is f one actually using HighScore AI? What what what what what does it actually do for you? Yeah. I mean, you know, we're relatively early in our journey. So we went live May 19 this year. And and I'd always thought this that our usage of it would be in stages. You know, solve the initial problem first, I e, help the talent acquisition team with their screening and then step into the other benefits that HiveScore can offer. So, primarily, we're using it presently as a a tool to help us review CVs at that early stage. We're not we've not yet got into the the great functionality, I would say, that HiredScore offers around fetching candidates. You know, we've got a big a huge pool of previous applicants. I'm excited to see what HiredScore can do for us in terms of finding great people who've applied previously. But I think that will happen in time once we've really started to see the the time saving benefit from those early stages. And, again, the other thing that we're kind of working on, and we'll be introducing at a later stage is some of the masked screening functionality. But, again, that's something we want to do later. We know as I do it We're really trying to do this in stages to do it well. You know, as as many of you who know the sport will know, f one has a a a DNI charter. The the teams, the FIA, we have all signed up to this charter and committed to look at our practices to do things differently, to do things better, and to meet some of those DNI challenges that we see within the sport. And, again, when I when I looked at Hivescore and the my screen that it offered, I I I thought actually that could really help us do that. So in time, again, that will be something that we bring in, to meet some of our, you know, public objectives around around d and I. Yeah. And I I think as well, I mean, the the left the the main point I picked from that is your your challenge was the volume of incoming applicants, right, that you were receiving. So that that is what you focused on initially. It's not, we haven't got enough candidates, so let's let let's dip into our existing candidate database. Right? So may makes perfect sense. So, you know, as we as we introduce AI into our organizations and our employees, and in this case, recruiters, were given these AI tools to, help drive efficiencies and and and and, you know, remove a burden from their workload. How how how how did and how have your recruiters responded to the introduction of of HighScore AI? And, you know, did they need to sort of build up trust in the solution? What, you know, what did that look like? Yeah. I think there has absolutely been a period of adjustment for the team. I think, you know, I said I said the size of the team earlier. I said, you know, 3.7 f t, four people. There was definitely a mix of feeling. Some very, very excited, some less excited, a bit more apprehensive about it. But I think it you know, for me, I knew it would take some time to to get that trust in in the tool. And as a result, I was really keen to involve them at the earliest stage possible and give them time with Hivescore before you we went live with it. And I think the more time they've had with it, the more time they've spent using it, they've got more comfortable with it. And, I'd say the the the more they use it, the more their confidence and trust is increasing, the more they see great candidates being well rated, you know, and they're doing their kind of comparisons and checking and making sure the the more confidence they then have in the candidates that high scorers, you know, Workday is presenting to them as the best ranked candidate. So, yeah, it's taking time, but I'm definitely seeing trust increase within the team as we go along. Yeah. No. Good. So, obviously, one of the way one of the ways of of increasing trust in a in a in an AI solution is is to have measures of success, and you kinda touched on it there a little bit. So, you know, has the since the introduction of, HighScore AI there, has the process, you know, become more efficient? Have you saved screening time? Have you been able to measure that? Yeah. I mean, yeah, it's it's it's a really important question. Well, probably the most crucial. What impact does this have? Going into the project, I had three main criteria for success. The first, as you know, screening time. Can we bring that down? The second, and again, is that nannies will be a shock to people. The time to fill, can we reduce the time it takes to fill positions that we've got? And thirdly, agency spent. Can we decrease the amount of money we're spending with agencies? I think on the latter two, I feel like it's a bit too early to make an assessment on those fronts, but certainly on the first. And I always assumed this would be the case anyway. But with screening time, we we have seen a a pretty dramatic reduction actually. So, we've had a 43.7% reduction in the time taken to screen candidates. I mean, yes, I've been anywhere live May 19, and I've already seen that. And I think that, you know, that's a really big tip. That was the primary aim going into this into this project. So I'm I'm really pleased to have seen that. Yes. Massive massive benefit. So so we I'm talking there about the the sort of the the recruiters and, you know, the sort of their experience. But, yeah, what about your candidates? Do you think this is improving their experience in any way? Yes. I think I I I believe so. And I was, again, I was thinking about this before the session. For me, it's in it's in two key ways. I mean, the first is around time spent waiting to hear a decision. So the faster we're able to screen, the faster we're able to get to interview, etcetera, the faster we're able to fill, the less time candidates are spent waiting. And I think so we're already seeing that time saving on the, screening time. We'll hopefully see it on the time to fill as well. And I think, therefore, candidates will hear faster whether they've been successful or not, and I think that's obviously gonna result in an improved experience. The other one is a bit more nuanced, but I think it's probably more important. So previously, we had absolutely no way of guaranteeing that your CV would be reviewed. Now we can. So everybody who applies will have their CV reviewed. And I just think that's absolutely brilliant. If you you know, as as a candidate, as I've been for other roles, there's nothing more disheartening than putting your heart and soul into an application and then not hearing anything or not hearing anything for some time or not even being sure that someone's actually gonna look at your CV and see whether you know, take even a thirty second view on whether you'd be suitable or not. And as I say, we had no way of ensuring that all candidates could be reviewed previously given the numbers, but now we can. And I just think that makes a huge difference to the candidate's experience simply to be able to offer complete parity. We can ensure that everybody gets reviewed, and I think that's a really big deal. Yeah. Perfect. So, yeah, optimize the back office. You actually improve the candidate experience. So how did you we kinda touched on this a bit so we can move through it quickly. But, yeah, how did you manage, this change within your HR team and, you know, looking back on, adopting the AI solution? Any any advice you give to our our attendees today? Yeah. That yeah. You're right. I touched on this earlier, but I think it's worth reiterating that, really, it was about bringing them along the for the journey and bringing them in at the at the earliest stages possible. So given the size of the team, I was in a position to be able to accommodate all of them in the project team, not just, you know, take some. And and although that meant more time from them was taken at the early stages, I knew that would pay dividends in the long run. So they were involved in all of all of our design sessions. They were involved in all of our testing sessions. And what that meant is they had time to feel like their input was gonna be taken on board with how this thing was set up. But, crucially, just to be in it, to use it, to get used to, you know, using the functionality, so that when we went live, everybody in the TA team had already been in and got used to it. And and as I say, the the the dividends were really clear. Training was really easy. We didn't really need to train anybody. They've already been in testing. They knew how the system worked. And as a result, I think user adoption within the TA team has been has been very high. And for me, that was really, really important. And I know, you know, for larger organizations with much larger TA functions, that may not be possible. But, certainly, I would say bring as many people along for the journey as you can. I think it does pay dividends once you go live. Yeah. And I think I think as well, you know, what they we talk a lot about, it's about human and AI collaboration. So the AI is just going to take some tasks from a role. So probably some of those tasks we're just not able to perform because of time and so unlike screening all the candidates to give the actual employee, or in this case, the recruiter, more time to really focus on the higher value activities. So Yeah. Looking back, have there been any sort of unexpected benefits and challenges that emerged either during or after the implementation that you just didn't initially anticipate from the introduction of AI? Yeah. I mean, I think there was one that was unexpected, but it shouldn't have been unexpected. So it's almost a little bit embarrassing to admit this, but I'll share it anyway, and hopefully people can learn from, a few of the mistakes. You know, Workday make it really clear that the quality of your job descriptions is one of the most crucial parts of this. You know? If you don't give the tool good parameters to assess candidates, it's not gonna be able to do a good job. It's all well and good saying that, but until that fact bites, I I don't think, I don't think we'd really understood what that meant. But it was brought home to us shortly after we went live. We had a had a project manager role. So a very, you know, not not a role that's unique to F1. Many, many companies have project managers. We had about 600 applicants, and they were all ranked a and b. And we're looking at it going, well, hang on a minute. This hasn't worked then, has it? You know, that doesn't help us at all. But then what we did is we took time. We looked at the job description. We looked at the criteria that we set. We spoke to the hiring manager, and we adjusted, and we add the necessary added the necessary specificity in order to allow the tool to do its job properly. So we did that, and then delightfully watched the hired score regrade the existing applicants according to the criteria that we had added in. And then we had a good spread of applicants across the board. We had a's, b's, c's, and d's, and about 60 a's. And suddenly, okay. Great. Breathe a sigh of relief. It is working as we as we were hoped. And as I said, that that shouldn't have been, unexpected, but it's not I don't I think until you really see how the tool is grading that you can kinda start to adjust and add in potentially the the level of necessary detail. The other one, I mean, that was unexpected, and I think I mean, you can judge whether this should have been expected or not. Perhaps it should have been. But, again, there's another point around job description. So, the role that we have that that is really unique is that of a timekeeper, whose job is literally to time the cars going around the second. So there aren't many organizations in The UK that employ that role. But, historically, when we've advertised for it, we have asked for good timekeeping experience. You know, a person knows in the context of the job description that that means experience of timing motorsport events. But that's not what the wording says. Right? So we put the role live, and they're getting well ranked candidates who are turning up to work on time. And, you know, because it's it's we haven't given the necessary, context for that criteria. And it simply needed to be just reworded. Right? Good experience of, you know, timing motorsport events. That's all it needed. But it it's something we haven't really considered going into it. And I think, you know, other organizations may have very unique, very specific roles, terminology that makes sense. They understand it. But I think ensuring that, the tool and, of course, your applicants know what that means is really important. Yeah. So let them learn. Yeah. With AI, I can make assumptions on. Brilliant. So just last question before we skip over to, q and a. So for those sort of HR leaders in the audience, with, you know, considering their own AI journey, what what what's the single most important piece of advice you would offer based on Formula One's experience? I mean, I think it's really an extension of the point I made around the talent acquisition team, and that's about bringing your key stakeholders in at the earliest stages possible. So at Customer F1, we have an AI steering committee whose role it is to decide, you know, to review all cases for using AI and make a decision as to whether it's appropriate, whether it's proportionate. Is it gonna, solve the problem that we're encountering? Is it safe to do so? And I took the time at the outset of the project to identify the key people on that steering committee, speak with them separately, explain to them the problem that we were encountering, and kind of, you know, sell them the solution that I thought high school would be. And then brought them along for the journey, made sure that they had time to do their due diligence, that ideas putting this at their feet last minute. And what that meant was that when we got to me pitching HiveScore effectively to the AI steering committee, I had already got the buy in from those key people, and it meant that getting the necessary approval to go live was relatively straightforward, not without its challenges. And there was a lot of time spent as I doing that due diligence both before the purchasing decision and between then and when we went live. But really bringing those key people in at the earliest stages, not trying to keep them at arm's length, not trying to keep them away from what you're doing and kind of only give them the necessary information that they you think they might need to give you the approval, but really bringing them along for the journey. And I I think that, for me, it was a key to our success, and I I strongly suspect it will be a key to many other organizations' success too. Yeah. No. Definitely. Yeah. So get get all the right people and the right teams involved early. So brilliant. So let's let's now, skip across to the q and a and and to all our attendees, you know, you have to upvote because we're gonna go for the the questions with the most votes. And the first one is, basically, kind of about bias. It's obviously a big concern. I don't wanna introduce bias, by using an AI tool. How did how did Customer F1 look at this? And, obviously, I'm assuming it was something that you evaluated and you were very cognizant of. Just, you know, what what was what was your approach to, the concerns about bias with an AI tool? Yeah. I mean, there was, you know, there were long lengthy discussions internally on this topic, that I'll, you know, not go into the detail of. But I think for me, there are some key things that we looked at, and and you already touched on one of them earlier, Richard, which is ensuring that people remain and play a key part in your processes. So, you know, AI is is not making the decisions in isolation, and, indeed, that's what the law requires of us. Right? So it's it was about ensuring that, our talent acquisition team still played the right role in determining whether candidates would progress or not. And one of the things that we looked at and spent some time with our, you know, legal and compliance teams was doing some testing and continuing to do that testing even after we'd gone live, continuing to ensure that we are comfortable with the scores that are being provided. And and for us, we know the the really simple way in which we're doing that is a commitment from the team to review a proportion of the lower ranked candidates. And and we I had some fun discussions with our, legal team around what that proportion would would be. You know, airing on the side of side of caution, they were probably hoping we would re review a large amount. But, actually, of course, the more we review, the more we're gonna eat into that time saving that I was hoping to to to bring in. So there was a bit of a trade off there, but, ultimately, we reached a point where we agreed a sensible figure, we thought, agreed a time frame over which we would expect to see that taper off. So, you know, that proportion reducing. I think that was one of the key discussions for us as we as we considered, how we would how we would manage that, how we would, you know, defend decisions that we would we would take. I think the other the other really interesting point was around whether we allow candidates, the opportunity to opt out, to say, I don't want AI to to review my application. And we started from the position that we would allow candidates to do that. But then the more we thought about it, the more we realized, actually, we can't offer those candidates a comparable grading experience that the AI tool can. So by doing that, we are treating candidates differently and therefore introducing potentially the bias that we are attempting to eliminate. So we took the decision, and time will tell whether it was the right one, to say if you want to apply for role at Customer F1, you need to agree to your, application being reviewed by the tool. And after, there's some long reflection and discussion with the relevant teams. I really do think that is the best way to ensure fairness across the board, to put everybody through the same process. I think it's much harder than to accuse us, hopefully, at the same time will tell, of treating people differently. Yeah. I know. So yeah. I mean, obviously, the AI is not making any decisions, which I think is a key point. And then also, of course, as a as as the as the vendor who who developed this AI functionality, we have a full responsible AI framework and governance process of checks and balances in place to minimize any risk of of bias being introduced. So, next question, which is from Gabriela. It's a very long question. So, Gabriela, forgive me. I'm not gonna read it all out. But it it's linked to the whole thing about how do you get recruiters' trust, with the AI that it's actually, you know, reflecting. It it it's sifting the candidates in in a way that that that that's, sort of aligned with how how F1 would, you know, the the recruiters will look at the candidates. It seems like Gabby is struggling a little bit. I don't know what technology she's using, but maybe just a a little bit about the building up that trust in the tool again. Yeah. I I mean, part of it, which I I I don't know if this helps really, but but for our team, they were desperate for a solution. So, really, that that helped because they simply couldn't review the number of candidates they were getting. So I I know that's not applicable to everyone, but for us, that really helps. I just wanna kind of add that in to reiterate the context. I think we've certainly had higher levels of trust as a result of how difficult things were previously. But I I do think, you know, much like any relationship, there is no substitute for time. And I don't really wanna talk about relationships with AI. It might get a bit weird, but I do think it takes time to build up trust with the tool. And I don't think you can there's any way around that really, other than simply giving your TA team time and kind of accepting that they will look at, and be reviewing more candidates than they possibly need to, you know, shortly after you've gone live. Checking, making sure. But I don't think that's a bad thing, really. I think you you want the team to take the time to get comfortable. And we we always expected to see that, the time the TA team would spend reviewing the lower ranked candidates for all the reasons we've discussed, you know, would reduce over time, but it would take time. And it wouldn't be something that just happened overnight. Yeah. No. Good. Thank you. So the next question is, from Martin where he's asking, why did you choose HiredScore as opposed to some of you know, there are other solutions that are kind that they that do something similar ish, that could be integrated into Workday. Did you did you, you know, did you look at other potential solutions to help you with that problem of managing those huge volume of applicants or, you know, what what what was the process there? Yeah. We would yeah. Some some review of other, solutions was done, but, actually, to be honest, given the level of integration HiredScore was offering, I think it made the decision relatively straightforward. We wanted to keep that user experience both for TA and for hiring managers as close to Workday as possible in order to increase adoption and make sure that's always being used properly. And I didn't see anything from anyone else that was being offered that would, certainly, from my initial expirations, would do do things better. So I think for me, that that level of integration that was on offer was a kind of, yeah, particular selling point. Back to the earlier, you know, my earlier response to Richard's question. We had been had come from a world where everything was disparate. And so I'm always keen to try and bring in solutions that don't take us back there, to keep things talking well to one another. Yeah. No. Make yeah. Makes makes sense. So question from Leo. Does f one use Paradox? Paradox is is a is a company that you work they recently announced we're going to acquire, and they, basically provide the conversational career site, conversational apply, and conversational interview scheduling. So, Alastair, is that salute I know the answer to this, but is that is that a solution that is it is that a solution that you use? Not yet. No. Perhaps we should consider usually. Yeah. That's okay. That's okay. Yeah. And for the all our attendees, we're very excited about this acquisition. It's just a fantastic piece of tech that, will really enhance the candidate experience, but, also, it's gonna take away that nightmare of having to schedule interviews, which is one of the worst things, you know, you have to do in the recruitment process. And it that solution in the last year scheduled, I think, 32,000,000, interviews. So that's one interview being scheduled every second, roughly. So, yeah. So but the answer is no, but maybe that will change. We'll get you back on, Alastair. Yeah. Talk about that. Yeah. Right. Well, I get to see a demo at, at, Rising Media, Alexa. Oh, you get to see lots of demos. Yeah. Okay. Cool. Yeah. And also Asana, which is another AI company that we are in the process of, acquiring, which is very exciting, but I'm sure there'll be lots of lots of, information flowing around that. So interesting question here from Camilla. Were you involved in shaping how the AI model evaluates CVs? For example, by helping define the screening criteria. We we're not involved in how the tool grades, but, you can give and and should give feedback as to whether, as far as I understand it, well, you know, whether you agree with the ranking that the tool has provided. And, again, as I understand it, that's, that feedback is reviewed and adjustments made where necessary. So, you know, where we were seeing things that we don't agree with, there is, I think, options within, and I'm sorry. I know there are options within high score to note that you disagree and change a grade, and it appears differently as a result. And as I say, over time, that that feedback is collected and reviewed to see whether, adjustments should be made to the, assessment framework. But that's the same for everybody. So, you know, all customers have that same functionality, and I've the the feedback is reviewed to get that. You know, it's one it's one solution. We don't have a unique instance for us. The the the power of the tool is in that huge dataset. Right? So I think it makes sense that all feedback is considered and then put any adjustments made accordingly. Yeah. And I think as well, you know, you mentioned it earlier on that you needed to to refine the job descriptions. Right? Because that has that has a big impact on Yeah. That scoring. So so so so you can so you you learn as you go and actually it it just shows that actually your job descriptions are very important in terms of getting that, that screening optimized. So so so yeah. Absolutely. I think just on that point where, you know Yeah. We've made more adjustments to our job descriptions than we have to candidates. Great. So that's that's what we've seen. You know? If there are changes necessary, it's normally been required on our side rather than tools. Exactly. And then the tool uses that uses that information. Right? So you're kinda, like, you're you're fine tuning it as you go. Okay. We've we've reached sort of the forty five minutes, and I think that's how long we said the, the webinar would be. There there are a few more questions in there, but I think we covered the ones that were most let me just see if there's anything that's been really uploaded. No. We've covered all the most popular ones. So apologies to those people, but we didn't manage to get round to your questions. We'll have a look at those and see if we can get back to you. Let me share that and just wrap things up. So please do give us your feedback. There'll be a little survey that pops up, and we, you know, we'd love to hear what you think about the webinar just so that we make sure that webinars in future are, you know, are are focused on what's important to you and and so on. I'd just like to remind everyone that, Workday Rising, is coming up in November in Barcelona. There's so much going on. There are so many announcements. We will have, hopefully, by that time, these two new AI solutions will be a part of the Workday family. They'll you know, it's gonna be it's gonna be fantastic. There's so much to talk about, so much to show you. It's a great way to meet with your peers. So please really seriously consider coming because it's gonna be absolutely brilliant. We also have more of these looking forward with Workday, webinars coming up. We see the next one, on October 7, Fireside Chat with Asda, a very big UK retailer, on their journey with Workday success plans. And then coming up on the, ninth oh my goodness. It's gone too small. I can't see it where the tickets come up. So, something fantastic coming up on the ninth. I'll I'll just say that. And then we do these virtual test drives, hands on sessions, which you can see there, and there's a QR code. And remember, you'll get a recording, sent to you of this webinar so you can always, reference these slides and and click and, scan the QR codes to access more information. So, thank you, Alastair. That was brilliant. Thank you for your insights. You're on the AI journey, and you've had some great results, so far. And I'm sure we'll all be really interested to see, what's coming next and and hopefully hear from you again, in the future. So thank you, Alastair. Thanks for having me. No. You're welcome. And thank you to all of those, those hundreds of people who, joined us, for this session. I hope you all found it useful. Please do give us your feedback. And, I wish you all a fantastic remaining Workday. So thank you very much, and goodbye.