How Will Agentic A.I. Transform Your People Strategy?

Matt Grimshaw00:00:02

The problem with using a large language model like ChatGPT just off the shelf is it doesn't have any context and it can't learn how to get better. Every time you put an inquiry into ChatGPT, it basically starts again.So what we're doing with the agents is taking some of those capabilities that you get with large language models, but putting them to work in the context of your organization, your data, and training it so that the agent can actually get better and more accurate over time. So. So an AI agent.If you've seen the film Despicable Me, I think the best way to think about an agent is like one of those little yellow minions, if you imagine creating a small bit of code essentially that you create to do one job.So an example might be if someone asks you for an employment reference, the agent's job is to go and look up how much they get paid when they started their job title, et cetera, et cetera, and then write an employment reference letter. But I think people are aware of the idea of a Gen AI hallucinating, but maybe it's worth giving a bit of background on what that is.So, large language model.

Timothy R Andrews00:01:14

Today I am delighted to welcome Matt Grimshaw, the founder of Youda who's at the forefront of transforming hospitality with agentic AI for employee experiences. And, and if you're like me, you don't know agentic AI is. That's why we have Matt. Matt, welcome to the show.

Matt Grimshaw00:01:29

Thank you very much.

Timothy R Andrews00:01:30

So tell me, Youda, what is Youda? For everybody listening, where did its name come from?

Matt Grimshaw00:01:37

So Youda is, as you said, an agentic AI platform. I wonder if it's worth just trying to explain what that is before I dump it jumps today. So an AI agent.If you've seen the film Despicable Me, I think the best way to think about an agent is like one of those little yellow minions. So it's, yeah, you're, you're, you're rocking the look for it.So if you imagine creating a small bit of code essentially that you create to do one job.So an example might be if someone asks you for an employment reference, the agent's job is to go and look up how much they get paid when they started their job title, et cetera, et cetera, and then write an employment reference letter. Or you might create an agent that says, when we get a new starter, please ask them for a bank account details and set them up on the payroll.Or you might set up an agent that says, after someone's been working with us for two, two and a half months, send them a quick reminder that they're about to be auto enrolled into the pension scheme and explain what the pay. So you create them to do very, very small jobs and then they sit in an environment with the tools they need to do those jobs around them.And then when they get a notification that someone wants them to do their job, they basically spin up, do the job and go back to sleep. And so what Youda is, is we have what's called an AI agent environment. So the ability to build agents from, from like natural language prompts you.So you don't need a software engineer to build these things, you can just tell the agent what you want it to do.And then that agent environment is connected to an app on team members phones with a newsfeed, group chat and essentially it comes together with a digital assistant so you can interact with the agent and then it's also connected to an HRAS because you need a way of collecting and managing the data that comes out of the the agentic experiences. So that's kind of what it is.Why would that be of any interest is the first thing is you can get rid of a load of admin stuff that frankly no one really wants to do. You know, like all that stuff around return to work checks, renewing visas, change of hours letters, promotions, all the ad.When you employ lots of people you just, there is a big burden of admin and compliance and you can automate all that. The second thing is you can the agents can respond to any of the data or events within the systems.They you can personalize things so you can have different onboarding experiences for people who've worked for you before versus those who haven't or people who working part time versus full time or people are studying outside of work. You can give them a different experience and you can get the agents to respond to events as well.So if you identify that someone has a particular need then an agent can spin up and respond to that.And then the final piece of the jigsaw for us is generating the data that will allow people teams to start to predict with more accuracy predicting things like flight risk like who's going to leave within 90 days, what's causing people to leave within 90 days or predicting mental health needs or training needs needs or those sorts of things. You'll be able to understand what's causing the outcomes within your system and then you can start to test ways of improving it.

Timothy R Andrews00:04:30

So it's basically there's these little, I know little agents within this Whole thing. And then if it's a man triggers one of these to does it and then gradually works it all out and then produces the data.So somebody hands in this, we talked about the 90 days. So somebody leaves within 90 days there'll be some sort of trigger that will be looking at their, their exit interview if they've got one.Those that do what are the results in there?And then that's stored somewhere and then it can collate it all and then within, I don't know, a few months you'll be able to say, well actually the majority of our leaders are leaving because this one bottleneck, whether it's a manager or a pay issue or whatever.

Matt Grimshaw00:05:08

Yeah. So the idea is that with the agents you can create a much richer data picture of how people, what's going on for people at work.So imagine an onboarding experience where you initially get a, from, from one of an agents in the app. Say hey, welcome to the business, like tells you the story of the business, you know, introduces you to your team, all those sorts of great stuff.Also does all your admin for you.So you know, we'll get your bank, we'll do a digital contract, we'll get your bank account details, we'll do the tax declaration, then we'll make sure you get allocated the right compliance training and nudge you through that. But you can also get feedback.So like at the end of your first day you can have an agent that spins up and when you clock out on the first day it'll say, hey, how was your first day? Maybe one to 10. But then because the agents use the large language models, we can do what's called natural language processing.We can ask an open question if that makes sense so you can actually get to some insight on what's driving people's satisfaction with experiences. You can have, you know, day one feedback and maybe you're asking again at the end of week one and week two and so on and so forth.And we can also be nudging the manager for like checking conversations through that 90 days and we can give the manager an agent so if they record a voice note of that checking conversation that gets filed onto the profile. So you take that data as well.And then we're also getting the data that we can pull out of like rotor systems and lms and so we know when what shift pattern people are working and maybe we're asking them to rate those shifts. So you've got that data as well.And as you build up that, that complex event based data structure you're then able to apply what's called causal inference to understand what are the drivers. And the important thing is, in my view, often the situational factors will be a better predictor than anything you know about the individual.So I suspect you will find things like whether you give people two days off in a row is a good. Or if you, if someone has to work a double or what's the stability of the team in which that person started working?You know, if they're joining a team with high turnover, relatively low tenure, you'd expect that to be a harder environment for someone to join than if there's stability around them. But we can also look at the personal factors. You know, does it make a difference if someone doesn't share a first language with someone on the team?Or does it make a difference if they rate three of their first five shifts as one out of ten? Those sorts of things will all go into the model as well. And, and what causal inference allows you to do is to then isolate those factors.So we'll be. So that you can build up this really insightful view of like how onboarding's working.Maybe is there a segment of your employee base that you're doing a great job for and some and another that you're not. You know, maybe onboarding is a lot more successful for full time team members than part time, for instance.Or is there a, as you said, is there a particular moment in the journey like do people get to week six and if they don't get pushed onto busier shifts, they get bored and leave? Maybe. Or is it, you know, manager behavior or something else.But for people teams at the moment, I just don't think they have the type of data and insight that allows you to go, right, great. This is the thing we can focus on in order to actually improve things and drive a business outcome.There's no, they just don't have the precision of insight. You need to be able to prioritize stuff.

Timothy R Andrews00:08:16

Those tends to start from the unconscious bias that might go on with people in terms of. Because you've got real raw data.One of the questions I've got actually, because it immediately springs to mind, you know, I've worked for a very risk averse company and GDPR pops into my head because there's a heck of a lot of data and I've got kind of guess I've got two questions. One is the general data of that. But secondly, does that information go to.If you've got it for a whole employee deck, let's Say would the managers have access to the individuals feedback and responses or was it, would it be collective or does it depend on how it's set up? I realize there's two questions there. So one is GDPR generally and then one is a sort of confidentiality element to it.

Matt Grimshaw00:08:56

Yeah.So from, from a GDPR perspective I think you, obviously there's, there's rules around how you collect data and process data and those sorts of things.As an employer you have a right to collect data on your employees and use that to, so there's not, there's not a legal constraint around doing this sort of thing. I think there is an interesting cultural point if that makes sense.Like I think people are aware, particularly gen, like different generations actually seem to be more aware of like sharing their data and what it's being used for. And so from a user experience perspective, what we try and do is signal like why we are asking for certain things.And I think there's also this sense of culturally you want to be an organization where people share their ideas and share their feedback because they think is going to be used in the right way. Does that make sense?And I think you can, you can, I think to be candid, I think the regulations will need to catch up with what's now possible from a technological technology perspective. But organizations are also going to need to be quite considered about how they use that data.So what we're trying to enable people to do is to improve employee experiences in a way that also creates value for the business. So like we're looking for those sort of win win scenarios rather than using data to try and like trick people or track.Does that, does that make sense? Like, and I think that that cultural piece is really important. And then yeah, you're absolutely right.Within the model that's, you know, the data modelling, you know, we can set that permissions protocol up so that you know, people, certain, you know, categories of data are only accessible to certain people. I think the big point is most users are happy to share and interact with you if you are providing something useful to them, does that make sense?And like you know, simple Youda. One of the good things about Youda is we just, we just solve a lot of real problems if that makes sense.Like if you're a team member, you can go onto Youda and say, you know, what's the recipe for this month's special? Or what's our parental leave policy? Or I'm running late, what should I do? Or like how do I process a refund on the till?And the agent will find the answer for you. Or if you need stuff like an employment reference is a classic one, you know, maybe you need an employment reference for a new tenancy.Typically, like, I know you've. You've worked in people. Seems that's usually like a request that goes to a manager that then goes to a people team.And it's like, it's never a priority for the people team because they didn't see it coming. And it's not like business critical.But if you're waiting to get a tenancy, like, it kind of is important that you get this sorted and you're not stressed out about it.So, you know, usually on a Friday afternoon, someone in the people team will sit down and pull the word template and then look up the information on the payroll or the HR and fill it in and send it back. And maybe it takes a week or two, you know, whereas on a.With an agent, you can just go on and say, I need an employee point reference, and it takes about three seconds and it'll send it back to you. So I think our focus is on how do we re.How do we give time back to frontline teams, how do we give time back to people teams, and how do we create an experience for people that just feels much more relevant and personal and responsive? You know, like in the industry, you've got people joining the industry who've grown up with a certain expectation around how tech works.You know, like, if I've.If I'm 23 and I've grown up with an iPhone and Netflix and Amazon and all the rest of it, and then my first day and with a hospitality company, I'm filling in paper forms and, like writing my address out for the fourth time. And so it just feels really anachronistic. So that's the.That's the sort of thing we're trying to enable people teams to do, is to give people an experience that feels a bit more like their consumer experience.

Timothy R Andrews00:12:24

Feels like it can move away from some of the old school, just all this paperwork that just needs to be doing. I think anybody that works with me knows my view on admin. It's a necessary evil, but it is an evil.Anything that can make it go away or make it easier is a massive tick in my book.And also, I think with HR as well, with the people teams, there's always quite a lot of administration just naturally from the job because you need to have everything recorded. It feels like some of this stops a lot of that reputation competition, and that then we might be able to focus on the people element a lot more.

Matt Grimshaw00:12:59

Yeah, yeah, I think you're absolutely right.Like when you employ hundreds or thousands of people, there is an admin burden that like if you haven't worked in an HR team before, like you're probably a bit blind to, you know, like most that.If I think about like a typical thousand person hospitality business, it will get, roughly speaking, four or five hundred emails into a people team inbox every month with you know, like just requests. Someone has to pick all that stuff up.Someone has to make sure that every new starter, you know, does a right to work check, tax declaration, get them onto payroll, does their compliance training. Someone has to check that everyone who's on a visa is renewing it.And like people at the moment that's like manually chasing people to try and get them to renew stuff like return to work checks after people have been sick, like all of that stuff. It's not like you can't, you can ignore it, you have to do it.But if you do it, if it's a person doing that job, it's, it's not a great job to be honest, because it's a bit soul destroying chasing a manager for the 15th time to do stuff.And it's expensive, you know, like you're now paying 15, 20 pounds an hour for people to move data between systems or to fill in a form, all the rest of it.Candidly, like we think that you as agents can probably do about 80, 85% of the tasks that would normally fall on an HR administrator or frontline manager. So you can like, you can get rid of so much stuff.And in hospitality the magic of it is in like producing a great product, like the craft of that and in human connection and service and being. And like everything else I think you can get, you should try and get rid of so that you got more time for the stuff that actually matters.

Timothy R Andrews00:14:30

Believe in that. And I particularly like how you talked about the recipe. People can look up a recipe, the special of the month or whatever.That is such a good tool to have.And I'm assuming it also works for example with like employees handbooks, you could get that uploaded where you know, there's various companies I work for and I'm sure that you also, some of the people you've worked with, it's like tombs, you know, it's like, I mean they call it the work bible for a reason. They might as well call it the work War and Peace, right?And there's just no way like you, you could but 83 pages or 94 pages of a staff document and then to remember can be quite difficult. Whereas I guess if you want to know, black tight, 15 denier acceptable, that will give you the answer.

Matt Grimshaw00:15:12

Exactly, exactly. And your point is exactly right. Like, quite a lot of effort goes into producing this content.But in the real world, let's be honest, like if you're working and you're busy, like, are you going to go and weed through a manual to look at it? No, because you've got a job to do and so it never gets used. Whereas with Yuda, you can put in like you say the employee handbook.You can also put in if you've got like, you know, manuals for the equipment you use.Like, you know, what to do if there's a flashing light on the grill or how to process a refund on the, on the till or all of those, what to do if the WI fi is broken or you know, all of that, who to call if the dishwasher breaks. You know, like all that routine day to day stuff.If you've got that documented somewhere or if you've got training material on, you know, how to, how to on shift coaching or, you know, all of that sort of stuff, you can make it available so that if a team member asks a question that, that relates to, they actually find what they need when they need it.And the other nice little thing at the moment is if you ask the question in a different language, it will translate the content back into that language. So if you say not that I can, you know, like, how do I process a refund on the till? In French? It'll, it'll return the answer in French.So it's all about, in my opinion, trying to personalize the experience, trying to make it feel really responsive and getting people what they need when they need it with as little hassle as possible. That's, yeah, that's, that's really what we're going after.

Timothy R Andrews00:16:29

Is the app quite self contained or can you connect it to other things like ATS or other sort of systems like Opera or whatever?

Matt Grimshaw00:16:39

Yeah, so I think the more systems you integrate into it, the more value you get. So the obvious, the most obvious integration with us is the rotor.So if you have a good integration with a rotor one that means you can send, do simple things like only send people messages when they're on shift so you're not disturbing them when they're off shift. Imagine you're, you're a people team, you're turning up at site, you can go into the agent, say who's on shift today?And it will read the rota, give you the profiles of people who are actually, you know, you're expecting to meet that day and their name and all that sort of thing. So the router is a real key one.And also because people's questions tend to relate to the rotor, you know, like, when's my next shift, how many days holiday have I got left? All of those sorts of things.We usually also integrate, as you say, into an ATS to, like, take a payload of the information that comes through the recruitment process and pick up from that. And then other obvious ones, I guess, are like, LMS systems so that you can allocate people to the right courses and those sorts of things.And then more recently, we're looking a bit outside that. The. One of the key, just from a personal point of view I'm quite keen to do, is customer feedback.Like, it as a sort of irritates me a little bit that in some organizations, you know, if a customer left some feedback on Jane, Jane's probably the last person that's going to hear about it. Does that make sense?Like, it'll go into the market, teams even, but so, you know, when customers leave feedback for an individual or for a team, how do we get that back to them as quickly as possible so that. So that they get that. That feedback loop? And the other one is, is people want to know about sales and stock and things like that.So, yeah, the more integrations, the more you can get the agents to do. Yeah, it's.I think we see ourselves sort of sitting on top of a lot of your existing tech and pulling on the data for that and where possible, picking up some of the functionality to make things feel more seamless.

Timothy R Andrews00:18:24

What objections are you finding from people within hospitality? So if I'm listening to this, and this is great, but I'm not too sure what kind of questions are you asked?

Matt Grimshaw00:18:33

I think the real challenge is just what we're doing is like, is brand new, like, agentic AI is, you know, months old. And I think most people have an understandable, like, nervousness about new technology.You know, like, let's be honest, I suspect in hospitality, people have been burnt a bit in the past, you know, like they've been promised stuff and it hasn't delivered. So I think there's a. There's like a polite. This sounds really interesting.And some people are, like, adventurous and want to jump, be the first to jump in. And some are like, come back in six months. And, you know, when You've got so, so I think there's that, just that general nervousness about it.I think also AI is, I think for most people in the people space, everyone's woken up. This is too big to ignore. Like it's not going away, it's not a fad.The potential impact of this is so significant that you like you could, it will be untenable to not be doing this in 12, 18 months time. But there is a like a black box element of AI, like it doesn't work like software.It has and understanding how to utilize it effectively is like a bit like it's out of people's past experience. You know, if you're a people practitioner, like you know, it's just a new field, if that, if that makes sense.So I think that's the, that's the major thing is trying to explain to people how it works and what it's good at and what it's not good at.And I think finding people with the confidence or giving people the confidence to try something new I think is the biggest hurdle for us at the moment.

Timothy R Andrews00:20:06

I find hospitality quite an interesting space when it comes to technology because I guess it's like everything in our industry, you know, we've got the whole kind of people that want to improve salaries and there's those that still dinging on to you know, 90 hours a week and minimum wage and all of that like. And so applied technologies are a bit similar in that we talk about how we're a fast moving industry, that we're like cutting edge.But there's a lot that doesn't that resist and hold on to the old way when we know the old way doesn't work. Just, you know, 2019 we had a bit of a clearing out of the decks, you know, or 2020 rather. And things have moved on quite rapidly.And there are parts in the industry where technology is really, really important. You know, for example, we're running loan star. What roles can be replaced by technology?That's not about replacing the people that are in there, it's about, about, well, if we can't get the people, what can we do about it? And this is a prime example of how certain gaps can be filled. And I'm all for it.I think anything that can make somebody's life better and if the employee can get a better experience by knowing what's expected of them without having to wait for two days for an email because the managers, that's not a priority to answer what you should be wearing right now kind of Thing because they're dealing with disciplinaries or whatever. I'm not saying that's the right attitude to have, but that is reality.Then something like that, that can make it lazy and it will cut down on people's negative experience when they turn up in, you know, tender tights when they shouldn't done or whatever it is. I do have a question though, because it relates to AI and excuse my ignorance, but obviously AI can hallucinate sometimes.Is there a possibility that this might occur within your app?

Matt Grimshaw00:21:49

Yeah. So it's probably just worth trying to explain what hallucinate. If.So, I think people are aware of the idea of Gen AI hallucinating, but maybe it's worth giving a bit of background on what that is. So large language models are generative AI models that are essentially prediction engines.So something like ChatGPT is basically predicting the next token in the sentence. So if I say to you like the cat in the, you will finish? Yeah, you're as good as ChatGPT. Right. It literally, it's like predicting the next thing.And what's happened is to create these things we basically oversimplify.It's like taken the Internet, put it through a supercomputer and said predict the next word and every time it gets it right, you give it the computer equivalent of a cookie and every time it gets it wrong, you get it to do it again.And now it's got to the point where these things are phenomenally powerful and they appear to be able to do things that frankly we didn't think that they would be able to do. Now when people talk about hallucination, it's when the large language model will essentially create some copy that's factually inaccurate.Now the large language model has no concept of reality.If that makes it doesn't know what the difference between a fact and a non fact, it's just pattern matching the language so it has the ability to create stuff that is not true if that. That's what we commonly take to the challenge, if you like, is that's actually the feature of generative AI.So to make generative AI useful you need it to create stuff. That's the whole point of the technology, is that it's creative.So it's the challenge of how do you take a generative model and put it to work in the context of your organization. And that's really what we're doing with UDA is trying to think of an analogy.If you use ChatGPT, it's a bit like having a really, really Clever intern, right? You've just got an intern out. Like they will always tell you they can do stuff. They'll produce copy really, really quickly.And most of the time it's really, it's, it's good enough, you know, like you can use it. You probably wouldn't use it for like the final draft of your board pack, but like for a first draft or for some ideas or like, it's really useful.The problem with using a large language model like ChatGPT just off the shelf is it it doesn't have any context and it can't learn how to get better. Does that make sense? So like, every time you put an inquiry into ChatGPT, it basically starts again.So what we're doing with the agents is basically taking some of those capabilities that you get with large language models, but putting them to work in the context of your organ, your data, and training it so that the agent can actually get better and more accurate over time. So take, you know, our example about looking up a recipe.What happens is you type into the bot, you know, what's the recipe for, you know, a vegan burger. The agent will then turn that inquiry into basically a set of shapes, like a vector.It will go and look at the knowledge library to find what matches that, and then it pushes the answer from the knowledge library back through a large language model in order to create the text. That's an answer. So the large language model is generating. Does that make sense? It's like that. It's the genius of the thing.But what you're trying to make it do is generate copy that is tethered to the information that you've got in your knowledge library. So it's not just making it up from nowhere. Does that make sense?It knows that these are the ingredients and the steps for your vegan burger, rather than just a general vegan burger. That would work in the abstract. So it's about really how you take this stuff and make it useful within the context of organizations.And that's why, in my opinion, agentic AI is going to be so transformative. Because the problem at the moment isn't that the models aren't good enough, it's that you can't make them work in the context of your organization.

Timothy R Andrews00:25:29

So how I think what's important for one of my listeners, and you're thinking, okay, this sounds wonderful, this is exactly what you need. Now, not every tool will fit every business.So what do you think are the maybe two or three questions that people should be answering before they come to you to say this might be an.

Matt Grimshaw00:25:44

Effective tool for them, look like really happy to talk to people whenever they're interested, like I'm just there. But I think the big constraints that people will have is actually making the new technology work with the old technology. Does that make sense?So everything that you've bought that was built before AI may, may cause you challenges. The thing that.So my view on this is within the next 18 months, 24 months, the impact of AI on productivity and employee experience will be so transformative that you can't ignore it. You know, imagine you're working for a fairly large organization.In two years time, someone's going to turn around to you go, well everyone else is operating their people teams with 25% fewer heads. Their turnovers drop from this, from this. Employee satisfaction's go from here to here. Why have we still got, why, why have we not done this?And the challenge won't be putting the new AI in so much as making it work with your existing technology.And you know, you talked about the integrations and like if you've got applications within your stack that don't have a good API and won't share information with you, really difficult to make AI work properly with that. And it's very difficult to make AI work on a legacy data architecture. You need something that's designed for, for AI.So if I was in a people team right now, my genuine advice to try and get on this as early as possible. Because the AI is not, like I said before, it's not like software. Like software, you program it and then it just does what you programmed it to do.And if you're like a purchaser, it's a bit like buying a new car with software. Like if you buy a new pole system for instance, you're going to get 95% of the value of that system straight away. You just drive it.AI is much more like training an athlete than it is buying a car.You have to train it and teach it with your data and user experience and then it gets faster and faster and better and better and you start to pull away from everyone else.So my advice would be, I think, look at it as early as possible and I think you need to be really conscious of what you've got in your existing stack and the challenges that that might cause you further down the road. Like, you know, if you've got a rotor application that won't play nicely actually that's a sort of 12 month project to replace that.So, so that's the, that's the piece that you. That I'd be really, really aware of.And then when you actually get into it, my advice to people is always start with the stuff that gives people time back.The best way to cheer everyone up on improved motivation and engagement in an organization is not to do anything new per se, is to get rid of the things they hate and they don't want to do.And if you can find, if you can find admin or tasks that happen fairly frequently that no one likes doing and you can automate them, you can make an impact quite quickly.And as a people team, you then start to get the time and headspace you need to then think about, okay, cool, what's the, what's the stuff that we want to focus on that actually really moves us forward and makes a. Makes a difference to the business? So, yeah, that's. That'd be. I think the biggest thing is you can't be an ostrich on it. It's just too big.It's too big to ignore.

Timothy R Andrews00:28:46

People listening to this. Some of them are going, what? And it's gonna, they're gonna have to listen to the episode again so they can get some more points.But also if they want to speak to you directly, how, how's the best way that they can contact you?

Matt Grimshaw00:28:57

Any. I. I like Youda.Co is the website I'm on LinkedIn and those sorts of things.Like, and like, I don't know if you can say this with it not appearing like in not genuine, but I'm, I'm like, I think I'm a reasonably normal, like, I'm like really happy to just have a chat and I won't try and, you know, sell you something at first. Like, I think I'm a pretty reasonable person and reasonably friendly and just happy to help. So hopefully.I don't know how you say I'm approachable without making it sound like you're definitely not approachable. But yeah, just get in touch.

Timothy R Andrews00:29:27

I'm very happy to have a chat for you, Matt. Everyone that's met Matt talks about how approachable he is, how genuine he is and how lovely he is.And having spoken to him before here, before the episode today, I can also vouch for that. So please do drop him a line. We'll put links down on the episode so that you can contact him directly.Matt, thank you very much for coming onto the show.

Matt Grimshaw00:29:47

My pleasure.

Timothy R Andrews00:29:48

Great.Speaking to you is clearly something that's not going to go away and something we all need to don't think about if we haven't already there much to think about.

Joe McDonnell00:29:56

A huge thank you to our brand partners, Graphic Kitchen and Leisure Jobs for their continued support of Talking Hospitality. Graphic Kitchen bring creative storytelling to life, helping hospitality brands stand out in a crowded market.Leisure Jobs connects top talent with best opportunities in the industry, making it the go to platform for hospitality careers. We're proud to have them both on board.