AI-Powered Recruitment for Hospitality

Connecting Hospitality Workers and Employers

I'm a restaurant I'm CEO and co -founder we are a company doing recruiting in the hospitality sector we work vertically in this domain specifically what we do we connect job seekers on one side so workers of this domain like waiters cooks bartenders or restaurant managers with the people on the other side the the employers, like from hotel owners or restaurant owners and so on and so forth.

How we do it? Like on one side for the employers we try to source the candidates for them and simplify their recruiting job so they can actually see only the fit candidates, the potentially fit candidates.

And on the other side we support a sort of career advisor, the workers of this domain to find their next opportunity to create their CV, to create their cover letters and so on and so forth.

Transforming the Recruitment Process with AI

Today I'm talking on how we use AI on our process and how we optimized our process and we changed our process in the past 12 -18 months.

Just to give you a little bit of numbers, so we're talking about 220 ,000 workers of this domain, workers in Italy. so we work only in Italy with a little bit of let's say restaurants abroad but most of the job seekers and professionals are in Italy how it is our

Helping Employers Create Better Job Ads

AI system structured so on one side on the employer side we support the employers on creating the job ad and this has been one of the most difficult thing to do because like supporting them into understanding into letting them think what kind of contract they provide what kind of benefits they provide how to structure the job ad is what actually makes the whole process efficient

because otherwise most of the owners they think something but they don't think it's important to write it down on a job ad and then the job seekers like get confused and don't apply so this is actually the most important part of the

process then we have some validators some simulators for the salaries and we also have a tool to like suggest them how to improve the job ad so measuring all the other job ads of similar positions in similar places so we just say okay you may offer this you may offer that more or you can write this or you can write that on the other side instead okay once the job ad is done

Building Complete Candidate Profiles

we have the job seekers and the applicants so for each one of them we parse the CV the unstructured documents they have so we use AI to create an understanding of their professional profile but then what's actually most most of the times missed in our recruitment process is what is not

contained in the CV so we have recruitment agent like an AI agent and AI assistant which supports the candidate into providing the information that's actually missing from their CV but it's actually contained in the job

ad so for example if you apply to a job and it's requested to have three years as a cook with some responsible let's say activity and you don't have it in the CV or it's not clear from the CV the agent asks you to specify more information about that topic so you can complete the application better and so

they have this sort of interaction with the AI agent which is currently done through whatsapp vocal messages and messages and whatever and then we build all these things and we create a sort of an evaluation for the employer so the employers have these applications with these evaluations, let's say, organized.

From WhatsApp Conversations to Employer Evaluations

So this is a screenshot, like a demo between WhatsApp applications, and it was a bit difficult, so this is a screenshot of a chat that the job seekers have, so they can send vocal messages and text messages.

Now, this is not on WhatsApp because we are currently releasing, and I will be talking a bit more about it later, let's say a migration from WhatsApp to our own in -app system.

And this is what the employers receive, so it's a sort of analysis structure for each single candidate in the same way, in which we specify what are the strengths, what are the weaknesses of that applicant what we faced and struggled or let's say we worked on was to have

Responsible AI and Human Oversight

to be compliant in the ai act framework or anyways in some sort of common sense ai usage and in the recruitment is kind of tricky so we always kept the human informed so the job seeker informed about all the decisions and all the steps of the applications and we all the

people that are not fit for a given job we discard them automatically so we send them an email with the motivation on why we specifically like didn't choose this application this didn't move this application forward and we allow them to say hey I don't agree or something is missing or I'd like to add more details details, and right now we have 0 .05 % of these objections on all the applications, and we have real humans, real recruiters actually managing the whole flow.

Recruitment at Scale

On an average total of 28 ,000, 30 ,000 applications per month with the relevant conversations and interaction with the AI. AI.

We are now publishing around 380 jobs per month and yeah this is just some numbers we have.

The Challenge of Migrating Away from WhatsApp

This is a challenge we're facing right now and one of the current challenges I wanted to bring this as a topic and so WhatsApp is changing their pricing from next month and this is what happens when you are heavily dependent on a provider it's changing the pricing and basically now before we were paying just for the first message we were sending and then the conversation was free so whenever the user answers to you like you can continue the conversation for the next 24 hours now you pay for each single message and you imagine with 30 ,000 conversations per month like the price would increase so much so now we are

migrating everything inside the app and this is a challenge when you move uh these amounts of applications which is not a huge number of course like we're not talking about big data but still like letting the users adopt ai and a technology and a methodology is already hard enough whenever you need to migrate to another tool and platform then it requires a bit of time and so since this

Supporting Adoption of a New In-App Experience

This meetup is on the AI topic, so we're also using AI as internal tools for managing all these, let's say, processes and everything.

Measuring Performance and Improving Continuously

And I just wanted to say that we think, we experience that measurement is key. So whenever you can define some strong KPIs and some clear KPIs and some clear metrics, you have a baseline and then you can continue continuously measure like how your product is behaving in our case like all the application funnel so how many people were dropping off in the conversation steps and how many people were evaluated after the application so what was the experience during the chat

and so on and so forth and now we are releasing these and we are using these tools to actually make the rolling out process like a little bit easier than it used to be maybe one year ago so so yeah this is this is one of the challenges

Why AI Makes Recruitment Faster

that we have on the AI world because you publish an AI based product and then you need to migrate you need to change it and also handling this kind of operations is is tricky so yeah this is this was my brief topic on how AI made

us more effective why because on one of the most important part is that it made us faster we were using a sort of classical recruiting way before so we had real recruiters we still have real recruiters working with us simply they monitor and manage the systems in a different way but now we can shortlist candidates in few hours and this is what actually makes us effective because a person in this domain finds a job in few days and so like the faster you are the better chances you actually have to connect the two sides of this of this of this market so yeah thank you very much