Transcript has been slightly edited for continuity.

Matt Alder (00:00):

Support for this podcast is provided by Paradox, the conversational AI company that's transformed the hiring process for global TA teams like General Motors, Nestle, and McDonald's to get recruiting work done faster. What if recruiting and hiring was as simple as this? Yes. This the conversation I'm having with you right now with Paradox, it is they leverage conversational AI to seamlessly automate time consuming recruiting tasks like applicant screening, interview scheduling, and onboarding via chat conversations right on the candidate's phone or laptop. So recruiters can spend more time with people, not Software. Paradox has helped global employers save countless hours and millions in recruiting costs simply by making hiring simple and conversational Visit Paradox AI to learn how paradox can work for you. That's paradox.ai.

Matt Alder (01:03):

There's been more of scientific discovery, more of technical advancement and material progress in your lifetime and mind than at all the ages of history.

Matt Alder (01:17):

Hi there, this is Matt Alder. Welcome to episode 576 of the Recruiting Future Podcast. It's been a year since generative AI burst onto the scene and took over the entire TA conversation for 2023. Some of the predictions made back then about its immediate impact on the world of work. Were a little bit out there even for something that clearly has so much disruptive potential. So one year on where have we got to, what are the genuine use cases? What still hype and how will AI actually transform talent acquisition over the next few years? My guest this week, Adam Godson, president and Chief product Officer at Paradox and Yale Floreal, VP of product at Paradox, are the perfect people to answer these questions. Hi Adam. Hi Al. Welcome to the podcast. An absolute pleasure to have both of you on the show. Please, could you introduce yourselves and tell us what you do?

Yael Florenthal (02:20):

Yeah, with pleasure. So, hi everyone. My name is Yael Florenthal. I'm a VP of product at Paradox. I am located in Tela Aviv office. Producting stuff, exciting stuff. A lot of focus recently about generative ai, which we'll talk about soon.

Adam Godson (02:39):

Yeah, great to be with you again, Matt. I'm Adam Godson, I'm president and chief product officer at Paradox. My goal is to push boundaries in talent acquisition technology and then make all that happen.

Matt Alder (02:49):

Fantastic stuff. Now you and me, Adam, we last spoke in March about generative AI because there's not been that much else to talk about this year other than generative AI when it comes to talent acquisition. My first question is obviously the pace of change is very, very, very, very fast here. What's changed since March? How has it evolved and how has the way that you are using generative AI in practice evolved as well?

Adam Godson (03:14):

Yeah, I think it's interesting. I think the overall biggest story that I would say is that there've been slow gains, but not breakthroughs in how it's changed since March where I think companies have started to convert a little bit of the potential energy with that, which everyone sees into kinetic energy of getting some things done. But I don't think there's a use case I can point to that says there's been a giant breakthrough in talent acquisition where we no longer have to do this thing or there's this giant push and breakthrough in this other way. I think we're starting to see some pushes forward, some interesting co-pilot models, some interesting conversational ai. We'll talk about that as we go forward. I think we're seeing some interesting tool sets, but I think a lot of it is still very early days where it's left to the swivel chair integrator, the person to use three or four different tools to get stuff done. Not really built into our systems yet, but I think some of the potential energy itself even it's getting clearer about what will the use cases be and how will we use this? What are some of the challenges? So it's all getting clearer, but I think it's in some ways maybe been a little slower than people might've expected it to be.

Matt Alder (04:26):

Yeah, I suppose after that kind of initial, I can't even think almost hysteria when this launched. I suppose before we get into any more detail, it's probably worth just getting some definitions down here in terms of what's the difference between generative ai. Paradox talks a lot about conversational AI and there are other types of AI as well. Talk us through all of them and how they work.

Yael Florenthal (04:51):

So basically both generative AI and conversational ai, they both stem from the same umbrella of artificial intelligence, but they serve different purposes. So generative AI is all about creating new content, can create text, can create images, even code for example. You can ask for it to generate a job advertisement for you and you can do it from scratch, just simply understanding language and the worldwide web and create that job advertisement for you. Conversational ai, however, is designed for human interaction. So a very common example is your typical AI chatbot on a website where it's programmed to understand human queries and then respond in the way that actually meet that criteria and is based on an existing database. So while they're both under artificial intelligence, the purposes are different for each one.

Matt Alder (05:50):

What about things like data? Because people often talk about AI and data and all that kind of stuff as well. Where does that fit in

Yael Florenthal (05:57):

With artificial intelligence you were asking? So with generative ai, it is when you ask for it to generate new content for you, it is based on an existing set of data. It might be some chat g pt, which is based on a very wide range of data and thus can create very exceptional and very creative answers. You can also host the data yourself and run the generative AI on your own data. So basically it all comes down to what are you looking to achieve and what is the task that you want to complete. And based on that you'll carve out the data you want to inject the generative ai.

Matt Alder (06:44):

And I suppose that leads on to my next question because we tend to sort of talk about generative AI as a kind of a big term and this is what's going to revolutionize talent acquisition, what parts of it are the best fit for TA and what bits aren't actually that useful or that useful at the moment?

Yael Florenthal (07:00):

So one example I can think about, that's probably what Adam's thinking about is well is it really excels at automating and streamlining very repetitive tasks such as creating job descriptions or I don't know, sorting through resumes or labeling candidates or conversations or data. So this doesn't only save a lot of time, but it also ensures some sort of consistency can potentially reduce unconscious bias at least in the early stage of recording. So that's one task for sure it's really good at.

Matt Alder (07:40):

And is there anything that isn't useful that people are maybe focusing on the wrong thing when they're, because I know lots of people are experimenting with it. I had a podcast interview yesterday with their head of TA and their recruitment marketing team and they were doing all kinds of experimentation with different types of generative ai. Is there people going off in the wrong direction? Are there things they shouldn't be focusing on?

Yael Florenthal (08:00):

I think it's really exciting this technology and there has been a lot of hype and maybe still is and it can solve a lot of stuff and it could really help us with those routine tasks. However, I don't think, I mean I know it can't really fully grasp complexities of human interactions or human emotions or interpersonal dynamics. There's probably a lot of startups there that are trying to solve it, but it's not really there yet. So if we'll take an interview for example, and you have a candidate that maybe shares an example about a conflict they had in their previous job, the AI can maybe understand the sequence of events and it can outline it, but it can't really grasp the emotional aspect of it. It can't really learn what we can learn when we see a person shas about a conflict.

Matt Alder (08:59):

That makes a lot of sense. So how is AI helping your clients right now? What kind of recruiting challenges are you solving with the AI that you are using? Is there a particular type of company that you are helping the most? How's it? How's it looking right now?

Adam Godson (09:15):

Yeah, I think we talked some months ago. I think we focused on making a generative conversational AI experience and we wanted to focus on that part to how do we make Olivia who's our conversational assistant have a great interactive two-way conversation. And so I think the conversation quality is the part where we've raised the bar significantly this year and working with our teams to understand what are the guardrails and the bar for quality in this industry has to be very high. Someone can't ask the questions, what are the benefits for this role? And you get them wrong, we've got to be right. And so how to reduce errors and hallucinations, how to be sure that we get the right information based on that user because the potential here is about one-to-one personalization to be able to personalize every conversation to the individual having it and the company they're having it with. But there's a lot challenge to making that happen. And so for us it is improvement in all the metrics around conversational quality. So we get more people to say thank you, we get better completion rates, we get more questions asked for conversation, we get better explicit ratings of those conversations. We get less confusion in conversations and they all overall just feel warmer and better to objectively have those questions get answered in a recruiting process and have that work get done.

Matt Alder (10:36):

I mean in terms of type of companies, are there particular areas of industry or types of hiring where the adoption's quicker than others?

Adam Godson (10:44):

I think we've mostly seen companies that care a lot about their employer brand. And so sometimes that's consumer brand companies, folks that have external product brands and folks that are willing to push some boundaries and are oftentimes using AI in other parts of their business or have groups that are using ai. They send us lots of long questionnaires about AI safety and all those things as you can imagine. But it's people that are willing to push boundaries and maybe have a little experience with that. And there are many other companies that are willing to let other companies go first, find where the boundaries are in the world and then they'll go second and that's fine too. It takes all types.

Matt Alder (11:22):

So difficult questions now. I'm going to split this question into two because I'm kind of really interested to differentiate. So I know it's obviously it's impossible to predict what's going to happen. And we've talked about there's been no kind of big breakthrough since March by the time this goes live in a week or SO'S time the world, we'll see.

(11:41):

World may have changed. But with that caveat, how do you think things are going to develop? I mean, first of all, in the medium term, what do you think is going to happen over the next two to three years with all of

Adam Godson (11:52):

This? So I think what ultimately has to happen is process re-engineering of all of our talent acquisition processes. And so today what we're doing is we are using generative AI in the current processes. And so figuring out how they can help certain points in those processes there. There's a copilot model, there's a toolbox model, there's conversational agents, there's lots of ways to do those things, but it's all based on the frameworks we've had for 50 years of how we do talent acquisition. And so I think what really has to change in the next step is a re-engineering of how people think about the recruitment process and how the entire process will change. And I think that starts to separate the types of work into transactional work and emotional work. And I use the word emotional intentionally there that it really is the type of work that requires human depth.

(12:52):

And I mentioned it earlier about interviewing someone and understanding their story about a conflict. And I also sometimes talk about the act of a recruiter of convincing someone to join that is emotional work that technology cannot do. It cannot convince you to leave your job, move across the country, interrupt your career for something and join you at their cause because there's no cause. They're not there, they're not real. And so that emotional work will have to be done by a person. And so that process, that re-engineering to separate that emotional work that humans need to do versus the transactional work that could be automated.

Matt Alder (13:28):

I want to come back and talk about that in terms of the implications for recruiters and careers and all that sort of stuff. Before you though, super impossible question, where do you think we're going five years down the track? I know that there was a lot of speculation recently that OpenAI might have invented artificial general intelligence or something incredibly, incredibly scary. Where do you think we go in five years time with this?

Adam Godson (13:51):

Yeah, I think the recruiting process in five years looks completely different than it does today. I think the way that people are assessed for roles with, they apply for roles. Another good example is actually the job seekers in many ways are ahead of companies at this. So today we've got a dynamic where job seekers are using AI to write their resume or their cv. I've seen estimates as high as 60 to 70% of cvs are now being written with AI tools. And on the other side we've got companies using AI tools to read them. And so we've got, there eventually is a breakdown that starts to happen around how do we even assess who this person is at scale and new methods may be needed to do that. And so I think in five years the talent acquisition process is looks entirely unlike what it does today and how we think about assessing people for jobs, how they go about raising their hand to jobs. And ultimately I think there should be celebration. I don't think there's anyone that looks at today's processes and says, wow, that's an amazing process, just is how I would design it. And that's where I think we've got a responsibility and an opportunity as an industry. We actually do get to think about how we start to design this thing as we would have it and start to make that happen. And that's an incredibly exciting time.

Matt Alder (15:10):

I think you're right. I think if you transported someone in a time machine from 30 years ago and asked them to apply for a job, they would recognize so much of the process, resume, cover letter, a face-to-face interview, all that kind of stuff, which shows how far we haven't come. And I'm really interested as to when that point of lots of AI is talking to each other and why are we doing this anymore? We need to reinvent things comes. I think that's really interesting. I suppose combining all that together, what does that, lots of people listening will be thinking about what their future career might look like in talent acquisition as things are going to change like this. What does this mean for recruiters? What do you think their role is going to be? And I suppose more importantly, what kind of skills are going to be needed in two years time, three your time, five years time, however long it is?

Adam Godson (16:01):

Yeah, I think there will be a bifurcation of the skillset and what people want to do. And I think today we conflate a lot of what people consider recruiting work as not that value added. And there's a lot of clicking work, there's not a lot of recruiting going on. It is a lot of moving people in systems and administrative work and clicking through the at s where a real recruiting work is about convincing people to join. It's emotional. It is about how do I convince you to come to my company? How do I be sure that you're the right fit? And I think we can automate a lot of the transactional conversations now. That's one of the things that will change with AI is some of the things like a job intake conversation or a screening conversation. Those things could get automated. And so I think from a skill perspective, there's going to be a choice where people decide they have high emotional intelligence, they love talking to people, they want to convince people to join every conversation of the day, and they will absolutely love that. And those are the recruiters today that really hate the system stuff. That stuff all just gets in the way of talking to people. That's what they love. And then there'll be people that focus more on the systems aspect. And so I think you'll see some divide there and you'll see a lot less transactional work.

Matt Alder (17:23):

You mentioned earlier about people going first and people wanting to be second to see what happens with implementing these kind of things. What would your advice be to heads of talent acquisition who are looking at how they integrate AI into their strategy moving forward? On the one hand, what should they be cautious about? What should they be looking out for? But then on the other hand, what do they need to do to make sure they stay ahead of the curve?

Yael Florenthal (17:50):

I can take that. So I think I know that now more than ever, AI tools has become much more user-friendly and accessible than ever. So first of all, I advise anyone who hasn't done so to go to cloud.ai or to chat j PT and just start experimenting and start writing prompts, you really don't need much to start writing prompts and asking it to perform tasks for you. There's a lot of magic to this combination of words, Geneve ai as if again, it can solve all of your problems. It is a very small technology. It's really good if, for example, you want to customize your email, that's one thing. You can do it easily today within a matter of 10 seconds, but it's up to you. So if you're going to ask it to write a romantic poem for your 15 years anniversary and decide what you should get your partner, that's very risky. So it's up to you. You need to lay your guards in advance and decide how far you are going to take it and create constant feedback loop and make sure it's working for you and you are ahead of the game. So pick your poison or pick your problems to be solved wisely is what I would suggest.

Matt Alder (19:17):

So final question. We talked about the medium term, we talked about the long term. We've talked about appointments I think is very clear that the talent acquisition is going to have to change. How does this journey start? What happens in 2024? What do you think? What progress do you think we're likely to make in the next 12 months if we were having this conversation again this time next year, what would we be, how would we review the year?

Adam Godson (19:43):

Yeah, that's great and I hope to have this conversation next year. Let's get on the books. Matt. I think 2024 is going to continue to be a year of experimentation of people understanding in a certain part of an existing process, how can I get some gains typically in a toolbox kind of a method? How do I solve a single problem in a simple way for part of this? And that's actually a great way to start. For example, one of the things we see our clients start with is using AI for interview scheduling, rescheduling, even the complex stuff. There's oftentimes a human person or group of people and frankly no one loves it. And so finding some discreet task to really automate and use AI to do that and do that well and get those games and build confidence. And we typically see people go from average time the schedule of four days to 30 minutes and just some really big change in those where they can then point to a win, go to get more money and say, let's continue to automate and use AI in that.

(20:49):

So I think we'll continue to see lots of wins in discreet single problems. My hope is that we'll start to rethink some processes more deeply and think about how we can change the way that talent acquisition operates. I think it'll take some certain industries and some certain problem sets to find some of that creative thinking in that. But I fully expect 2024 again to be a more with less kind of a year where recruiters are feeling strapped and they're looking for tools like AI that can help and can help them have more of those meaningful conversations that they're looking to have.

Matt Alder (21:24):

Adam Yael, thank you very much for talking to me.

Introduction (21:27):

Thank you.

Adam Godson (21:28):

Thanks Matt. Good talk as always.

Matt Alder (21:31):

My thanks to Adam and Yael. If you're a fan of the Recruiting Future podcast, then you will absolutely love our monthly newsletter Recruiting Future Feast. Not only does it give you the inside track on what's coming up on the show, you can also find everything from book recommendations to insightful episodes from the archives and get first access to new content that will help you understand where our industry's heading. For a limited time, subscribe to the Recruiting Future Feast newsletter and get instant access to the video recording of the recent remixed webinar on AI and talent acquisition featuring some of the smartest thinkers in the industry. Just go to Matt alder.me/webinar to sign up. That's matt alder.me/webinar. You can subscribe to this podcast on Apple Podcasts on Spotify or via your podcasting app of Joyce. You can find and search all the past episodes@recruitingfuture.com. And don't forget to sign up for the newsletter Recruiting Future Feast. Thanks very much for listening. I'll be back next time and I hope you'll join me.

Introduction (22:47):

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